1996-Solution growth of silicon on multicrystalline Si substrate--Growth velocity, defect structure
氧沉淀对p型硅的少子寿命的影响
JOURNAL OF APPLIED PHYSICS 110, 053713 (2011)
The effect of oxide precipitates on minority carrier lifetime in p-type silicon
J. D. Murphy,1,a) K. Bothe,2 M. Olmo,3 V. V. Voronkov,4 and R. J. Falster1,3
The formation of oxide precipitates is complicated by the morphological transformation they undergo as they grow.16,17 One study has focused on this transformation with
a)Author to whom correspondence should be addressed. Electronic mail: john.murphy@.
高分子材料学经典教材
多分散性的描述：分布曲线法、分散系数HI法。
▲常见三大合成材料的相对分子质量范围
塑料
高密度聚乙烯 聚氯乙烯 聚苯乙烯 聚碳酸酯
相对分子质量
6～30万 5～15万 10～30万 2～6万
橡胶
天然橡胶 丁苯橡胶 顺丁橡胶 氯丁橡胶
从上面所叙述材料的发展可 以看到，科学发展是无止境的， 一时的满足和安于现状就会导致 落后，不断进取、不断创新才更 有所作为。
人类需求是推动科学发展的 动力。
绪论
一、高聚物的基本概论 ●高聚物
高聚物（high polymer）是高分子化合物（macromolecular compound）的简称，是由 成千上万个原子通过化学键连接而成的高分子（macromolecule）所组成的化合物。
第一章：绪 论 高分子材料学简介
人类的文明史=材料的发展史
材料包括： 金属材料 无机非金属材料
有机高分子材料
复合材料
INTRODUCTION
• Advancement in technology is directly associated with the development of new materials
Man-made (Synthetic) Macromolecules
1839 Elastic property improvement of natural rubber by vulcanization
1870 Commercialization of celluloid (75% cellulose nitrate + 25% camphor)
硅氧烷化合物的合成与应用进展
材料工程Journal of Materials Engineering第4 9卷 第4期2021年4月 第13-22页Vol. 4 9 No. 4Apr. 2021 pp. 13 — 22硅氧烷化合物的合成与应用进展Research progress in synthesis andapplication of siloxane compounds程玉桥，路双，冯喆，赵文辉，张治婷，赵越(天津工业大学化学与化工学院，天津300387)CHENG Yu-qiao ,T/U Shuang ,FENG Zhe,ZHAO Wen-hui ,ZHANG Zhi-t.ing,ZHAO Yue(School of Chemistry and Chemical Engineering ,TiangongUniversity? Tianjin 300387 , China)摘要：基于硅氧键特点以及不同条件的化学反应是构建结构迥异、性能独特的新型有机/无机硅氧功能材料的重要方法，近年来，引起了学术界的普遍关注。
新型硅氧功能材料兼具有机/无机化合物性质，以其良好的生物相容性、耐高低 温性以及电绝缘性能被广泛应用于众多领域。
本文综述了硅氧烷化合物设计、合成与应用的研究领域及发展现状，重点 介绍线性结构(一维结构)、非线性结构(二维结构)、多面体低聚倍半硅氧烷化合物(三维结构)以及有机/无机杂化硅氧烷化合物的设计及合成方法，并通过研究可拉伸聚硅氧烷弹性体、硅氧烷化合物涂层、新型驱油用硅氧功能材料等多种方式以增进硅氧烷化合物在生物医学、航空航天、功能材料及三次采油方面的应用进展。
关键词：线性结构；非线性结构；多面体低聚倍半硅氧烷；有机/无机杂化硅氧烷化合物；合成方法doi ： 10. 11868/. issn. 1001-4381.2020. 000125中图分类号：O613.72文献标识码：A 文章编号：10014381(2021)04-0013-10Abstract ： Chemical reactions based on the characteristics of silicon-oxygen bonds and differentconditions are important methods to construct new organic/inorganic siloxane functional materialswith very different structures and unique properties , which have aroused widespread attention in the academic community. The new silicon-oxygen functional materials have both organic/inorganic compound properties , and are widely used in many fields for their good biocompatibility , high and lowtemperature resistance , and electrical insulation properties. The research fields and developmentstatus of the design , synthesis and application of siloxane compounds were reviewed in this paper , focusing on the design and synthesis methods of linear structure (one-dimensional structure ),nonlinear structure (t.wo-climensional structure ) , polyhedral oligomeric silsesquioxane compounds (three-dimensional structure) and organic/inorganic hybrid siloxane compounds , and the application progress of siloxane compounds in biomedicine , aerospace , functional materials and tertiary oilrecovery will be promoted by studying stretchable polysiloxane elastomer , siloxane compound coating , new silicone functional materials for oil displacement and so on.Key words : linear structure ； nonlinear structure ； polyhedral oligomeric silsesquioxane ； organic/inorganic hybrid siloxane compounds ;synthesis method随着材料科学的不断发展，硅氧烷化合物因其良 好的耐热性、生物相容性、高透气性和高绝缘性能在诸 多领域占据着重要地位。
半导体碳化硅衬底的湿法氧化
第53卷第2期2024年2月人㊀工㊀晶㊀体㊀学㊀报JOURNAL OF SYNTHETIC CRYSTALS Vol.53㊀No.2February,2024半导体碳化硅衬底的湿法氧化鲁雪松1,2,王万堂1,2,3,王㊀蓉1,2,杨德仁1,2,皮孝东1,2(1.浙江大学材料科学与工程学院,硅及先进半导体材料全国重点实验室,杭州㊀310027;2.浙江大学杭州国际科创中心,先进半导体研究院和浙江省宽禁带功率半导体材料与器件重点实验室,杭州㊀311200;3.浙江大学电气工程学院,杭州㊀310027)摘要:半导体碳化硅(4H-SiC)材料具有硬度高㊁脆性大㊁化学性质稳定等特点,一般使用化学机械抛光工艺来加工4H-SiC 以获得超光滑平坦表面㊂湿法氧化作为单晶4H-SiC 化学机械抛光的重要过程,直接影响着化学机械抛光的速率和表面质量㊂本文综述了目前单晶4H-SiC 湿法氧化的研究现状,讨论了4H-SiC 湿法氧化工艺所选用的氧化剂,如KMnO 4㊁H 2O 2㊁K 2S 2O 8等㊂在此基础上,进一步总结了常用的氧化增效方法,如光催化辅助氧化㊁电化学氧化㊁芬顿反应等,并从理论计算的角度分析了单晶4H-SiC 湿法氧化的机理,最后展望了4H-SiC 湿法氧化未来的研究方向㊂关键词:碳化硅;半导体;加工;湿法氧化;化学机械抛光;材料去除率中图分类号:TN305㊀㊀文献标志码:A ㊀㊀文章编号:1000-985X (2024)02-0181-13Wet Oxidation of Semiconducting Silicon Carbide WafersLU Xuesong 1,2,WANG Wantang 1,2,3,WANG Rong 1,2,YANG Deren 1,2,PI Xiaodong 1,2(1.State Key Laboratory of Silicon and Advanced Semiconductor Materials,School of Materials Science and Engineering,Zhejiang University,Hangzhou 310027,China;2.Institute of Advanced Semiconductors &Zhejiang Provincial Key Laboratory of Hangzhou Innovation Center,Zhejiang University,Hangzhou 311200,China;3.College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China)Abstract :Semiconducting silicon carbide (4H-SiC )exhibits characteristics of high hardness,notable brittleness,and excellent chemical stability.The commonly employed technique for achieving an ultra-smooth and flat surface is chemical mechanical polishing (CMP),which is utilized to process the 4H-SiC surface.Wet oxidation,as an important process of chemical-mechanical polishing of single-crystal 4H-SiC,directly affects the rate and surface quality of CMP.This paper provides a comprehensive overview of the current research status of wet oxidation of single-crystal 4H-SiC.It discusses the oxidants used in the wet oxidation of 4H-SiC,such as KMnO 4,H 2O 2,K 2S 2O 8.Based on this,it further summarizes commonly employed oxidation-enhancement methods,including photocatalytic-assisted oxidation,electrochemical oxidation,and Fenton reaction.The mechanism of wet oxidation of single-crystal 4H-SiC is analyzed from the aspect of theoretical calculation,and the future research direction of wet oxidation of 4H-SiC is proposed.Key words :silicon carbide;semiconductor;processing;wet oxidation;chemical mechanical polishing;material remove rate ㊀㊀收稿日期:2023-06-25㊀㊀基金项目:国家自然科学基金(62274143,62204216);浙江省 尖兵 领雁 研发计划(2022C01021,2023C01010);杭州市领军型创新创业引进培育计划(TD2022012);中央高校基本科研经费(226-2022-00200)㊀㊀作者简介:鲁雪松(1999 ),男,江苏省人,硕士研究生㊂E-mail:1264180612@ ㊀㊀通信作者:王㊀蓉,博士,研究员㊂E-mail:rong_wang@ 皮孝东,博士,教授㊂E-mail:xdpi@ 0㊀引㊀㊀言半导体碳化硅(4H-SiC)材料具有宽禁带㊁高饱和电子漂移速率㊁高临界击穿电场㊁高热导率等优异性能[1-2],已在高频和高功率电子器件㊁新能源汽车㊁智能电网等领域展现出广阔的应用前景㊂随着4H-SiC 应用的推进,人们对4H-SiC 衬底的表面质量提出了越来越高的要求,实现原子级平整和降低表面㊁亚表面损伤成为4H-SiC 衬底加工的首要目标㊂182㊀综合评述人工晶体学报㊀㊀㊀㊀㊀㊀第53卷图1㊀4H-SiC 晶圆的CMP 装置示意图[3]Fig.1㊀Schematic diagram of CMP apparatus for 4H-SiC wafer [3]4H-SiC 衬底的加工过程包括平磨㊁滚圆㊁线切㊁研磨和化学机械抛光(chemical mechanical polishing,CMP)㊂CMP 作为4H-SiC 衬底加工的最终工序,对于4H-SiC 衬底表面质量具有决定性的作用㊂如图1所示[3],CMP 首先利用氧化剂使衬底表面形成质地较软的氧化层,然后通过机械作用去除氧化层以重新暴露衬底表面,并使其再次与氧化剂发生氧化反应,从而实现化学氧化-机械去除的交替作用,最终得到原子级平整的光滑表面㊂研究表明,湿法氧化过程是决定4H-SiC衬底CMP 加工效率的重要因素[4]㊂因此,深入理解4H-SiC 的湿法氧化机理并提升4H-SiC 的湿法氧化速率,是提升4H-SiC 表面质量和CMP 加工效率的重要基础㊂本文以4H-SiC 的湿法氧化为主题,讨论了目前4H-SiC 湿法氧化中氧化剂的选择㊁氧化机理㊁工艺参数的调整㊁增效方法的选用等方面的研究进展,展望了为提高CMP 过程中4H-SiC 的湿法氧化效率,进而提高CMP 过程中的材料去除速率和表面质量而开展的研究㊂1㊀4H-SiC 湿法氧化的氧化剂及其在CMP 中的应用早在1999年,研究人员就尝试将多晶SiC 浸入不添加任何磨料的氧化剂溶液中[5]㊂他们使用材质为氮化硅和铸铁的抛光盘,分别测试了SiC 在高锰酸钾(KMnO 4)㊁双氧水(H 2O 2)㊁三氧化铬(CrO 3)溶液中的抛光效果,其中浓度(质量分数)为3%CrO 3的浆料抛光速率最高,为4.2ˑ10-6mm 3/(N㊃m),20%H 2O 2(体积分数)和5%KMnO 4(质量分数)的抛光速率分别为1.1ˑ10-6和1.2ˑ10-6mm 3/(N㊃m),可见氧化剂的种类和浓度对于SiC 的抛光速率有着重要影响㊂1.1㊀高锰酸钾高锰酸钾(KMnO 4)具有强氧化性,是4H-SiC 衬底CMP 的常用氧化剂㊂目前,业界以KMnO 4和α-Al 2O 3分别作为4H-SiC 衬底CMP 的湿法氧化剂和磨粒,在pH =8~10时,材料去除速率(material remove rate,MRR)可达到1~1.5μm /h,得到的4H-SiC 衬底的表面粗糙度为0.2~0.5nm㊂有研究者将KMnO 4和α-Al 2O 3混合制备抛光浆料[6],利用HNO 3调节浆料pH 值为3,对4H-SiC 的Si 面进行CMP 实验,获得的MRR 为0.98μm /h,表面粗糙度Ra 为0.235nm㊂同时对不同浓度KMnO 4溶液进行对比试验,发现0.3%(质量分数,下同)的KMnO 4可以大幅提高4H-SiC 的MRR㊂此外,实验对于KMnO 4的浓度和浆料pH 值进行了详细探究,结果显示当KMnO 4浓度为6.5%㊁浆料pH 值为2时,4H-SiC 衬底的MRR 为1.4μm /h,粗糙度从0.425nm 下降至0.105nm,原因归结为高锰酸钾溶液在酸性条件下具有更强的氧化性㊂利用 Al 2O 3+KMnO 4 体系除了可以对常规的掺氮导电型SiC 衬底进行CMP,同样可以用于加工高纯半绝缘SiC 衬底㊂研究发现,向抛光液中加入一定量的硝酸铁(Fe(NO 3)3)可以有效提高对半绝缘4H-SiC 的MRR [7]㊂实验结果表明,添加0.5%的硝酸铁可使MRR 提高34%,粗糙度由0.123nm 降至0.110nm,同时抛光浆料的摩擦系数(coefficient of friction,COF)得到有效降低,推测硝酸铁的加入使SiC 晶圆表面形成的氧化层更加柔软,从而增强了氧化铝颗粒的犁耕效果㊂除了Al 2O 3磨粒,也有研究采用SiO 2胶体作为磨料[8],饱和KMnO 4溶液作为氧化剂,通过KOH 和HNO 3调整抛光液的pH 值为3~4,探究并寻找合适的抛光液流量㊁抛头转速㊁抛光压力㊁抛光时间等工艺参数,最终在抛头转速35r /min㊁抛光头转速22r /min㊁抛光压力250g /cm 2㊁抛光液流量7.6mL /min㊁抛光时间8h 时,得到了粗糙度为0.099nm 的超光滑4H-SiC Si 面㊂除了在4H-SiC 衬底CMP 中常用的Al 2O 3和SiO 2胶体磨料,还有一些其他种类的磨料也被应用于KMnO 4体系中㊂例如以KMnO 4为氧化剂,分别使用SiO 2和CeO 2作为磨料,对6H-SiC 的Si 面进行抛光[9]㊂结果表明,以 2%CeO 2+0.05mol /L KMnO 4 为组分的抛光液的MRR 为1.089μm/h,高于以 6%SiO 2+0.05mol /L KMnO 4 为㊀第2期鲁雪松等:半导体碳化硅衬底的湿法氧化183㊀图2㊀锰的pH 值与氧化还原电位(E )的关系图[11]Fig.2㊀pH value versus E diagram of manganese [11]组分的MRR(0.185μm /h)㊂推测在SiC 的CMP 过程中,CeO 2颗粒和氧化物层之间会形成化学齿(Si OCe 键)[10],增大磨料与SiC 表面的粘附力,进而提高CMP 时的摩擦力,使得以CeO 2作为磨料的抛光液获得了更高的MRR㊂此外,一些研究者也尝试使用MnO 2为磨料[11],KMnO 4作为氧化剂,在300kPa 的N 2氛围下对4H-SiC 进行CMP,MRR 为243nm /h,高于使用 H 2O 2+MnO 2 体系的57nm /h 和仅使用MnO 2的26nm /h,这表明KMnO 4氧化剂对提高MnO 2的抛光效率具有显著作用㊂此外,如图2所示,选用MnO 2作为磨料的独特之处在于,MnO 2在高pH 区会部分转变为MnO -4,这使得磨料本身也会参与氧化反应,提高了氧化速率,进而获得更高的MRR㊂1.2㊀双氧水双氧水(H 2O 2)作为常用的绿色氧化剂,凭借其氧化性强,分解产物无毒等优势在CMP 领域得到了广泛运用㊂H 2O 2作为氧化剂提高4H-SiC 衬底MRR 的原理为[12]㊀2H 2O 2ң2H 2O +O 2(1)H 2O 2ң2㊃OH (2)SiC +4㊃OH +O 2ңSiO 2+2H 2O +CO 2(3)SiO 2+2OH -ңSiO 2-3+H 2O (4)如式(1)所示,在室温下,H 2O 2通常可以分解为H 2O 和O 2㊂根据式(2),在CMP 过程中,H 2O 2还会因外界压力㊁晶片和抛光垫之间的摩擦力,以及摩擦运动所产生的瞬态热而分解为羟基自由基㊂4H-SiC 衬底表面会在羟基自由基和氧气的作用下被氧化为质地更软㊁更易被去除的SiO 2(见公式(3)),并与碱性环境下大量存在的OH -反应生成可溶性的SiO 2-3(见公式(4))㊂这也解释了为什么H 2O 2的加入会显著提高4H-SiC 衬底的MRR㊂Pan 等[12]使用浓度为0~10.5%的H 2O 2作为氧化剂,平均粒径为100nm 的胶体SiO 2作为磨料,利用氢氧化钾(KOH)和单乙醇胺(MEA)调节抛光液pH 值,使用聚氨酯抛光垫进行1h 的抛光实验㊂实验结果表明,当抛光浆料中不含H 2O 2时,4H-Si 的Si 面的MRR 几乎为0nm /h;当H 2O 2含量为6%及更高时,MRR 稳定在105nm /h㊂值得注意的是,当浆料成分为30%硅溶胶㊁6%H 2O 2和0.6%KOH 的最优配比时,使用原子力显微镜(AFM)在1μm ˑ1μm 的区域内可以清晰地观察到原子台阶结构(见图3),台阶高度均匀(约0.25nm),对应于6H-SiC 晶体中单层Si 和C 原子的厚度,这种原子台阶结构证实了CMP 的去除机理是以化学反应为主㊂原子台阶也是衡量半导体碳化硅CMP 效果的一个重要指标,Zhou 等[13]专门研究了原子台阶对SiC CMP 的影响㊂研究发现,位于原子台阶边缘的原子比台阶平面上的原子拥有更强的化学活性,因此,原子台阶宽度会影响CMP 的MRR,台阶宽度越小,台阶密度越大,单位面积上位于台阶边缘的原子也就越多,MRR 越高㊂偏8ʎ离轴的SiC 衬底的MRR 是正轴(偏0ʎ)SiC 衬底的两倍,因为其拥有更小的台阶宽度和更大的台阶密度㊂抛光液的pH 值和氧化剂浓度同样会影响湿法氧化速率和表面质量,进而影响CMP 的速率和抛光后的表面平整度㊂有研究者使用胶体SiO 2作为磨料,H 2O 2作为氧化剂,测试了不同pH 值下4H-SiC 的MRR [14]㊂结果表明,4H-SiC 衬底的MRR 由pH =4时的32nm /h 增加到pH =6时的51nm /h,并在pH =8时达到峰值(111nm /h),pH 值进一步增加至10时,MRR 下降到了105nm /h 左右㊂此外,H 2O 2氧化剂浓度对SiC 衬底抛光表面质量也有着重要的影响[15]㊂实验结果表明,在氧化剂浓度从0.0325mol /L 逐步提高到0.225mol /L 时,衬底表面粗糙度逐渐降低,实现了原子级平整,当氧化剂浓度进一步提高到0.3mol /L 时,衬底表面出现局部不平整,产生腐蚀坑,说明此时化学作用强于机械作用,表面可能覆盖有氧化层㊂184㊀综合评述人工晶体学报㊀㊀㊀㊀㊀㊀第53卷图3㊀(a)使用成分为30%硅溶胶㊁6%H 2O 2和0.6%KOH 的浆料抛光所得SiC 晶片的AFM 照片(1μm ˑ1μm 区域);(b)a 1和a 2之间的横截面图像[12]Fig.3㊀(a)AFM image of SiC wafer polished using a slurry composed of 30%silicon sol,6%H 2O 2,and 0.6%KOH (1μm ˑ1μm area);(b)cross-sectional image along the line between a 1and a 2[12]1.3㊀其他氧化剂与KMnO 4和H 2O 2相似,次氯酸钠(NaClO)也具有较强的氧化性,特别是在碱性条件下,NaClO 表现出更强的氧化性,因此也被作为氧化剂应用于碱性SiO 2体系中㊂研究人员对比了SiO 2胶体分别在NaClO 和H 2O 2作为氧化剂时对4H-SiC 衬底Si 面的抛光效果[16],实验结果显示采用10%NaClO(体积分数)和3%H 2O 2(体积分数)获得的MRR 分别为0.073和0.035μm /h㊂进一步向含NaClO 和SiO 2胶体的抛光液中加入金刚石硬质磨料(粒径0.1μm),MRR 显著增加到0.92μm /h,并获得了Ra =0.52nm 的表面粗糙度㊂在另一项研究中[17],向粒径为25nm 的金刚石颗粒和KOH 改性的SiO 2胶体中加入NaClO 氧化剂,材料去除量从加入氧化剂前的0.07mg /h 提高至加入后的0.3mg /h,推测NaClO 不仅参与了SiC 表面的氧化反应,同时增强了SiO 2胶体与SiC 表面的化学反应,形成了更厚的氧化层㊂图4㊀6H-SiC 不同晶面上SiO 2氧化层的角分辨ARXPS 结果和成分示意图[19]Fig.4㊀ARXPS results and composition schematic of SiO 2oxide layer on different crystal planes of 6H-SiC [19]还有一些研究者[5]分别对比了CrO 3㊁H 2O 2和KMnO 4作为氧化剂的MRR 和表面粗糙度,发现CrO 3表现出最好的抛光效果,MRR 可达0.2~0.4μm /h,说明使用CrO 3作为SiC 衬底CMP 氧化剂具有一定的应用前景㊂此外,也有研究者使用过硫酸钾(K 2S 2O 8)作为氧化剂㊁Al 2O 3作为磨料,对6H-SiC 的不同晶面进行CMP 实验,以此来研究SiC 的晶面各向异性对CMP 的影响[18]㊂实验数据表明,C 面MRR 最大可达1184nm /h,远大于Si 面的MRR 最大值(349nm /h)㊂使用XPS 进一步分析抛光表面,发现抛光后Si 面氧化物含量高于C 面,这表明C 面的氧化物比Si 面更易去除㊂Hornetz 等[19]利用过渡氧化层理论解释了这一现象,如图4所示,他认为在SiC 氧化成SiO 2的过程中,SiC 原子层与SiO 2原子层之间存在着一个过渡原子层Si 4C 4-x O 2(x ɤ2),这个过渡层能阻止SiC 进一步被氧化为SiO 2,从而降低SiC 的氧化速率,在Si 面中,这层过渡层厚约1nm,而在C 面中过渡层更薄,这也导致了C 面有更快的氧化速度㊂为了实现超光滑表面,业界用 两步法 实现了SiC 的CMP [20],使用 KMnO 4+Al 2O 3 体系对4H-SiC 衬底进行粗抛,再用 H 2O 2+SiO 2 体系进行精抛㊂实验结果表明,在KMnO 4浓度为6.5%㊁pH =2的情况下,第一步粗抛的MRR㊀第2期鲁雪松等:半导体碳化硅衬底的湿法氧化185㊀可达1400nm/h;在H2O2浓度为10%㊁催化剂V2O5浓度为4%的条件下,第二步精抛速率可达150nm/h,最终表面粗糙度可达0.066nm㊂目前, 两步法 已经在4H-SiC的CMP中得到广泛运用㊂2㊀4H-SiC氧化的机理2.1㊀第一性原理计算第一性原理计算在探究4H-SiC表面氧化机理的研究中起到了重要作用,通过密度泛函理论(density functional theory,DFT)和电子结构计算方法,可以计算碳化硅表面的结构㊁表面能㊁化学键能等物理量,并进一步探究氧化反应的热力学和动力学性质㊂此外,第一性原理计算还可以模拟4H-SiC表面氧化过程中的原子和分子的相互作用和运动,为实验研究提供可靠的理论依据㊂在已有的研究中,研究者通过DFT计算详细分析了Si面和C面的氧化过程[21],发现对于C面,C原子会与吸附O形成CO分子直接从表面解离,而对于Si面而言,在Si原子与外来O原子成键后,相邻亚层C原子相互连接,形成碳纳米簇,以减少悬挂键的数量㊂这揭示了碳化硅Si面和C面氧化行为的差异,从理论上解释了Si面和C面氧化速率不同的可能原因㊂此外,通过DFT计算可以研究4H-SiC C面和Si面的初始氧化过程[22]㊂计算表面能结果表明,即使在O覆盖率低的表面上,C面的C原子会优先形成CO分子脱附,而在Si面上O原子的吸收则优先发生㊂此外,在C面上,可以在SiC表面的最顶层形成三配位O原子,从而形成特征不同于Si面上的SiO2类层(见图5)㊂这些发现表明,C面和Si面之间碳解吸行为的差异以及形成的SiO2层的结构差异可能是SiC表面氧化速率各向异性的原因㊂图5㊀4H-SiC C面上O结合表面的典型构型的侧视图(a)和Si面上O结合表面的典型构型的侧视图(b),其中橙色㊁绿色㊁红色分别代表Si㊁C㊁O原子[22]Fig.5㊀Side view of the typical configuration of O-bound surface on the C-face of4H-SiC(a)and the side view of thetypical configuration of O-bound surface on the Si-face of4H-SiC(b),where the orange,green,and red colorsrepresent Si,C,and O atoms,respectively[22]利用周期DFT和反射高能电子衍射(RHEED)动态摇摆梁[23],分析研究了氧分子吸附后SiC表面上的各种可能的化学吸附状态(见图6),计算显示O2分子在最顶端的原子簇位点上发生解离吸附,首先第一个O2分子吸附形成SiO2,然后第二个O2分子进一步吸附形成SiO4基团,后续第三和第四个O2分子将吸附于如图6(b)中所示的adlayer位置㊂研究结果为探索氧化过程中氧气吸附和扩散机理提供了一定的指导㊂2.2㊀分子动力学模拟分子动力学模拟在SiC表面氧化研究中具有较好的研究前景,因为它可以提供高分辨率的结构和动力学信息,且可以模拟大尺度㊁长时间尺度的反应过程,从而揭示氧化反应的机理与动力学行为㊂基于分子动力学模拟的方法,可以采用反应力场(ReaxFF)分析SiC不同取向晶面早期阶段的氧化行为[25],从模拟结果中获得氧化物厚度和生长速率㊂模拟发现在氧化过程中,从SiC表面溢出的C物质浓度是Si的3倍,C面具有最高的氧化速率,其次是m面㊁a面和Si面㊂这一结果与第一性原理计算结果和实验事实相符㊂在此基础上,Newsome等[26]使用ReaxFF对暴露于O2和H2O分子的SiC表面的初始氧化过程进行模拟㊂结果表明,SiC逐渐在O2和H2O的作用下转变为硅的氧化物,同时形成类似石墨的层㊂在过量O2的存在下,类石墨186㊀综合评述人工晶体学报㊀㊀㊀㊀㊀㊀第53卷层被进一步氧化为CO和CO2㊂研究还分析了两个原子和三个原子簇的轨迹,发现Si O和C C键的形成是以O O和Si C键消耗为代价的,表明SiC氧化同时会形成碳团簇结构㊂图6㊀6H-SiC(0001)3ˑ3表面的顶视(a)和侧视(b)图[23](基于Starke的扭转Si adlayer模型[24]),黑㊁白㊁灰分别对应处于不同层级的Si原子Fig.6㊀Top(a)and side(b)view of6H-SiC(0001)3ˑ3surface[23](based on Starke s twisted Si adlayer model[24]), where black,white,and gray correspond to Si atoms located at different layers单晶SiC由于具有晶面各向异性,其Si面和C面的物理㊁化学性质,以及氧化和去除机理都有显著差别,有研究使用基于ReaxFF的分子动力学模拟,对6H-SiC在2100K下的Si面和C面抛光过程分别进行了模拟[27]㊂使用金刚石板模型在一定载荷下对处于H2O体系中的C面和Si面进行接触和摩擦㊂如图7所示,随着摩擦过程中温度逐渐升高,SiC的表面会与H2O发生反应,C面反应产物的主要成分是无定形氧化硅,而Si面反应产物的主要成分是结晶二氧化硅㊂6H-SiC的C面材料比Si面材料氧化速度快,导致相同条件下C面MRR大于Si面㊂图7㊀6H-SiC的Si面和C面与H2O分子的界面反应示意图[27]Fig.7㊀Schematic diagram of the interfacial reaction mechanism between the Si-face and the C-face of6H-SiC with H2O molecules[27]㊀第2期鲁雪松等:半导体碳化硅衬底的湿法氧化187㊀3㊀湿法氧化的增效方法3.1㊀光催化辅助氧化除了使用传统氧化剂实现4H-SiC衬底表面氧化,研究者还开发了一系列增效方法来提高氧化剂的氧化效率,从而获得更高的MRR和表面平整度㊂光催化辅助CMP(PCMP)主要是利用紫外光照射光催化剂(如TiO2),在光催化反应过程中产生的羟基自由基可以增强氧化效率,从而提高CMP的速率[28](见图8)㊂在PCMP过程中,电子和空穴在紫外光的照射下被激发到TiO2的导带(CB)和价带(VB)[29]㊂然后,光生电子和空穴扩散到TiO2的表面㊂O2和H2O2的电子捕获剂可以有效地捕获电子,分别产生具有强氧化性的O-2和㊃OH等活性氧化物(ROS)㊂值得注意的是,TiO2表面的光生电子和空穴并不稳定,极易因复合而使光催化反应结束㊂ROS作为氧化性极强的物质,提高其产生的效率有利于改善4H-SiC的氧化,从而提高CMP的效率[30]㊂图8㊀光催化辅助CMP原理图[28]Fig.8㊀Schematic diagram of photocatalytic-assisted CMP[28]有研究者通过测量氧化还原电位(oxidation reduction potenital,ORP)和静态氧化实验[31],探究了光催化剂㊁紫外光㊁电子捕获剂和pH环境对PCMP工艺的影响㊂在紫外光照射下,含有1g TiO2㊁0.3g(NaPO3)6㊁10mL H2O2和5g SiO2磨料的PCMP浆料的MRR最高(0.95μm/h),表面粗糙度最低(Ra=0.35nm)㊂此外,研究者还对其中的原理进行了探究,在PCMP的过程中,表面产生了Si C O㊁Si O㊁C O和C O 等㊂在紫外光照射下,TiO2颗粒表面产生羟基自由基,并流入SiC衬底和抛光垫之间的界面[32]㊂H2O2主要通过在紫外光照射下产生羟基自由基来氧化SiC㊂可能的相关反应为[33]TiO2+hνңh++e-(5)h++H2OңH++OH(6)H2O2+hνңH2O+O2(7)e-+O2ңO-2(8)O-2+H2O2ңOH+OH-+O2(9)SiC+4OH+O2ңSiO2+2H2O+CO2(10)H++OH-ңH2O(11)为探究影响PCMP效果的主要因素,有研究者探究了光照强度㊁H2O2浓度㊁TiO2浓度和pH值等因素对188㊀综合评述人工晶体学报㊀㊀㊀㊀㊀㊀第53卷紫外光催化反应速率的影响[34],并对四个因素进行了正交实验,通过测试ORP表征光催化反应速率㊂实验结果表明,H2O2浓度对光催化反应速率的影响最大,当H2O2浓度小于4.5%时,ORP随H2O2浓度增大而增大,当H2O2浓度超过4.5%时,ORP几乎不再随之增长㊂同时,研究还发现碱性环境下的ORP高于酸性环境的,这是因为碱性环境体系中存在大量OH-,它可以作为电子捕获剂参与光催化反应,从而生成更多具有强氧化性的羟基自由基㊂除了上述几个影响PCMP的主要因素,紫外光的照射位置也会对MRR产生一定影响[35]㊂实验结果表明,光照抛光液的MRR明显高于光照抛光盘的,推测是因为使用光照抛光盘的方式时,抛光液和紫外光接触时间过短(小于3s),光催化反应未能充分进行㊂为了改善光催化性能,使光催化反应充分进行,除了将光催化剂作为添加剂加入抛光液中进行CMP,还可以使用喷涂技术将表面改性的TiO2颗粒添加到聚氨酯(PU)抛光垫基质中,制备出TiO2光催化固结抛光垫[36]㊂实验对比了使用传统抛光垫和TiO2光催化固结抛光垫的抛光效果,数据表明,随着抛光垫中TiO2浓度的增加,MRR最高可达到约200nm/h,远高于使用传统抛光垫的100nm/h㊂同时,与传统抛光垫相比,使用光催化剂固结抛光垫进行CMP后的SiC衬底表面可以观察到明显的原子台阶结构(见图9),粗糙度也从0.1120nm降低至0.0539nm,展现了光催化剂固结抛光垫在半导体碳化硅CMP加工中的优势㊂图9㊀使用不同抛光垫在紫外光下对SiC研磨片Si面进行5h抛光后的AFM照片(1μmˑ1μm区域)[36]㊂(a)传统抛光垫,Ra:0.1120nm;(b)光催化剂固结抛光垫,Ra:0.0539nmFig.9㊀AFM images of polished Si-face SiC wafer surface by different pads under UV light(1μmˑ1μm area)for5h polishing from the original ground wafer[36].(a)Conventional pad,Ra:0.1120nm;(b)photo-catalystincorporated pad,Ra:0.0539nm值得一提的是,硫酸根自由基(SO㊃-4)的ORP(2.60~3.10V)高于㊃OH的(1.90~2.70V),且SO㊃-4的寿命(30~40μs)高于㊃OH(ɤ1μs)[37-38]㊂因此,基于硫酸根自由基的先进氧化工艺(SR-AOPs)有望提高PCMP的效率㊂Wang等[39]利用紫外和TiO2的协同作用激活过硫酸钾(K2S2O8),发现MRR和表面粗糙度[Sq(均方根偏差)]分别为608nm/h和0.521nm㊂基于SR-AOPs提高CMP效率的机理总结为SiC+2SO㊃-4+2㊃OH+O2ңSiO2+CO2ʏ+2SO2-4+2H+(12) PCMP可以提高MRR并保持优异的表面质量[31,40-42]㊂此外,PCMP仅需要添加紫外光源,无须对现有CMP设备进行结构修改或增加复杂的设备㊂因此,PCMP在现有CMP工艺中的应用具有巨大的潜力㊂然而,该方法仍存在一些挑战㊂首先,需要保证光催化剂在浆液中的分散性㊂PCMP过程通常使用纳米粒子作为光催化剂,这些纳米粒子在水相中容易发生团聚,导致光催化效率降低,因此需要进一步改善光催化纳米粒子在浆液中的分散稳定性㊂其次,需要解决经过长时间紫外光照射的抛光垫的性能退化问题㊂最后,长时间紫外灯照射产生的热量可能会影响抛光浆的性能,需要进行进一步研究㊂3.2㊀电化学辅助氧化电化学机械抛光(electrochemical mechanical polishing,ECMP)工艺在金属层(如Cu㊁W和Al)的CMP中被广泛研究和应用[43]㊂等离子体电化学氧化(PECO)技术目前已经应用到SiC的表面氧化上[44],如图10所示,将SiC连接阳极使其表面带正电,电解液中的O2在电场作用下与OH-反应生成氧等离子体O2-,并被㊀第2期鲁雪松等:半导体碳化硅衬底的湿法氧化189㊀SiC表面吸引而聚集,进而发生氧化反应㊂通过能量色散光谱(EDS)和X射线光电子能谱(XPS)分析,证明SiC表面已被氧化为SiO2,并且在SiO2和SiC之间形成了过渡层(SiCO x)㊂PECO实验结果表明,该方法是一种可行且有效的氧化SiC表面的方法,对于SiC的CMP有很好的应用前景㊂图10㊀SiC-溶液界面和O2-的形成[44]㊂(a)SiC-溶液界面;(b)O2-在SiC表面的聚集;(c)O2-的形成Fig.10㊀SiC-solution interface and formation process of O2-[44].(a)SiC-solution interface;(b)aggregation of O2-onSiC surface;(c)formation of O2-影响ECMP的因素有很多,包括pH值㊁氧化剂种类和浓度㊁外加电场等㊂研究人员[45]使用电化学工作站对4H-SiC进行ECMP,探究了4H-SiC在不同pH值㊁不同氧化剂及其浓度下的腐蚀电位和腐蚀电流,并通过CMP实验验证不同条件下的抛光效果㊂结果表明,选用20%SiO2为磨料,在5%H2O2㊁pH=12的条件下可以获得285.7nm/h的Si面去除速率㊂此外,研究还发现NaNO3的加入能明显抑制C面的MRR,但能提高Si面的MRR,从而缩小Si面和C面的去除速率差,这对于SiC衬底双面抛光工艺的优化具有借鉴意义㊂Deng等[46-47]研究了芬顿反应在ECMP中的应用,并分析了电芬顿反应(EF反应)的增强机理㊂结果表明,外加电场显著提高了氧化活性(总㊃OH浓度)和抛光效果㊂当H2O2浓度为5.0%,外加电压从0.0V增加到1.5和3.0V时,氧化活性分别增加了133.47%和196.24%,COF分别增加了9.05%和13.36%,MRR分别提高了32.26%和65.59%㊂电场的应用促进了Fe3+向Fe2+的转化,使EF反应比传统芬顿反应生成更多㊃OH,显著提高了抛光浆料的氧化活性,增强了SiC的氧化和抛光效果㊂3.3㊀芬顿反应近年来,芬顿反应因其可以凭借H2O2与Fe2+反应产生强氧化性的羟基自由基(㊃OH)而受到广大研究者的关注和应用,研究一致认为影响芬顿反应的因素有Fe2+浓度㊁pH值㊁H2O2浓度㊁温度㊁溶解氧浓度㊁有机溶液种类等[48-49]㊂实验表明,过量的Fe2+(FeSO4ȡ0.03%)和过高的pH值(pHȡ5)会导致形成絮凝复合物或沉淀物,而过量的H2O2(H2O2ȡ10%)可能会捕获反应中产生的㊃OH,降低CMP效率[50]㊂通过使用含有0.02%FeSO4和5%FeSO4的芬顿试剂,在pH=3的H2O2中产生了高浓度的㊃OH,显著提高了SiC衬底的抛光质量,获得了Ra=0.1869nm的光滑表面㊂此外,有研究者比较了芬顿反应中不同催化剂的催化效果及其对SiC衬底晶圆CMP的影响[51],并使用Fe3O4催化剂获得了粗糙度为0.47nm的SiC衬底光滑表面㊂通过XPS分析芬顿反应CMP前后SiC表面成分的变化,实验人员总结出基于芬顿反应的SiC衬底CMP工艺原理[52]:在SiC衬底的抛光表面上,大量C Si和C C键被暴露并形成悬空键,这些键很容易被通过外界反应而重建或移除㊂如图11所示,芬顿反应溶液在Fe3O4的催化下进行反应,生成Fe2+和Fe3+㊂其中Fe2+与H2O2发生芬顿反应,产生强氧化剂㊃OH,破坏了C Si和C C键㊂接着,SiC表面与反应溶液中的溶解氧(O2)接触,Si原子与O原子反应生成Si O2键(即SiO2氧化物层),同时,C原子与O原子结合产生C O 键(气态CO2)㊂Fe3+与H2O2连续反应生成Fe2+,使整个反应连续进行㊂芬顿反应的催化效率和浆料稳定性会受到浆料pH值的影响㊂当浆料pH值高于3时,Fe2+会转化为。
Gate Oxide Reliability Physical and Computational Models
2
Andrea Ghetti
Gate Source in
n+ channel p-substrate
Fig. 1. Schematic structure of a n-MOS transistor
dioxide lose its insulating properties (breakdown) as it is applied (dielectric strength). Obviously, MOS devices operate at lower field. However, if a lower electric field is applied for a long enough time, the oxide slowly degrades (wear out), and eventually breaks down anyway. This phenomenon called time dependent dielectric breakdown (Tddb) is an important parameter for MOS device reliability and it is the object of this Chapter. Usually, time dependent dielectric breakdown is divided in two categories: extrinsic and intrinsic breakdown. Breakdown is defined intrinsic when it is related only to the oxide structure, while it is extrinsic when it is due to defects that can be present because of the many technological steps needed to make an IC. Extrinsic and intrinsic breakdown have different characteristics, and, usually, are characterized in different ways. However, with the continuous reduction of the oxide thickness and increase of the electric field, intrinsic breakdown has become the most likely problem as far as oxide reliability is concerned. In summary, this Chapter is focused on the intrinsic reliability of the gate oxide of MOS devices. Intrinsic oxide reliability is a very complex matter to tackle. There are still many phenomena to be understood. A number of models have been proposed to explain some of the feature of oxide breakdown, but a comprehensive model is still lacking. In this Chapter, we will review the main physical models that have been proposed about intrinsic oxide breakdown. We will try to show pros and cons of each model, possible computational implementation or practical methodology to predict oxide breakdown they enable, and what it is still missing. This Chapter is arranged as follows. Section 2 details the concept of reliability applied to gate oxide in the microelectronics industry, also introducing the essential elements that are common to all reliability models. Sections 3,4,5 describe in details these elements. In particular, Sect. 5 addresses also the issue of the reliability projection provided by the different models. The different types of breakdown are discussed in Sect. 6. Finally, Sect. 7 draws some conclusions.
Wafer Fabrication
Wafer FabricationFor more info, Please visit the following websites:http://www.leb.e-technik.uni-erlangen.de/lehre/mm/html/start.htmJust copy it from the websites.The first step in wafer production is the fabrication of a silicon single crystal. A small crystal, called the seed crystal, is rotated and slowly withdrawn from the molten hyper-pure silicon to give a cylindrical crystal. The silicon crystal is sliced to obtain thin disks, known as wafers on which chips are made, hundreds at a time, during the following processing. After slicing, the wafers are finely ground, mirror-smooth polished and cleaned.The most common semiconductor material used today is silicon. In addition to silicon, numerous other materials have been studied, and gallium arsenide (GaAs) is used instead of silicon in some applications at present (e.g. high-frequency devices).All processes require extremely clean rooms with filtered air to have a low concentration of particles of dust or other contaminants so that a high chip yield can be attained.Three important steps during crystal fabricationOxidation Processes in SemiconductorManufacturingToday's ULSI technology is to a large extent based on the excellent properties of thermally grown silicon dioxide layers. SiO2 is used as gate dielectric in MOS devices, as implantation or doping mask, and for device isolation purposes.Most of the silicon oxidation processes today are carried out at atmospheric pressure in oxidation furnaces at temperatures between 800 and 1,200°C. Theappropriate oxidant gases are dry oxygen, wet oxygen (water steam). For wet oxidation, the water steam can be extracted by influx of gases (oxygen, argon, or nitrogen) into a vessel filled with water. Another possibility is to initiate a reaction of oxygen and hydrogen at the inlet of the reactor tube. The wafers are placed verticallyor horizontally in quartz boats and the temperature of the hot zone is controlled withan accuracy of 1°C, in order to grow oxide layers in a reproducible manner.It has been proven by a number of experiments that thermal oxidation of silicon proceeds by diffusion of the oxidant through the growing oxide. The oxidation reaction itself takes place at the oxide-silicon interface. During oxidation, theoxide-silicon interface moves into the silicon material as the silicon is oxidized. Taking into account the densities of silicon and of SiO2, it can be shown that about 44% of the oxide layer grows into the silicon substrate. The remaining 56% grows on topof the silicon, resulting in a non-planar surface if oxidation is local.The lateral and vertical isolation of device structures in ULSI determines to a large extent the performance of the technology with respect to packaging density and parasitic effects. Classical local oxidation (LOCOS) has been widely used to laterally isolate the active regions of an integrated circuit. The oxide is grown at those parts of the wafer surface where a Si3N4 masking layer has its openings. Before starting the oxidation there is already a thin oxide layer in between the nitride layer and thesilicon substrate. Because of diffusion of the oxidant into the region below the nitride, also the oxide beneath the nitride is growing leading to the characteristic bird's beak shape after completion of the process. This situation is illustrated in the Figure 1, which shows the result of an oxidation in wet oxygen at 950°C for 10 hours(from: C. Claeys, J. Vanhellemont, G. Declerck, J. Van Landuyt, R. Van Overstraeten, S. Amelinckx, VLSI Science and Technology/1984, K.E. Bean, G. Rozgoni, Eds., The Electrochemical Society, Pennington, 1984, p. 272.).Figure 1: TEM picture of a bird's beak, obtained by using classical LOCOS.Figure 2: Loading of wafers into oxidation furnance.Deposition Processes in SemiconductorManufacturing TechnologyFor the deposition of conducting and insulating materials in semiconductor processing, a wide range of different techniques is used. Among them, physical vapor deposition (PVD) and chemical vapor deposition (CVD) are the most important ones.Materials in semiconductor manufacturing that can be deposited by CVD are for example: Silicon dioxide, silicon nitride, polysilicon, tungsten, copper, titanium nitride, aluminum. the link:Examples for CVD processes.Examples for CVD Processes Used in Semiconductor Manufacturing.Materials in semiconductor manufacturing that can be deposited using PVD are for example: aluminum, titanium, titanium nitride, tantalum, copper.Sputter reactorPrinciple of Physical Vapor Deposition (Sputter Deposition)At low pressure, a voltage is applied to two parallel electrodes resulting in a plasma discharge. The accelerated gas ions impinge onto the cathode (target) and metal atoms are emitted from the target which deposit on the wafer leading to layer growth.Reactor for sputter depositionUsually the conformality (perfect conformality means, that for all positions at the device surface the same layer thickness is achieved) of CVD layers is much better than the conformality of PVD layers. This is demonstrated by the 2 movies: the first one shows a 3D simulation of a sputter deposition of aluminum into a contact hole, the second one shows a 3D simulation of tungsten CVD into the same contact hole. The CVD process yields better layer conformality than the PVD process.The 3D simulations shown in the movies have been carried out using the topography simulator SC-TOP from the software house SIGMA-C. Within SC-TOP, a 3D module for layer deposition developed at FhG-IIS-B is used.Sputter deposition of aluminum(130 kB) Tungsten CVD(121 kB)3D simulation of aluminum sputter deposition in a contact holeBlue: initial surface before depositionGreen: evolving surface of the deposited aluminumIt can be seen that the conformality of the layer is poor, that means the layer thickness inside the contact hole is much smaller than the thickness on top of the structure.3D simulation of tungsten CVD in a contact holeBlue: initial surface before depositionGreen: evolving surface of the deposited tungstenAlthough the conformality is rather good, an enclosed gas volume (so-called void) remains after the opening of the hole is closed by the growing layer.It is also possible to perform simulations on equipment scale. For instance, the temperature distribution in a CVD furnace can be calculated by means of simulation. As an example we show the simulation of the heating of a deposition furnace, carried out with the program PHOENICS-CVD by Cham.Heating of a deposition furnace(356 kB)Lithography in Semiconductor ManufacturingTechnologyLithography is the process of transferring geometric shapes on a mask to the surface of a silicon wafer. These shapes make up the parts of the circuit, such as gate electrodes, contact windows, metal interconnections, an so on. The final integrated circuit (IC) is made by sequentially transferring the features from each mask level by level, to the surface of the silicon wafer. For example, between each successive image transfer an ion implant, drive-in, oxidation, or metallization operation may take place.In the IC lithographic process, a photosensitive polymer film is applied to the silicon wafer, dried, and then exposed with the proper geometrical patterns through a photomask to ultraviolet (UV) or other radiation. After exposure, the wafer is brought into contact (e.g. by dipping or spraying) with a solution that develops the images in the photosensitive material. Depending on the type of polymer used, either exposed (in the case of positive resists) or non-exposed (for negative resists) areas of the film are removed in the developing process. After development the resist acts as a mask, for instance for etching patterns into underlying layers.Resists are made that are sensitive to UV light, electron beams, or ion beams. At present, optical lithography is the prevailing method. In the figure below, an example for the application of resist on the wafer is shown.In the animation below, we show a 3D simulation of the development process of a positive resist layer which has been exposed to light with anwavelength of 365 nm (so called i-line) through a mask with a square opening. Such kind of pattern is used for example to etch contact holes in insulating material underneath the resist. The simulation has been carried out with the lithography simulator SOLID-C which has been developed at FhG and which is commercially available from the softwarehouse SIGMA-C.Start the animation (346 kB)3D simulation of a lithographic development processWe show a 3D simulation of the development process of a positive resist layer which has been exposed to light with an wavelength of 365 nm (i-line) through a mask with a 0.5 micron square mask opening. The wavy shape of the developed resist is due to standing waves which form in the resist during exposure and which lead to significantly varying exposure doses for different depths in the resist layer.Etching Processes in Semiconductor ManufacturingEtching processes are used to partly remove material in order to create patterns to obtain the desired device or interconnect geometry. Particles in the etching component (a liquid or gas) remove material by attacking the open surface.The material may be isotropically removed, known as chemical or "wet" etching, or be etched in a plasma reactor ("dry"-etching). In the case of a dry-etching process, the total etch rate consists of an ion-assisted rate and a purely chemical etch rate due to etching by neutral radicals, which may still have a directional component. The total etch rate can depend on shadowing within the reactor and by the structure on the substrate itself, the angle-dependent flux distribution of particles from the reactor volume, the angle of incidence of the particles relative to the surface normal direction, reflection/re-emission of etching particles, and surface diffusion effects. Reactive ion etching (RIE) provides high anisotropy which is achieved by etching that is enhanced (via different mechanisms) by ions impinging onto the surface. The main advantage of RIE is enhanced directionality which becomes increasingly important as device sizes decrease substantially and etching must proceed in vertical direction without affecting adjacent features.Bench used for wet-etching of 300 mm wafers.In the animation below, we show an etching process where a contact hole is opened by a combination of an isotropic chemical etching step followed by a highly directional RIE step. The process has been simulated by using the program SC-TOP by SIGMA-C.Start the animation (82 kB)Simulation of an etching process to open a contactholeIn the animation shown above, a rotationally symmetric contact hole is etched using a resist layer as mask. What is shown is a slice through the middle of the contact hole.The hole is etched by an isotropic wet-etching step followed by a reactive ion-etching step which is highly directional. The advantage is that it is easier to fill such a contact by metal sputtering than a contact that is created by a directional process only. The reason is that the upper part of the contact (created by the isotropic etch step) is widened so that metal atoms from the reactor volume can better reach positions inside the contact than in the case of a directionally etched contact.Diffusion Processes in Semiconductor TechnologyDiffusion of impurity atoms in silicon during processing is important for the electrical characteristics of silicon devices. Various ways of introducing dopants into silicon by diffusion are used and have been studied with the goals of controlling dopant distribution, total dopant concentration, uniformity, and reproducibility.Diffusion is used to form base, emitter, and collector regions in bipolar device processing, to form source,drain and channel regions, and to dope polysilicon in MOS processing. Dopant atoms that span a wide range of concentrations can be introduced into silicon in many ways. The most commonly used methods are1.Diffusion from a chemical source in a vapor form at hightemperatures,2.Diffusion from a doped-oxide source, and3.Diffusion and annealing from an ion-implanted layer (see ionimplantation).The electrical activation of ion-implanted species is carried out by annealing. This causes a redistribution of the impurity atoms which should be as low as possible. In order to optimize the electrical behavior of the device, it is important to know how the impurities redistribute during the anneal. The development of appropriate models and simulation programs to predict the diffusion is one major topic in semiconductor technology research.Vertical furnace which can be used for diffusion, oxidation,or for chemical vapor deposition (CVD) processes.Below we show several examples of how dopants redistribute during diffusion processes. The simulations have been carried out with the 1D process simulator ICECREM from FhG-IIS-B.You can have a look at the following 1D simulations:Diffusion from a source with constant concentration(144 kB)Diffusion of a shallow profile in a semi-infinite half-space.(141 kB) Redistribution of boron after ion implantation(192 kB)Boron diffusion in oxidizing atmosphere(182 kB)Phosphorus diffusion in oxidizing atmosphere(179 kB)Codiffusion of arsenic and boron(178 kB)Diffusion of boron at high concentrations(148 kB)Ion Implantation Processes in SemiconductorManufacturingIntroductionFor performing ion implantation, atoms or molecules are ionized, accelerated in an electric field and implanted into the target material. A widevariety of combinations of target material and implanted ions are possible. The dose of the implanted ions can vary between 1011 and 1018 cm-2. Usually, the acceleration energy lies between several keV and several hundred keV, but with special equipment it is possible to work with energies up to several MeV. The range of the implanted ions in the substrate depends on the mass of the implanted ions, their energy, the mass of the substrate atoms, crystal structure and the direction of incidence. As an example, the mean range of 100 keV phosphorus ions in silicon is about 150 nm.Main advantages of ion implantation (in comparison to diffusion) for the doping of semiconductors are:Short process times, good homogeneity and reproducibility of the profilesExact control of the amount of implanted ions by integrating the current. This is of particular importance for low concentrations, e.g.for adjusting the threshold voltage of MOS transistorsRelatively low temperatures during the processDifferent materials can be used for masking, e.g. oxide, nitride, metals, and resistImpla ntation through thin layers (e.g. SiO2 or Si3N4) is possibleLow penetration depth of the implanted ions. This allows modification of thin areas near the surface with high concentration gradientsSequences of implantation steps (with different energi e s and doses) allow optimization of the dopant profilesThere are also some disadvantages, such as:Damage of the substrate is caused by the implanted ionsThe change of material properties is restricted to the substrate domains close to the surfaceAdditional effects during or after implantation (such as channeling or diffusion) make it difficult to achieve very shallow profiles and to theoretically predict the exact profile shapes.Depth ProfilesThe larger is the energy of the ions during ion implantation, the deeper penetrate the ions into the target. The ion trajectories are statistically distributed in the target due to the collisions of the ions with the target atoms being affected by partly randomly distributed impact parameters. Therefore not all ions stop at the same depth but there is a certain depth distribution of the ions after ion implantation. The depth distributions of the implanted ions in silicon are presented in the following figures:Energy dependence of depths profiles for boron implantationDose dependence of depths profiles for boron implantationBoron, implantation energy 100 keVEnergy dependence of depths profiles for phosphorus implantationDose dependence of depths profiles for phosphorus implantationEnergy dependence of depths profiles for arsenic implantationDose dependence of depths profiles for arsenic implantationArsenic, implantation energy 100 keVThe maximum of a typical implantation profile in crystalline silicon is mainly formed by the randomly moving ions. At larger depth, a contribution of channeled ions is dominant. The channeling effect is only possible in a crystalline material. For larger implantation doses, the silicon crystal is damaged and channeling becomes less probable. Therefore, the maximum of the doping distribution grows approximately proportional to the dose of implantation while the tail has the tendency to saturate at certain doses. This effect is seen for phosphorus and arsenic ions. For boron, the damage probability is lower and the saturation of the channeling tail is not seen up to doses 5*1015 cm-2 for a conventional 7 degree tilted ion implantation.As you may see in this picture, the heavier is the ion, the shorter is its penetration range at the same energy.Monte-Carlo Method for Simulation of Ion Implantation Since the process of ion implantation has a statistical nature, it is straight-forward to use statistical methods to simulate it on computers. The most important of such methods is the Monte-Carlo method. which is based on the usage of random numbers. Particularly, the position where an ion hits the crystalline target is calculated using random numbers. Furthermore, the atoms of any material are in a permanent movement due to thermal vibrations. The actual positions of the vibrating atoms in the target are also simulated using random numbers. The trajectories of the ion are determined by the interactions of the implanted ions with the target atoms. The final position of an implanted ion is where it has lost its complete energy. As an example we show ion trajectories calculated with the Monte-Carlo method in crystalline silicon:Trajectories of boron ionsTrajectories of arsenic ionsThe more ion trajectories are used in a Monte-Carlo simulation the more accurate is the result. This example (77 kB) shows how the simulated doping distribution in an NMOS transistor depends on the number of the simulated ion trajectories.The Monte-Carlo simulation results shown here have been calculated with the code MCIMPL developed at The Institute for Microelectronics, TU ViennaThe dose and energy dependences of implantation profiles have been simulated using ICECREM process simulator developed at the Fraunhofer Institute of Integrated CircuitsCoupled 2D Process and Device Simulation The Metal-Oxide-Semiconductor Field-Effect-Transistor (MOSFET) in combination with other electronic devices allows the amplification of voltages and a high signal-power gain. MOSFETs are widely used in power electronics and above all, they are the core of integrated circuit (IC) technology at the present time. Because of the small size, millions of MOSFET devices can be integrated into one single chip. This opportunity and the fact that MOSFETs consume only very little energy, are the key to the rapid development of modern ASIC s (application specific ICs) and memory chips.In MOS technology, typical device dimensions like the gate length are reduced below one micron, e.g. in today's (1999) state-of-the-art memory products the minimum feature size is 0.25 microns. In these advanced devices, trade-off relationships cause limitations to the device performance and new physical effects arise. In order to reduce the development time and the immense costs, computer simulations become moreimportant. TCAD (technology computer aided design) based layout and the simulation of new devices offer the possibility to approximately predict the electrical behavior before processing any material. After calibration, the number of experiments to optimize an existing technology is reduced by the use of modern 1D, 2D and 3D simulation programs. Moreover, simulations help to estimate the influence of process fluctuations on device behavior which becomes more serious in the sub-micron-regime.A typical simulation setup consists of a coupled process and device simulation. The process simulation is performed to determine the device geometry and the dopant distribution in the active regions resulting from a sequence of process steps. Using the process simulation result as input, the electrical behaviour of the component can be simulated by means of device simulation.You can get more information about process simulation and have a look at an example of an advanced NMOS transistor here.A detailed look on a two-dimensional device simulation of this transistor gives you an insight into the device during the development of the characteristic curve.The simulations shown in this presentation have been carried out by using the software DIOS ISE (process simulation) and DESSIS ISE (device simulation), both from the software house ISE AG.Simulation of the Process Flow for the Fabrication of an NMOS TransistorYou can have a look at the following process steps:Step 1Step 2Step 3Step 4Step 5Step 6Step 7Step 8Step 9Step 10Step 11Step 12Step 13Step 14Step 15Step 16Step 17Step 18Step 19Step 20Step 21For more info, Please visit the following websites: http://www.leb.e-technik.uni-erlangen.de/lehre/mm/html/start.htmJust copy it from the websites.。
Michael-quirk-半导体制造技术-第五章-半导体制造中的化学品
30 20
40 50
10 00
70 80
High
High
temperature pressure
30 20
40 50
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70 80
Moveable piston
Volume increase
Semiconductor Manufacturing Technology
by Michael Quirk and Julian Serda
Properties of Materials
• Temperature • Pressure and Vacuum • Condensation • Vapor Pressure • Sublimation and
Deposition • Density • Surface Tension • Thermal Expansion • Stress
by Michael Quirk and Julian Serda
© 2001 by Prentice Hall
Objectives
After studying the material in this chapter, you will be able to:
1. Identify and discuss the four states of matter.
Sublimation
Dry ice (CO2)
Semiconductor Manufacturing Technology
by Michael Quirk and Julian Serda
Figure 5.7
© 2001 by Prentice Hall
Deposition
liquid–liquid phase separation
Biophysical Chemistry 109(2004)105–1120301-4622/04/$-see front matter ᮊ2003Elsevier B.V .All rights reserved.doi:10.1016/j.bpc.2003.10.021Cloud-point temperature and liquid–liquid phase separation ofsupersaturated lysozyme solutionJie Lu *,Keith Carpenter ,Rui-Jiang Li ,Xiu-Juan Wang ,Chi-Bun Ching a ,a a b bInstitute of Chemical and Engineering Sciences,Ayer Rajah Crescent 28,࠻02-08,Singapore 139959,Singapore aChemical and Process Engineering Center,National University of Singapore,Singapore 117576,SingaporebReceived 31July 2003;received in revised form 8October 2003;accepted 16October 2003AbstractThe detailed understanding of the structure of biological macromolecules reveals their functions,and is thus important in the design of new medicines and for engineering molecules with improved properties for industrial applications.Although techniques used for protein crystallization have been progressing greatly,protein crystallization may still be considered an art rather than a science,and successful crystallization remains largely empirical and operator-dependent.In this work,a microcalorimetric technique has been utilized to investigate liquid–liquid phase separation through measuring cloud-point temperature T for supersaturated lysozyme solution.The effects of cloud ionic strength and glycerol on the cloud-point temperature are studied in detail.Over the entire range of salt concentrations studied,the cloud-point temperature increases monotonically with the concentration of sodium chloride.When glycerol is added as additive,the solubility of lysozyme is increased,whereas the cloud-point temperature is decreased.ᮊ2003Elsevier B.V .All rights reserved.Keywords:Biocrystallization;Microcalorimetry;Cloud-point temperature;Liquid–liquid phase separation1.IntroductionKnowledge of detailed protein structure is essen-tial for protein engineering and the design of pharmaceuticals.Production of high-quality pro-tein crystals is required for molecular structure determination by X-ray crystallography.Although considerable effort has been made in recent years,obtaining such crystals is still difficult in general,and predicting the solution conditions where pro-*Corresponding author.Tel.:q 65-6874-4218;fax:q 65-6873-4805.E-mail address:lujie@.sg (J.Lu ).teins successfully crystallize remains a significant obstacle in the advancement of structural molecu-lar biology w 1x .The parameters affecting protein crystallization are typically reagent concentration,pH,tempera-ture,additive,etc.A phase diagram can provide the method for quantifying the influence of solu-tion parameters on the production of crystals w 2,3x .To characterize protein crystallization,it is neces-sary to first obtain detailed information on protein solution phase behavior and phase diagram.Recently physics shows that there is a direct relationship between colloidal interaction energy106J.Lu et al./Biophysical Chemistry109(2004)105–112and phase diagram.Gast and Lekkerkerker w4,5x have indicated that the range of attraction between colloid particles has a significant effect on the qualitative features of phase diagram.A similar relationship should hold for biomacromolecules, i.e.the corresponding interaction potentials govern the macromolecular distribution in solution,the shape of the phase diagram and the crystallization process w6x.Many macromolecular crystallizations appear to be driven by the strength of the attractive interactions,and occur in,or close to,attractive regimes w7,8x.Recent intensive investigation has revealed that protein or colloidal solution possesses a peculiar phase diagram,i.e.liquid–liquid phase separation and sol–gel transition exists in general in addition to crystallization w9,10x.The potential responsible for the liquid–liquid phase separation is a rather short range,possibly van der Waals,attractive potential w11,12x.The measurement of cloud-point temperature T can provide useful informationcloudon the net attractive interaction between protein molecules,namely,the higher the cloud-point tem-perature,the greater the net attractive interaction. Herein Taratuta et al.w13x studied the effects of salts and pH on the cloud-point temperature of lysozyme.Broide et al.w14x subsequently meas-ured the cloud-point temperature and crystalliza-tion temperature for lysozyme as a function of salt type and concentration.From these works the cloud-point temperature was found to be typically 15–458C below the crystallization temperature. Furthermore,Muschol and Rosenberger w15x deter-mined the metastable coexistence curves for lyso-zyme through cloud-point measurements,and suggested a systematic approach to promote pro-tein crystallization.In general,an effective way to determine the strength of protein interactions is to study temperature-induced phase transitions that occur in concentrated protein solutions.Liquid–liquid phase separation can be divided into two stages w11x:(1)the local separation stage at which the separation proceeds in small regions and local equilibrium is achieved rapidly;and(2) the coarsening stage at which condensation of these small domains proceeds slowly to reduce the loss of interface free energy w16x.The coexisting liquid phases both remain supersaturated but differ widely in protein concentration.The effect of a metastable liquid–liquid phase separation on crystallization remains ambiguous w17x.Molecular dynamics simulations and analyt-ical theory predict that the phase separation will affect the kinetics and the mechanisms of protein crystal nucleation w18x.tenWolde and Frenkel w19x have demonstrated that the free energy barrier for crystal nucleation is remarkably reduced at the critical point of liquid–liquid phase separation, thus in general,after liquid–liquid phase separa-tion,crystallization occurs much more rapidly than in the initial solution,which is typically too rapid for the growth of single crystal with low defect densities w15x.The determination of the location of liquid–liquid phase separation curve is thus crucial for efficiently identifying the optimum solution conditions for growing protein crystals. Microcalorimetry has the potential to be a useful tool for determining:(1)the metastable-labile zone boundary;(2)the temperature-dependence of pro-tein solubility in a given solvent;and(3)the crystal-growth rates as a function of supersatura-tion w20x.Microcalorimeters can detect a power signal as low as a few microwatts whereas standard calorimeters detect signals in the milliwatt range. Because of this greater sensitivity,samples with small heat effects can be analyzed.In addition, microcalorimetry has the advantage of being fast, non-destructive to the protein and requiring a relatively small amount of material.The present work is concerned with the analysis of the transient heat signal from microcalorimeter to yield liquid–liquid phase separation information for lysozyme solutions at pH4.8.To further examine the role of salt and additive on interprotein interactions, cloud-point temperature T has been determinedcloudexperimentally as a function of the concentrations of salt,protein and glycerol.2.Materials and methods2.1.MaterialsSix times crystallized lysozyme was purchased from Seikagaku Kogyo,and used without further107J.Lu et al./Biophysical Chemistry 109(2004)105–112purification.All other chemicals used were of reagent grade,from Sigma Chemical Co.2.2.Preparation of solutionsSodium acetate buffer (0.1M )at pH 4.8was prepared with ultrafiltered,deionized water.Sodi-um azide,at a concentration of 0.05%(w y v ),was added to the buffer solution as an antimicrobial agent.Protein stock solution was prepared by dissolving protein powder into buffer.To remove undissolved particles,the solution was centrifuged in a Sigma centrifuge at 12000rev.y min for 5–10min,then filtered through 0.22-m m filters (Mil-lex-VV )into a clean sample vial and stored at 48C for further experiments.The concentration of protein solution was determined by measuring the absorbance at 280nm of UV spectroscopy (Shi-madzu UV-2550),with an extinction coefficient of 2.64ml y (mg cm )w 21x .Precipitant stock solution was prepared by dissolving the required amount of sodium chloride together with additive glycerol into buffer.The pH of solutions was measured by a digital pH meter (Mettler Toledo 320)and adjusted by the addition of small volumes of NaOH or HAc solution.2.3.Measurement of solubilitySolubility of lysozyme at various temperatures and precipitant y additive concentrations was meas-ured at pH 4.8in 0.1M acetate buffer.Solid–liquid equilibrium was approached through both crystallization and dissolution.Dissolving lasted 3days,while the period of crystallization was over 2weeks.The supernatant in equilibrium with a macroscopically observable solid was then filtered through 0.1-m m filters (Millex-VV ).The concen-tration of diluted supernatant was determined spec-troscopically and verified by refractive meter(Kruss)until refractive index remained unchanged ¨at equilibrium state.Solubility of each sample was measured in duplicate.2.4.Differential scanning microcalorimetry Calorimetric experiments were performed with a micro-differential scanning calorimeter with anultra sensitivity,micro-DSC III,from Setaram SA,France.The micro-DSC recorded heat flow in microwatts vs.temperature,thus can detect the heat associated with phase transition during a temperature scan.The sample made up of equal volumes of protein solution and precipitant solu-tion was filtered through 0.1-m m filters to remove dust particles further.To remove the dissolved air,the sample was placed under vacuum for 3min while stirring at 500rev.y min by a magnetic stirrer.The degassed sample was placed into the sample cell of 1.0ml,and a same concentration NaCl solution was placed into the reference cell.The solutions in the micro-DSC were then cooled at the rate of 0.28C y min.After every run,the cells were cleaned by sonicating for 10–15min in several solutions in the following order:deionized water,methanol,ethanol,acetone,1M KOH and finally copious amounts of deionized water.This protocol ensured that lysozyme was completely removed from the cells.The cells were then placed in a drying oven for several hours.The rubber gaskets were cleaned in a similar manner except acetone and 1M KOH were omitted and they were allowed to dry at low temperature.3.Results and discussionA typical micro-DSC scanning experiment is shown in Fig.1.The onset of the clouding phe-nomenon is very dramatic and easily detected.The sharp increase in the heat flow is indicative of a liquid–liquid phase separation process producing a latent heat.This is much consistent with many recent investigations of the liquid–liquid phase separation of lysozyme from solution w 22,23x .In fact,such a liquid–liquid phase separation is a phase transition with an associated latent heat of demixing.In this work,the cloud-point tempera-tures at a variety of lysozyme,NaCl and glycerol concentrations are determined by the micro-DSC at the scan rate of 128C y h.3.1.Effect of protein concentrationIn semilogarithmic Fig.2we plot the solid–liquid and liquid–liquid phase boundaries for lyso-108J.Lu et al./Biophysical Chemistry 109(2004)105–112Fig.1.Heat flow of a typical micro-DSC scan of lysozyme solution,50mg y ml,0.1M acetate buffer,pH 4.8,3%NaCl.The scan rate 128C y h is chosen referenced to the experimental results of Darcy and Wiencek w 23x .Note the large deflection in the curve at approximately 4.38C indicating a latent heat resulting from demixing (i.e.liquid–liquid phase separation )process.Fig.2.Cloud-point temperature and solubility determination for lysozyme in 0.1M acetate buffer,pH 4.8:solubility (5%NaCl )(s );T (5%NaCl,this work )(d );T (5%cloud cloud NaCl,the work of Darcy and Wiencek w 23x )(*);solubility (3%NaCl )(h );T (3%NaCl )(j ).cloud Fig.3.Cloud-point temperature determination for lysozyme as a function of the concentration of sodium chloride,50mg y ml,0.1M acetate buffer,pH 4.8.zyme in 0.1M acetate buffer,pH 4.8,for a range of protein concentrations.It is worth noting that,at 5%NaCl,our experimental data of T from cloud micro-DSC are quite consistent with those from laser light scattering and DSC by Darcy and Wiencek w 23x ,with difference averaging at approx-imately 0.88C.This figure demonstrates that liquid–liquid phase boundary is far below solid–liquid phase boundary,which implies that the liquid–liquid phase separation normally takes place in a highly metastable solution.In addition,cloud-point temperature T increases with the cloud concentration of protein.3.2.Effect of salt concentrationFig.3shows how cloud-point temperature changes as the concentration of NaCl is varied from 2.5to 7%(w y v ).The buffer is 0.1M acetate (pH 4.8);the protein concentration is fixed at 50mg y ml.Over the entire range of salt concentrations studied,the cloud-point temperature strongly depends on the ionic strength and increases monotonically with the concentration of NaCl.Crystallization is driven by the difference in chemical potential of the solute in solution and in the crystal.The driving force can be simplified as w 24xf sy Dm s kT ln C y C (1)Ž.eq109J.Lu et al./Biophysical Chemistry 109(2004)105–112Fig.4.The driving force required by liquid–liquid phase sep-aration as a function of the concentration of sodium chloride,50mg y ml lysozyme solution,0.1M acetate buffer,pH 4.8.In the same way,we plot the driving force,f ,required by liquid–liquid phase separation as a function of the concentration of sodium chloride in Fig.4.At the moderate concentration of sodium chloride,the driving force required by liquid–liquid phase separation is higher than that at low or high salt concentration.As shown in Fig.3,with NaCl concentration increasing,the cloud-point temperature increases,which is in accord with the results of Broide et al.w 14x and Grigsby et al.w 25x .It is known that protein interaction is the sum of different potentials like electrostatic,van der Waals,hydrophobic,hydration,etc.The liquid–liquid phase separation is driven by a net attraction between protein molecules,and the stronger the attraction,the higher the cloud-point temperature.Ionic strength is found to have an effect on the intermolecular forces:attractions increase with ionic strength,solubility decreases with ionic strength,resulting in the cloud-point temperature increases with ionic strength.It is worth noting that,the effect of ionic strength on cloud-point temperature depends strongly on the specific nature of the ions w 13x .Kosmotropic ions bind adjacent water molecules more strongly than water binds itself.When akosmotropic ion is introduced into water,the entro-py of the system decreases due to increased water structuring around the ion.In contrast,chaotropes bind adjacent water molecules less strongly than water binds itself.When a chaotrope is introduced into water,the entropy of the system increases because the water structuring around the ion is less than that in salt-free water.This classification is related to the size and charge of the ion.At high salt concentration ()0.3M ),the specific nature of the ions is much more important w 25x .The charges on a protein are due to discrete positively and negatively charged surface groups.In lysozyme,the average distance between thesecharges is approximately 10Aw 26x .As to the salt ˚NaCl used as precipitant,Na is weakly kosmo-q tropic and Cl is weakly chaotropic w 27x .At low y NaCl concentrations,as the concentration of NaCl increases,the repulsive electrostatic charge–charge interactions between protein molecules decrease because of screening,resulting in the increase of cloud-point temperature.While at high NaCl con-centrations,protein molecules experience an attrac-tion,in which differences can be attributed to repulsive hydration forces w 14,25x .That is,as the ionic strength increases,repulsive electrostatic or hydration forces decrease,protein molecules appear more and more attractive,leading to higher cloud-point temperature.At various salt concentra-tions,the predominant potentials reflecting the driving force for liquid–liquid phase separation are different.Fig.4shows that the driving force,f ,is parabolic with ionic strength,while Grigsby et al.w 25x have reported that f y kT is linear with ionic strength for monovalent salts.The possible reasons for that difference include,their model is based on a fixed protein concentration of 87mg y ml,which is higher than that used in our study,yet f y kT is probably dependent on protein concentration,besides the solutions at high protein and salt concentrations are far from ideal solutions.3.3.Effect of glycerolFig.5compares cloud-point temperature data for 50mg y ml lysozyme solutions in absence of glycerol and in presence of 5%glycerol,respec-110J.Lu et al./Biophysical Chemistry109(2004)105–112parison of cloud-point temperatures for lysozyme at different glycerol concentrations as a function of the con-centration of sodium chloride,50mg y ml,0.1M acetate buffer, pH4.8:0%glycerol(s);5%glycerol(j).Fig.6.Cloud-point temperatures for lysozyme at different glycerol concentrations,50mg y ml lysozyme,5%NaCl,0.1M acetate buffer,pH4.8.Fig.7.Cloud-point temperature and solubility determination for lysozyme at different concentrations of glycerol in0.1M acetate buffer,5%NaCl,pH4.8:solubility(0%glycerol)(s); T(0%glycerol)(d);solubility(5%glycerol)(h);cloudT(5%glycerol)(j).cloudtively.Fig.6shows the cloud-point temperature as a function of the concentration of glycerol.The cloud-point temperature is decreased as the addi-tion of glycerol.In semilogarithmic Fig.7we plot the solid–liquid and liquid–liquid phase boundaries at dif-ferent glycerol concentrations for lysozyme in0.1 M acetate buffer,5%NaCl,pH4.8,for a range of protein concentration.This figure demonstrates that liquid–liquid and solid–liquid phase bounda-ries in the presence of glycerol are below those in absence of glycerol,and the region for growing crystals is narrowed when glycerol is added. Glycerol has the property of stabilizing protein structure.As a result,if crystallization occurs over a long period of time,glycerol is a useful candidate to be part of the crystallization solvent and is often included for this purpose w28x.In addition,glycerol is found to have an effect on the intermolecular forces:repulsions increase with glycerol concentra-tion w29x.Our experiment results of solubility and cloud-point temperature can also confirm the finding.The increased repulsions induced by glycerol can be explained by a number of possible mecha-nisms,all of which require small changes in the protein or the solvent in its immediate vicinity.The addition of glycerol decreases the volume of protein core w30x,increases hydration and the size of hydration layer at the particle surface w31,32x. In this work,we confirm that glycerol shifts the solid–liquid and liquid–liquid phase boundaries. The effect of glycerol on the phase diagram strong-111 J.Lu et al./Biophysical Chemistry109(2004)105–112ly depends on its concentration and this canprovide opportunities for further tuning of nuclea-tion rates.4.ConclusionsGrowing evidence suggests protein crystalliza-tion can be understood in terms of an order ydisorder phase transition between weakly attractiveparticles.Control of these attractions is thus keyto growing crystals.The study of phase transitionsin concentrated protein solutions provides one witha simple means of assessing the effect of solutionconditions on the strength of protein interactions.The cloud-point temperature and solubility datapresented in this paper demonstrate that salt andglycerol have remarkable effects on phase transi-tions.The solid–liquid and liquid–liquid bounda-ries can be shifted to higher or lower temperaturesby varying ionic strength or adding additives.Ourinvestigation provides further information upon therole of glycerol used in protein crystallization.Glycerol can increase the solubility,and decreasethe cloud-point temperature,which is of benefit totuning nucleation and crystal growth.In continuingstudies,we will explore the effects of other kindsof additives like nonionic polymers on phasetransitions and nucleation rates.Much more theo-retical work will be done to fully interpret ourexperimental results.AcknowledgmentsThis work is supported by the grant from theNational Natural Science Foundation of China(No.20106010).The authors also thank Professor J.M.Wiencek(The University of Iowa)for kinddiscussion with us about the thermal phenomenaof liquid–liquid phase separation.Referencesw1x A.McPherson,Current approaches to macromolecular crystallization,Eur.J.Biochem.189(1990)1–23.w2x A.M.Kulkarni, C.F.Zukoski,Nanoparticle crystal nucleation:influence of solution conditions,Langmuir18(2002)3090–3099.w3x E.E.G.Saridakis,P.D.S.Stewart,L.F.Lloyd,et al., Phase diagram and dilution experiments in the crystal-lization of carboxypeptidase G2,Acta Cryst.D50(1994)293–297.w4x A.P.Gast, C.K.Hall,W.B.Russel,Polymer-induced phase separations in non-aqueous colloidal suspensions,J.Colloid Interf.Sci.96(1983)251–267.w5x H.N.W.Lekkerkerker,W.C.K.Poon,P.N.Pusey,et al., Phase-behavior of colloid plus polymer mixtures,Euro-phys.Lett.20(1992)559–564.w6x A.Tardieu,S.Finet,F.Bonnete,Structure of the´macromolecular solutions that generate crystals,J.Cryst.Growth232(2001)1–9.w7x D.Rosenbaum,C.F.Zukoski,Protein interactions and crystallization,J.Cryst.Growth169(1996)752–758.w8x A.George,W.W.Wilson,Predicting protein crystalli-zation from a dilute solution property,Acta Cryst.D50(1994)361–365.w9x D.Rosenbaum,P.C.Zamora, C.F.Zukoski,Phase-behavior of small attractive colloidal particles,Phys.Rev.Lett.76(1996)150–153.w10x V.J.Anderson,H.N.W.Lekkerkerker,Insights into phase transition kinetics from colloid science,Nature416(2002)811–815.w11x S.Tanaka,K.Ito,R.Hayakawa,Size and number density of precrystalline aggregates in lysozyme crys-tallization process,J.Chem.Phys.111(1999)10330–10337.w12x D.W.Liu,A.Lomakin,G.M.Thurston,et al.,Phase-separation in multicomponent aqueous-protein solutions,J.Phys.Chem.99(1995)454–461.w13x V.G.Taratuta,A.Holschbach,G.M.Thurston,et al., Liquid–liquid phase separation of aqueous lysozymesolutions:effects of pH and salt identity,J.Phys.Chem.94(1990)2140–2144.w14x M.L.Broide,T.M.Tominc,M.D.Saxowsky,Using phase transitions to investigate the effect of salts onprotein interactions,Phys.Rev.E53(1996)6325–6335. w15x M.Muschol,F.Rosenberger,Liquid–liquid phase sep-aration in supersaturated lysozyme solutions and asso-ciated precipitate formation y crystallization,J.Chem.Phys.107(1997)1953–1962.w16x C.Domb,J.H.Lebowitz,Phase Separation and Critical Phenomena,Academic,London,1983.w17x D.F.Rosenbaum,A.Kulkarni,S.Ramakrishnan,C.F.Zukoski,Protein interactions and phase behavior:sen-sitivity to the form of the pair potential,J.Chem.Phys.111(1999)9882–9890.w18x O.Galkin,P.G.Vekilov,Nucleation of protein crystals: critical nuclei,phase behavior and control pathways,J.Cryst.Growth232(2001)63–76.w19x P.R.tenWolde, D.Frenkel,Enhancement of protein crystal nucleation by critical density fluctuations,Sci-ence277(1997)1975–1978.w20x P.A.Darcy,J.M.Wiencek,Estimating lysozyme crystal-lization growth rates and solubility from isothermalmicrocalorimetry,Acta Cryst.D54(1998)1387–1394.112J.Lu et al./Biophysical Chemistry109(2004)105–112w21x A.J.Sophianopoulos,C.K.Rhodes,D.N.Holcomb,K.E.vanHolde,Physical studies of lysozyme.I.Characteri-zation,J.Biol.Chem.237(1962)1107–1112.w22x Y.Georgalis,P.Umbach, A.Zielenkiewicz,et al., Microcalorimetric and small-angle light scattering stud-ies on nucleating lysozyme solutions,J.Am.Chem.Soc.119(1997)11959–11965.w23x P.A.Darcy,J.M.Wiencek,Identifying nucleation tem-peratures for lysozyme via differential scanning calorim-etry,J.Cryst.Growth196(1999)243–249.w24x M.L.Grant,Effects of thermodynamics nonideality in protein crystal growth,J.Cryst.Growth209(2000)130–137.w25x J.J.Grigsby,H.W.Blanch,J.M.Prausnitz,Cloud-point temperatures for lysozyme in electrolyte solutions:effectof salt type,salt concentration and pH,Biophys.Chem.91(2001)231–243.w26x D.Voet,J.Voet,Biochemistry,Wiley,New Y ork,1990. w27x K.D.Collins,Charge density-dependent strength of hydration and biological structure,Biophys.J.72(1997)65–76.w28x R.Sousa,Use of glycerol and other protein structure stabilizing agents in protein crystallization,Acta Cryst.D51(1995)271–277.w29x M.Farnum, C.F.Zukoski,Effect of glycerol on the interactions and solubility of bovine pancreatic trypsininhibitor,Biophys.J.76(1999)2716–2726.w30x A.Priev,A.Almagor,S.Yedgar,B.Gavish,Glycerol decreases the volume and compressibility of proteininterior,Biochemistry35(1996)2061–2066.w31x S.N.Timasheff,T.Arakawa,Mechanism of protein precipitation and stabilization by co-solvents,J.Cryst.Growth90(1988)39–46.w32x C.S.Miner,N.N.Dalton,Glycerol,Reinhold Publishing, New Y ork,1953.。
Epitaxial growth of III-V nitride semiconductors by metalorganic chemical vapor depositon
1. Introduction
The compound semiconductors in the InA1GaN quaternary system have been shown to be of both fundamental and practical interest in the realization of a wide variety of devices, including lightemitting diodes (LEDs), injection lasers, transistors, photodetectors, and photocathodes. These semiconductors have a direct band gap throughout the alloy composition range. The direct energy gaps of these materials cover a wavelength range from
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development [5]. At present, epitaxial growth of thin films of the III-V nitrides is primarily accomplished using either metalorganic chemical vapor deposition (MOCVD) [6-9] or molecular-beam epitaxy (MBE), [7, 10, 11]. Thin films of GaN and the ternary alloys InGaN, A1GaN and the binary A1N have been produced. More recently, quaternary alloys have been grown [12]. MOCVD has produced the highest quality III-N devices to date. In fact, MOCVD is currently used in the production of nitride device structures for commercial high-brightness blue light-emitting diodes (LEDs) [13]. Recently, there has been a rapid expansion of the research on the III-V nitride compound semiconductors, largely as the result of the great success in the use of MOCVD for the growth of high-performance GaN-based lightemitting diodes [14, 15] and injection lasers [16, 17]. Several extensive reviews have previously been written covering this topic [7]. Consequently, this description will focus on advances in the MOCVD III-N materials technology that have been made in the last few years [5, 18].
富勒烯和它的基本物理_化学问题_1996年诺贝尔化学奖简介[1]
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富勒烯和它的基本物理、化学问题1996年诺贝尔化学奖简介** 1996年11月4日收到解 思 深(中国科学院物理研究所,中国科学院凝聚态物理中心,北京 100080)摘 要 1996年的诺贝尔化学奖由美国得克萨斯州休斯顿的赖斯大学的柯尔教授和斯莫利教授以及英国萨塞克斯大学的克罗托教授因1985年发现富勒烯而分享,文章简要介绍了这一成就的发现、影响和由此而产生的新的化学分支和凝聚态物理研究的新领域.关键词 富勒烯,碳,团簇,笼形化合物Abstract 96 Nobel prize of Chemistry has been aw arded to Professor Harold K roto,U niver -sit y of Sussex,UK,Professor Bob Curl and Professor Rick Smalley,Rice U niversity,Texas,for t heir exciting discovery of Fullerene in 1985.Here the discovery story,impact to Condensed Matter Physics and Chemistry brought by t his discovery and t he new research fields derived from this discovery have been overview briefly.Key words Fullerene,c arbon,clust er,cage compound1 富勒烯的发现一年一度的诺贝尔物理奖和化学奖终于有了结果,前几年在化学界和物理学界曾大出风头的C 60分子,果然不孚众望,柯尔(R.F.Curl)教授、斯莫利(R.E.Smalley)教授和克罗托(H.W.Kroto )教授一举夺魁,荣获1996年诺贝尔化学奖这一殊荣.用高功率激光蒸发石墨而得到碳蒸气在惰性气体中冷凝、凝集而成的球状分子,这一球状分子包含60个碳原子,其外形酷似一个现代的足球,研究人员命名这一分子为巴基敏斯特 富勒烯 这3位的发现发表于1985年11月份出版的 自然 杂志上,当时受到了科学家的广泛的关注,既有批评、又有热情的赞扬.它在凝聚态物理、材料科学和化学本身所产生的影响,以及围绕这一新的发现所产生的新兴研究方向,足以说明富勒烯荣获诺贝尔化学奖不仅是由于它在开拓新的化学分支中的作用,而且对现有的理论化学中若干科学问题和概念都得以向三维方向延伸.在谈到富勒烯的发现时,人们常常提及1985年休斯顿的为期11天的合作研究.当时也有人戏称它为可能获得诺贝尔奖的11天的研究,如今这一预言业已得到应验.让我们回忆一下这宝贵的11天的研究成果是如何策划和如何发生的.1984年,克罗托教授从英国萨塞克斯大学专程到休斯顿的赖斯大学化学系访问他的同事柯尔教授.克罗托教授自70年代就开始从事分子射电天文学研究,在80年代中期,他开始考虑碳团簇可能与宇宙空间存在的反常红外吸收有关.在克罗托访问赖斯大学期间,他被介绍到斯莫利教授实验室.当时,斯莫利与他的同事正在利用一台新装置研究SiC 2的谱学问题,并意外地发现SiC 2分子有三角形的结构.在斯莫利的实验室里,一台激光蒸发团簇束的产生设备引起克罗托教授与柯尔教授用它制备长链碳分子的灵感,斯莫利教授对此研究计划也颇有兴趣.一年半之后,实验条件已经完全就绪,克罗托再次访问赖斯大学,并于1985年9月1日(星期天)在实验室开始了实验工作,在这里有两名研究生希思和奥布赖恩协助克罗托工作,而柯尔和斯莫利也常过问实验的进展.随着实验工作的顺利开展,在质量分析谱仪上出现了清晰的、令人激动的信号,即在质量数为720处的强峰代表了一个包含60个碳原子的稳定分子的存在.这一结果已经超过了埃克森(Ex xon)公司实验室1984年的工作.在初获胜利之后,9月6日(星期五)举行了研究组的全体人员会议,柯尔建议必须找到合适的工艺条件,以保证C60的峰成为占主导地位的峰.他们特别细心调节超声喷咀里吹出氦气的压力,并恰当地安排了簇与簇之间相互碰撞的空间,使体系更加接近热平衡状态,也使C60团簇的丰度不断提高,最终在质量数为40 120范围内只见到C+60和C+70的信号峰.除了C+60峰的强度比Exx on公司的小组的研究结果要高得多以外,赖斯大学的科学家在解释这一实验结果时,幸运得多.1984年Ex xon的罗尔芬发表题为 超声法制备碳簇束的指征 的文章,得到的结论是:(1)当质量数n 30时,碳簇(C n)中碳原子数目可奇、可偶;(2)当质量数20 n 90时,只存在偶数簇C2n.实际上,他们已经发现了全新的一组碳簇.但是,Ex xon公司实验小组实在太不走运了.在解释这一实验结果时,他们提出了存在线性链状簇的看法.这就使得他们与这一领域内的最激动人心的重要发现失之交臂,当然也失去了登上诺贝尔化学奖这一顶峰的机会.后来,有人评论这一少有的失误时说:这充分说明实验和理论研究工作必须更加紧密地联系起来;如果只有高超的实验技术,而理论上很弱,缺乏想像力,那末这种类同的失误是很难避免的.在赖斯大学化学系合作研究的三位主要科学家克罗托、柯尔和斯莫利教授,在分子的振动-转动动力学方面造诣很高,他们在面对由60个碳原子组成的稳定分子这一事实面前,提出了这一分子应该是球状的,而不是链状的这一关键模型.问题立即转化成为如何用60个碳原子搭建一个球状的分子模型.经过再三推敲,克罗托回忆起建筑师巴基敏斯特 富勒于1965年 1967年在蒙特利尔的万国博览会上所建造的蒙古包式的圆穹顶,其中使用了六边形和五边形,但是,没有人记得如何去使用这些六边形和五边形以及该分别用多少个六边形和五边形.他们从赖斯大学图书馆借来了一本有关富勒的建筑的书.克罗托多次生动地描述他曾经为自己的孩子搭建过一个类似的建筑物.直到临回英国的那天早晨,克罗托被告知斯莫利用纸片搭建了一个模型,成功地解决了富勒烯的分子结构.令人惊奇的是历史有时十分相似,世界上第一个DNA的双螺旋结构是用纸先做成的模型,而第一个富勒烯球状结构也是先用纸做成的模型.C60的球状结构具有截角正二十面体的对称性,看起来令人信服,但是结构模型的许多问题仍有待于回答.考虑到球状分子具有I20的对称性,实际上,这60个碳原子可以由对称操作联系起来.也就是说,因为处于同样的化学环境下,所以核磁共振的化学位移应该具有单线结构.毫无疑问,核磁共振实验是球状分子结构的直接考验.由于当时的实验方法只能获得微量的C60和C70,由飞行时间质谱仪检查到它们的存在,而无法收集到适宜的样品.从1985年第一篇文章的发表到1990年的4年时间内,科学家的兴趣只能局限于理论上的分析和对性质的预测.人类社会对于碳的第三种形态的存在,并没有表示出应有的热忱.这里我们必须提一下美国亚利桑那大学物理系的一个研究小组的霍夫曼等人在1972年发表过一篇石墨电极放电产生烟灰的文章.接着,霍夫曼与克里斯曼(德国,海德堡马普研究所)改进了放电装置,用收集到的烟灰做紫外吸收和拉曼散射时,发现了所谓骆驼灰的效应,并且断言引起它是由一种不明物所引起的.直到1985年有关C60的第一篇文章发表之后,亚利桑那大学的科学家才开始将不明物与C60分子联系起来.后来的实验表明,骆驼灰的红外吸收谱与C60的四条特征谱线完全一致.有人也曾这样评论这一事实,尽管亚利桑那大学的科学家是最早研究石墨烟灰来解决天体物理中问题的小组,显然,他们已经发现了碳簇的 森林 ,但是,他们在 森林 中游来荡去,什么也没有去发现,结果错过了C60的发现,也对呈现在他们面前的固体C60的新世界无动于衷.真是相逢未必就相识;不识卢山真面目,只缘身在此山中.应该指出,亚利桑那大学的研究小组的卓越贡献在于解决了如何从烟灰中分离出C60和得到C60的结晶形态.开始他们一天才能得到100mg的固体C60.毫无疑问,他们是世界上第一个观察到固体C60的科学家,也开拓了全新的富勒烯科学.直到1990年,由于他们的工作,在某种意义上说,才唤起了人类社会对C60发现的重视,并迅速扩展成为世界性的研究热潮.2 固体C60的物理性质固体C60的晶体结构由X射线衍射确定为面心立方结构,晶格参数a=1.402nm.C60之间主要靠范德瓦耳斯力结合.C60分子在固体中可取不同的方向排列,而且C60分子绕分子的某一轴向高速旋转,造成C60固体的声子谱包括振动部分和转轴摆动部分.固体C60的导电性能类似于窄能隙本征半导体,经过各种手段测量,价带底和导带顶之间的能隙为1 7eV左右.实验证明,掺杂碱金属的C60晶体呈现超导电性,且有较高的超导转变温度T c.典型的掺杂C60的样品K3C60(T c=18K),Rb3C60(T c =28K)都接近于传统超导体的最高转变温度,比过去有机超导体的T c提高了不少.目前,一般认为M3C60的超导电性可以纳入BCS的理论框架.C60与其他有机分子形成的固体化合物为电子转移体系,已得到一些有机半导体,其中有的表现出软磁性,与一般NO自由基的有机铁磁体并不相似.C60固体在高压下的行为也有很多的研究工作.简而言之,C60固体是一种典型的分子晶体,也是继石墨、金刚石之外的碳的第三种同素异构体.换句话说,它是碳的第三种存在形式.3 富勒烯化学自从能得到宏观数量的富勒烯样品以来,富勒烯化学的发展极为迅速,化学家利用各种化学反应和C60分子的特性已经合成了多种衍生物.但是由于C60分子存在60个可供选择的成键的自由基,因此产物的品种多,同素异构体多,造成分离、提纯的困难.如何建立选择性的反应机制来控制产品,已成为十分紧迫的研究任务之一.在众多的化学反应中,首先是烃类,用伯奇还原反应得到不含共轭双键的分子(C60H36,进一步加氢可以得到C60H60,后者完全不含双键,成为烷烃类.C60H36和C60H60均易氧化而重新得到C60.加卤族元素可得到C60F60,在加氟过程中,依次出现C60F6,C60F42,最后得到白色的C60F60.在适当的条件下,两个C60分子可以键合成哑铃状分子.应该指出,C60分子的直径为0 7nm,在笼内可以容纳下任一种元素的原子.但是,C60的分子一旦形成之后,它的 电子云排斥从外面接近的任一原子,因此外来原子、离子难于进入C60分子的笼内.一种较简单的方法是将要加入笼内的元素掺入石墨电极中,在放电过程中外来原子成离子被裹入笼内.4 结束语经过十多年富勒烯科学的研究发展,在各个领域内都似乎隐藏着应用的可能,人们也寄希望于它的广泛应用.应该指出的是富勒烯的应用尚需要大量的工作,其中必然有许多新的事物是我们仍未认知的.在祝贺克罗托、柯尔和斯莫利教授荣获1996年诺贝尔化学奖的同时,认真地回顾这一发现过程中的成功、失败,或许会对应用研究中许多问题的解决有所裨益.参 考 文 献[1] H.W.Kroto,J.R.H eath ,S.C.O Brien et al.,N ature ,318(1985),162.[2] E.A.Rohlfing,D.M.Cox, A.Kaldor,J.Chem.Phys.,81(1984),3322.[3] D.R.Huffman,Ad v.Phys.,26(1977),129.[4] W.Kr atschmer,mb,K.Fostiropoulos et al.,Nature ,347(1990),354.[5] Fulleren e C 60(History,Physics,Nanobiology,Nanotech -nology),ed by D.Koruga,Elsevier Science Publishers B.V.North -Holland,(1993).硅基发光材料研究进展** 1996年4月3日收到鲍 希 茂(南京大学物理系,南京 210093)摘 要 微电子技术是高技术中的关键技术,硅是微电子技术的基础材料.但是硅是一种非发光材料.为了发展光电子集成技术,必须大力发展硅基发光材料.多孔硅是一种有希望的硅基发光材料,它表明纳米晶粒中的量子限制效应对光发射是极有效的.随之涌现出一系列量子限制硅基发光材料,为发展光电子集成提供了新的途径.关键词 硅基发光材料,光致发光,光电子学Abstract Semiconducting silicon is the dominant mat erial in microelectronics,which is a key high tec hnology,but it cannot emit light efficiently.It is necessary to develop S-i based light emitt ing mat erial for optoelectronic integrat ion,and for this porous Si is a promising light emit ting material.T he quantum confinement effect in nanocrystallites has proved t o be highly effec t ive for light emission,as a result of whic h a series of quant um confined S-i based light emitt ing materials have appeaed which provide an entirely new approach t o integrated opt oelectronic s.Key words S-i based light emitt ing material,photoluminescence,optoelec t ronics微电子技术是高技术中的关键技术.它促进了其他各个技术领域的发展与现代化.微电子技术水平已是衡量一个国家发展水平的主要标志之一.微电子技术的核心是硅集成电路.硅是微电子技术的材料基础.硅具有一系列独特的半导体性质.硅是至今人们研究得最清楚,能获得的最纯净、最完整的材料.与之相对应,还发展了一套迄今最精密的硅平面工艺技术,利用这套技术,人们在小小的硅片上建立起了一座微电子学的技术大厦.在可以预见的未来,在微电子技术中,硅的基础地位是无以取代的.以硅集成电路、电子计算机为主体的微电子技术是信息技术的关键.信息技术的发展,要求信息传递速度更快,信息存储能力更大,信息处理功能更强.为此必须进一步提高微电子技术水平,但是,硅平面器件已趋向其物理极限,依靠缩小器件尺寸,提高精度,增强信息处理能力的潜力已很小.在微电子技术中信息的载体是电子,硅中电子移动速度是较低的.一个合乎逻辑的发展是,用速度最快的光作为信息载体,发展光集成技术或光电子集成技术,这将把信息技术推向一个全新的阶段.。
CZ和FZ方法介绍以及硅片的生产步骤2
International Scientific ColloquiumModelling for Electromagnetic ProcessingHannover, March 24-26, 2003 Modeling in Industrial Silicon Wafer Manufacturing - From Crystal Growth to Device ProcessesTh. Wetzel, J. VirbulisAbstractSilicon wafer manufacturing is one of the key processes that determine the yield and the profitability in semiconductor device production. The present paper gives an overview on vari-ous applications for numerical modeling in the wafer manufacturing process. It starts with ther-mal and convection models for the crystal growth process, both by the Czochralski (CZ) and the Floating Zone (FZ) method. Within this field, in particular modeling of electromagnetic field influence on melt flow has become an an indispensable means for the puller design and the process development for both methods. A further chapter is devoted to model approaches for predicting crystal defects, like grown-in voids, self-interstitial aggregates or oxygen precipitates. The defect modeling connect the crystal growth directly to the device manufacturing processes, as crystal defects may be detrimental or beneficial to microelectronic devices, produced on the silicon wafer. A last chapter points briefly to more recent applications of numerical modeling in auxiliary processes, like wafer heat treatment steps, epitaxial growth or wafer cleaning.IntroductionDuring the last five decades, the technology for growing silicon monocrystals from the melt, and the subsequent manufacture of silicon wafers, have become highly developed. The quality, purity and size of today's silicon crystals and wafers have reached an outstanding level. However, it remains time consuming and expensive to develop new processes that meet the crystal and wafer quality requirements for devices with further decreasing design rules. The current transition to a wafer diameter of 300 mm creates further challenges for the wafer industry.One of the main driving forces for the use of numerical modeling in the wafer industry are the extremely high costs for growth furnace design and growth process development. Thermal simulation of the global heat transfer in crystal growth furnaces contributes substan-tially to keeping the development costs at an acceptable level. In particular with the transition to 300 mm diameter CZ crystal growth, magnetic fields have become an important additional means to control heat and mass transfer in the large melt volumes. Numerical modeling facilitates the suitable design of inductor systems and helps to understand the effect of the magnetic fields on the melt flow. However, the growth conditions do not only affect yield or pull rate, but also the quality of the crystals. Grown-in defects like voids, self-interstitial aggregates or oxygen precipitates can be detrimental or beneficial in subsequent process steps. Therefore, defect engineering, i.e. the control of the formation of such defects, is an important part of the whole wafer production. Numerical modeling helps to predict the defect formation and behavior through crystal growth and for subsequent process steps, up to the device processes for microelectronic components in the chip manufacturer’s production line.Beside the success of the crystal growth and the defect simulation, there is an increasing number of new applications of numerical modeling in the wafer manufacturing industry, e.g. in process steps like wafer polishing, epitaxial layer growth or wet cleaning of the wafers.1. Crystal GrowthThere are two major methods for producing silicon monocrystals from the melt. With the Czochralski (CZ) method, today crystals of up to 300 mm are grown. The Floating Zone (FZ) technology is currently scaled up to grow 200 mm crystals.1.1 Czochralski GrowthFig. 1 shows a longitudinal cut through a CZ growth furnace. The prediction of the temperature field in the whole furnace and in the crystal requires a global thermal simulation, taking into account the heat transfer byconduction, convection and radiation.Software tools for the conduction andradiation calculation along with the pre-diction of the melt-crystal interface are avai-lable from different institutes [1, 2, 3]. Theyare based on 2D axisymmetric models, em-ploy view factor approaches for theradiation treatment and are based on theFinite Element Method (FEM) or the FiniteVolume Method (FVM). Some of thesecodes allow the reproduction of transientgrowth processes [2].With increasing melt volumes andcrystal diameters, the consideration of themelt convection has become more im-portant. The melt flow in large diameter CZcrucibles - today diameters of up to 32” withloads of up to 450 kg are used - is characte-rized by time dependent, three dimensional processes. The time needed for a fully transient, three-dimensional simulation of melt flow in a crucible of the mentioned size however, still prevents their application for industrial engineering purposes. Therefore,2D axisymmetric steady state models have been developed, that reproduce the most important features of the 3D flow, but do still provide reasonably short calculation time [4, 5]. One of the most critical parts in any CZ melt flow simulation, both 2D and 3D, is the consideration of turbulence. The 2D simulation tools usually employ k-ε or LowRe k-ε or k-ω models. Such tools require careful experimental verification and modification based on comparisons with experiments [5, 6, 7]. A model proposed in [8] provided good agreement of the simulated melt-crystal interface shapes with measured ones for 200 mm crystals. 3D time dependent simulations with LES turbulence models [9] and simulations close to DNS [10, 11] are used to further develop the understanding of the flow behavior and to improve less time consumingsimulation models. One goal of such attempts is the global modeling of oxygen transport in the Fig. 1: Schematic layout of an industrial CZ puller and simulated temperature distribution (left)CZ furnace, which is extremely sensitive towards any lack of precision in the turbulence modeling.Another aspect, closely related to reliable melt flow prediction, is the modeling of magnetic field influence. In 300 mm CZ growth, different types of alternating (AC) magnetic fields as well as static (DC) magnetic fields are used. The incorporation of the melt flow models into the global heat transfer simulation tools facilitates direct consideration of the effect of such fields on the temperature distribution in the crystal and all coupled phenomena, like point defect dynamics. A 2D axisymmetric model approach for the AC and DC magnetic field effect on the silicon melt is described in [5]. The model has been verified with experimental results from a CZ model setup with various magnetic fields [7, 12].1.2 Floating Zone GrowthFig. 2 shows a longitudinal cutthrough an FZ growth setup [13]. For thenumerical simulation of Floating Zonegrowth there is a complete model chainnecessary, starting with the prediction of thephase boundaries at feed rod, molten zoneand crystal, based on RF field influence andheat transfer [14]. A second part of themodel chain is covering the prediction of thetransient melt flow and heat transfer based on2D [15] and 3D [16] approaches. Based onthe melt flow calculation results, the dopanttransport can be simulated, yielding finallythe macroscopic and microscopic resistivitydistributions in grown wafers. The currentdevelopment of 200 mm FZ crystal growthprocesses has been substantially supported bythe use of such simulation models. Beyond these applications, theinfluence of additional low frequency inductors has been modeled [14] and considerations about the stress induced dislocation generation have been started [17]. A recently developed improved phase boundary simulation model is presented in [18].3. Defect ModelingThere are different types of defects in silicon wafers, which are related to the crystal growth conditions and the thermal history of the crystal and wafer. During the solidification process, intrinsic point defects, namely vacancies and silicon self interstitials, are incorporated into the crystal. These intrinsic point defects form grown-in defects during cooling down from melting to room temperature. Impurity atoms can also be incorporated into the growing crystal, later forming precipitates or other defects. The most common of these impurities is oxygen, which is dissolved from the silica crucible in CZ processes and transported through themelt to the crystallization front.Fig. 2: Schematic layout of a Floating Zone setup with simulated features and FEM meshThree types of defects in CZ crystals will bementioned here specifically: grown-in octahedral voids [19]formed by the aggregation of vacancies (Fig. 3), oxideprecipitates [20] and the OSF ring [19].Whether vacancy or self-interstitial related defectsare found in a CZ crystal or crystal region, depends on thevalue v/G in that region at the crystallization interface duringsolidification (v being the pull rate, G the temperaturegradient at the solid/liquid interface) [19, 21]. In addition todetermining these quantities from the thermal simulation,models are used to directly describe the point defectdynamics, i.e. the diffusive and convective transport of thesedefects during crystal growth as well as their annihilation by recombination [22]. The combination of such simulation models with the thermal simulation results, in particular the transient temperature field in the crystal, allows to designthe growth furnace and the growth process in such a way, that grown crystals show a desired defect species.Furthermore, especially for vacancy rich crystals, that are used e.g. for the production of memory chips, it is necessary to ensure a specific size and density of the grown-in voids. Simulation models have been developed, that describe the formation of such defects from vacancies [19]. The size of the grown in voids depends strongly on the cooling rate in a specific temperature interval during cooling down. Therefore, these models do also need the thermal history of the crystal as well as the results of the point defect models. Fig. 4 shows simulated size distributions of voids in fast and slow cooled CZ crystals. The void formation models are also used to predict the impact of wafer heat treatment steps on size and density of the voids.An important part of defect modeling is devoted to the behavior of oxygen in CZ silicon. As oxide precipitates are used as centers for internal gettering [20], models have been developed to predict the size and in particular the density of such defects in CZ crystals and wafers [23]. Another well known defect phenomenon is the so called OSF ring, appearing on the wafer surface afterwet oxidation. Thenature and formationof the OSF ring hasbeen studied by manyauthors (see [19] forfurther ref.). How-ever, there is ongoingresearch activity inthis field, as there arecomplex interactionsof oxygen precipi-tation with other pointdefects or impurityatoms in the growingcrystal, e.g. Nitrogen, that affect e.g. thewidth of the OSF ringFig.3: Octahedral void in anas-grown silicon crystal [19] Fig. 4: Simulated size distributions of voids in crystals with different cooling rates[24].3. Modeling for Wafer Processing StepsFollowing crystal growth, there are several process steps in a wafer production line. It starts with cutting of the ingots, goes through slicing, etching, polishing and ends with final cleaning of the wafers. Inbetween there can be several other steps like lapping, thermal treatment or epitaxial layer growth. In particular in the areas of etching, cleaning and epitaxial layer growth there are several simulation activities based on Computational Fluid Dynamics (CFD) codes, extended with chemistry and mechanical models. Many questions in this field can be handled already with standard CFD tools, like flow distribution in cleaning baths. Other examples for such simulations are the prediction of temperature distributions in annealing furnaces or in RF heated epi reactors.These more recent applications will gain increasing attention as they open a similar potential for improved physical understanding of the processes as well as for saving con-siderable amounts of time and money for process and equipment development. As in the crystal growth and defect modeling activities, the close collaboration of industry and research institutes will be extremely important for such new modeling topics, to finally have them at the same scientific level and with the same impact on industrial day to day research and development work.ConclusionsNumerical modeling is an integral part of today’s industrial silicon crystal growth and wafer manufacturing R&D activities, with a variety of applications. Crystal growth simulation with thermal and convection models, both for the CZ and the FZ method is the most well established application. Within this field, in particular modeling of electromagnetic field influence on melt flow has become an indispensable means for the puller design and the process development for both methods. The defect distribution in a wafer is extremely important for the yield and profitability of microelectronic device production lines. Therefore, various model approaches for predicting crystal growth and wafer treatment related defects, like grown-in voids or oxygen precipitates, have been developed and are successfully used in the industry. New applications of numerical modeling in auxiliary processes, like wafer heat treatment steps, epitaxial growth or wafer cleaning are being developed and successfully used in industrial equipment and process design.References[1] Dornberger, E., Tomzig, E., Seidl, A., Schmitt, S., Leister, H.-J., Schmitt, Ch., Müller, G.: ThermalSimulation of the Czochralski silicon growth process by three different models and comparison with experiment. J. Cryst. Growth 181 (1997), 461 pp.[2] Van den Bogaert, N., Dupret, F.: Dynamic global simulation of the Czochralski process I / II. J. Cryst.Growth 171 (1997), pp. 65-93[3] Kurz, M., Pusztai, A., Müller, G.: Development of a new powerful computer code CrysVUN++ especiallydesigned for fast simulation of bulk crystal growth processes. J. Cryst. Growth (198/199 (1999), pp. 101-106[4] Lipchin, A., Brown, R.A.: Hybrid finite-volume/finite element simulation of heat transfer and turbulence inCzochralski growth of silicon. J. Cryst. Growth 216 (2000), pp. 192-203[5] Wetzel, Th., Muiznieks, A., Mühlbauer, A., Gelfgat, Y., Gorbunov, L., Virbulis, J., Tomzig, E., vonAmmon, W.: Numerical model of turbulent CZ melt flow in the presence of AC and CUSP magnetic fields and its verification in a laboratory facility. J. Cryst. Growth 230 (2001) pp. 81-91[6] Lipchin, A., Brown, R.A.: Comparison of three turbulence models for simulation of melt convection inCzochralski crystal growth of silicon. J. Cryst. Growth 205 (1999) pp. 71-91[7] Krauze, A., Muiznieks, A., Mühlbauer, A., Wetzel, Th., Gorbunov, L., Pedchenko, A.: Numerical 2Dmodeling of turbulent melt flow in CZ system with AC magnetic fields. Proceedings of the Intl. Sc.Colloquium Modelling for Electromagnetic Processing, Hannover, 2003[8] Virbulis, J., Wetzel, Th., Muiznieks, A., Hanna, B., Dornberger, E., Tomzig, E., Mühlbauer, A., vonAmmon, W.: Numerical investigation of silicon melt flow in large diameter CZ-crystal growth under the influence of steady and dynamic magnetic fields. J. Cryst. Growth 230 (2001) pp. 92-99[9] Evstratov, Y., Kalaev, V.V., Zhamakin, A.I., Makarov, Y. N., Abramov, A.G., Ivanov, N.G., Smirnov,E.M., Dornberger, E., Virbulis, J., Tomzig, E., von Ammon, W.: Modeling analysis of unsteady three-dimensional turbulent melt flow during Czochralski growth of Si crystals. J. Cryst. Growth 230 (2001) pp.22-29[10] Vizman, D., Friedrich, J., Müller, G.: Comparison of the predictions from 3D numerical simulation withtemperature distributions measured in Si Czochralski melts under the influence of different magnetic fields.J. Cryst. Growth 230 (2001) pp. 73-80[11] Enger, S., Gräbner, O., Müller, G., Breuer, M., Durst, F.: Comparison of measurements and numericalsimulations of melt convection in Czochralski crystal growth of silicon. J. Cryst. Growth 230 (2001) pp.135-142[12] Pedchenko, A., Gorbunov, L., Gelfgat, Y., et.al.: Investigation of temperature field and melt flows inlarge-diameter CZ silicon modelling experiments with impact of magnetic fields. Proceedings of the Intl.Sc. Colloquium Modelling for Electromagnetic Processing, Hannover, 2003[13] Virbulis, J.: Numerische Simulation der Phasengrenzen und Schmelzenströmung bei der Züchtung vonSiliziumeinkristallen mit dem Floating-Zone Verfahren. Dissertation, Universität Lettlands in Riga 1997 [14] Raming, G.: Modellierung des industriellen FZ-Prozesses zur Züchtung von Silizium-Einkristallen.Dissertation, Institut für Elektrowärme, Universität Hannover 2000[15] Mühlbauer, A.. Muiznieks, A., Virbulis, A., Lüdge, A., Riemann, H.: Interface shape, heat transfer andfluid flow in the floating zone growth of large silicon crystals with the needle-eye technique. J. Cryst.Growth 151 (1995), pp. 66-79[16] Ratnieks, G., Muiznieks, A., Buligins, L., Raming, G., Mühlbauer, A., Lüdge, A., Riemann, H.: Influenceof the three dimensionality of the HF electromagnetic field on resistivity variations in Si single crystals during FZ growth. J. Cryst. Growth 216 (2000), pp. 204-219[17] Muiznieks, A., Raming, G., Mühlbauer, A., Virbulis, J., Hanna, B., v. Ammon, W.: Stress-induceddislocation generation in large FZ- and CZ-silicon single crystals––numerical model and qualitative considerations J. Cryst. Growth 230 (2001) pp. 305-313[18] Ratnieks, G., Muiznieks, A., Mühlbauer, A.: Mathematical modelling of industrial FZ process for large(200mm) silicon crystal growth. Proceedings of the Intl. Sc. Colloquium Modelling for Electromagnetic Processing, Hannover, 2003[19] Dornberger, E.: Prediction of OSF Ring Dynamics and Grown-in Voids in Czochralski Silicon Growth.Dissertation, Universite Catholique de Louvain 1997[20] Gilles, D., Ewe, H.: Gettering phenomena in silicon. Semiconductor Silicon 1994, Electrochemical SocietyProceedings 94-10 (1994) pp. 772[21] Voronkov, V.V.: The mechanism of swirl defects formation in silicon. J. Cryst. Growth 59 (1982) pp. 625-643[22] Sinno, T., Brown, R.A., von Ammon, W., Dornberger, E.: Point Defect Dynamics and the Oxidation-Induced Stacking Fault Ring in Czochralski-Grown Silicon Crystals. J. Electrochem. Soc. 145 (1998) pp.302[23] Esfanyari, J.: Modellierung und Computersimulation der Sauerstoffpräzipitation in Silicium. PhD Thesis,TU Wien 1995[24] von Ammon, W., Hölzl, R., Wetzel, T., Zemke, D., Raming, G., Blietz, M.: Formation of stacking faultsin nitrogen doped silicon single crystals.Proceedings of the 8th International Conference on Electronic Materials, Xian, China 2002AuthorsDr.-Ing. Wetzel, Thomas Dr.-Phys. Virbulis, JanisWacker Siltronic AG Center for Processes’ Analyses Numerical Modeling PAICP.O. Box 1140 Zellu Str. 8D-84479 Burghausen LV-1002 Riga, LatviaE-mail: thomas.wetzel@ E-mail: janis@paic.lv。
锂离子电池
液态
钴酸锂类型材料为正极的锂离子电池不适合用作大电流放电，过大电流放电时会降低放电时间 （内部会产生较高的温度而损耗能量），并可能发生危险；但磷酸铁锂正极材料锂电池，可以以 20C甚至更大（C是电池的容量，如C=800mAh，1C充电率即充电电流为800mA）的大电流进行充放 电，特别适合电动车使用。因此电池生产工厂给出最大放电电流，在使用中应小于最大放电电流。 锂离子电池对温度有一定要求，工厂给出了充电温度范围、放电温度范围及保存温度范围，过压 充电会造成锂离子电池永久性损坏。锂离子电池充电电流应根据电池生产厂的建议，并要求有限 流电路以免发生过流（过热）。一般常用的充电倍率为0.25C～1C。在大电流充电时往往要检测 电池温度，以防止过热损坏电池或产生爆炸。
组成部分
（5）电池外壳——分为钢壳（方型很少使用）、铝壳、镀镍铁壳（圆柱电池使用）、铝塑膜 （软包装）等，还有电池的盖帽，也是电池的正负极引出端 。
主要种类
主要种类
根据锂离子电池所用电解质材料的不同，锂离子电池分为液态锂离子电池（Liquified Lithium-Ion Battery，简称为LIB）、凝聚态锂离子电池和聚合物锂离子电池（Polymer Lithium-Ion Battery，简称为PLB）。
凝聚态
2023年4月19日，宁德时代发布凝聚态电池，能量密度最高为500Wh/kg，2023年内具备量产能 力。
工作效率
工作效率
锂离子电池能量密度大，平均输出电压高。自放电小，好的电池，每月在2%以下（可恢复）。没 有记忆效应。工作温度范围宽为-20℃～60℃。循环性能优越、可快速充放电、充电效率高达 100%，而且输出功率大。使用寿命长。不含有毒有害物质，被称为绿色电池。
2015年3月，日本夏普与京都大学的田中功教授联手成功研发出了使用寿命可达70年之久的锂离 子电池。此次试制出的长寿锂离子电池，体积为8立方厘米，充放电次数可达2.5万次。并且夏普 方面表示，此长寿锂离子电池实际充放电1万次之后，其性能依旧稳定。
Biofouling The Journal of Bioadhesion and Biofilm
This article was downloaded by: [Harbin Institute of Technology]On: 26 October 2012, At: 00:40Publisher: Taylor & FrancisInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UKBiofouling: The Journal of Bioadhesion and BiofilmResearchPublication details, including instructions for authors and subscription information:/loi/gbif20Structural optimization and evaluation of butenolidesas potent antifouling agents: modification of the sidechain affects the biological activities of compoundsYongxin Li a , Fengying Zhang b , Ying Xu a , Kiyotaka Matsumura a , Zhuang Han a , Lingli Liub , Wenhan Lin b , Yanxing Jia b & Pei-Yuan Qian aa KAUST Global Collaborative Research, Division of Life Science, Hong Kong University ofScience and T echnology, Clear Water Bay, Hong Kong, PR Chinab State Key Laboratory of Natural and Biomimetic Drugs, Peking University, Beijing, 100191,PR ChinaVersion of record first published: 24 Aug 2012.PLEASE SCROLL DOWN FOR ARTICLEStructural optimization and evaluation of butenolides as potent antifouling agents:modification of the side chain affects the biological activities of compoundsYongxin Li a ,Fengying Zhang b ,Ying Xu a ,Kiyotaka Matsumura a ,Zhuang Han a ,Lingli Liu b ,Wenhan Lin b ,Yanxing Jia b and Pei-Yuan Qian a *aKAUST Global Collaborative Research,Division of Life Science,Hong Kong University of Science and Technology,Clear Water Bay,Hong Kong,PR China;b State Key Laboratory of Natural and Biomimetic Drugs,Peking University,Beijing 100191,PR China(Received 5June 2012;final version received 26July 2012)A recent global ban on the use of organotin compounds as antifouling agents has increased the need for safe and effective antifouling compounds.In this study,a series of new butenolide derivatives with various amine side chains was synthesized and evaluated for their anti-larval settlement activities in the barnacle,Balanus amphitrite .Side chain modification of butenolide resulted in butenolides 3c-3d ,which possessed desirable physico-chemical properties and demonstrated highly effective non-toxic anti-larval settlement efficacy.A structure-activity relationship analysis revealed that varying the alkyl side chain had a notable effect on anti-larval settlement activity and that seven to eight carbon alkyl side chains with a tert-butyloxycarbonyl (Boc)substituent on an amine terminal were optimal in terms of bioactivity.Analysis of the physico-chemical profile of butenolide analogues indicated that lipophilicity is a very important physico-chemical parameter contributing to bioactivity.Keywords:antifouling;anti-larval settlement;barnacle;butenolides;structural optimization;side chain modification;lipophilicityIntroductionMarine biofouling,the undesirable accumulation of microorganisms,algae and animals on submerged substrata,is a major problem for all marine industries.The attachment and growth of fouling organisms on manmade surfaces submerged in seawater often cause technical and economic problems (Richmond and Seed 1991;Townsin 2003;Schultz et al.2011).Although antifouling (AF)paints containing organotins,lead,mercury or arsenic have been widely used to control biofouling in the past and have proven very effective,they are highly toxic and persistent once introduced into the marine environment (Voulvoulis et al.2002;Konstantinou and Albanis 2004;Zhou et al.2006).Given the International Maritime Organization (IMO)prohibition on the application of organotins to ships,effective from 17September 2008(Champ 2000),alternative AF paints with high levels of copper and herbicides have been used in recent years.However,these have also proven threatening to the marine environment because they can accumulate to high levels and have toxic effects on marine organisms (Omae 2003;Konstantinou and Albanis 2004;Bellas 2006;Thomas and Brooks 2010).Hence,there is anurgent need to develop new,effective,environmentally benign antifoulants.One of the most ecologically relevant AF strategies formulated in response to this need has been to develop products based on the natural chemical defenses of sessile marine organisms that keep their body surfaces free of fouling (Clare 1996;Kitano et al.2003;Nogata et al.2003;Dobretsov et al.2006;Fusetani 2011).Although more than 400natural AF chemical compounds have been found to date,none have been developed into commercial antifoulants for two main reasons.Firstly,their yield tends to be poor and secondly,they are too structurally complex to be synthesized (Fusetani 2004,2011;Qian et al.2010a).The supply problem is a major challenge facing researchers aspiring to develop natural antifoulants.Some notable solutions to the supply issue have recently been put forward through the chemical synthesis of a number of AF candidates,such as the structural optimization of 3-alkylpridine and alkyl isocyanides (Kitano et al.2003,2011;Blihoghe et al.2011).In previous studies conducted by the present authors,an analysis of the structure-activity relation-ships (SAR)of compounds isolated from marine organisms revealed that both furan and furanone*Corresponding author.Email:boqianpy@ust.hkBiofoulingVol.28,No.8,September 2012,857–864ISSN 0892-7014print/ISSN 1029-2454online Ó2012Taylor &Francis/10.1080/08927014.2012.717071D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012moieties were important functional pharmacophores for anti-larval settlement activity (Xu et al.2010;Li et al.Forthcoming 2012).In this study,rather than investing more effort in searching for additional bioactive compounds,the authors aimed to optimize the structure of AF compounds based on SAR to develop new and effective antifoulants.The recently developed compound 5-octylfuran-2(5H)-one (butenolide)(Xu et al.2010)is a promising AF agent with great market potential due to its simple structure,strong AF effect and low toxicity.An initial study of the structure–activity relationships of alkyl butenolides isolated from the deep-sea actinomycete Streptomyces sp.showed that the 2-furanone ring was an essential element for bioactivity (Xu et al.2010).Recent comparative proteomics and phosphoproteo-mics studies on the barnacle B.amphitrite and the bryozoan B.neritina have indicated that both of these species respond to butenolide by modulating their energy-and stress-related proteins (Qian et al.2010b;Zhang et al.2010).The species-specific morphological changes observed in B.amphitrite and B.neritina support the argument that butenolide has a species-specific AF mechanism (Zhang et al.2011).A subsequent study based on an affinity pull-down assay has shown that B.amphitrite ACAT1and B.neritina ACADVL,which are involved in the primary meta-bolism for energy production,are 2-furanone ring binding proteins (Zhang et al.2012).In addition to an ability to form a complex with a target protein,the effectiveness of a compound also generally depends on its ability to permeate cells and modulate the cellular signaling pathway (Camp et al.2012).It is apparent from drug research that drug-like properties such as ClogP,which are often used to calculate lipophilicity and aqueous solubility,have a strong influence on cell permeability and the aqueous bioavailability of the drug (Kubinyi et al.1979;Lo 2003).N-acyl is an essential functional group for many bioactive products such as N-acyl homoserine lactone (AHL)(Eberhard et al.1981;Wilkinson et al.2002;Nantasenamat et al.2008)and has been used tooptimize the lipophilicity and aqueous solubility of drugs (Kahns and Bundgaard 1991).A structure–activity relationship study of the AF amide analogues of loperamide suggested that amide moieties are important pharmacophores for potential AF activity (Moore et al.2009).The aim of the present study was to shift the physico-chemical properties towards drug-like properties by modifying the side chain of alkyl butenolide,thereby developing new and effective AF candidates.First,the introduction of various N-acyl groups into the alkyl side chain led to the selection of a series of compounds containing a Boc terminal group within the side chain.Variation of the length of the alkyl side chain at the 5-position then improved lipophilicity through a desirable arrangement that led to the development of new,effective anti-larval settlement candidates 3c and 3d with EC 50values of 2.13+0.54and 2.22+0.73m M against B.amphi-trite ,respectively.This study also further explored the side chain SAR of butenolides and defined the correlation between physico-chemical properties and anti-larval settlement efficacy against B.amphitrite .Materials and methodsChemical synthesis of butenolide derivativesAll the chemical reagents employed in this study were purchased from Sigma Aldrich and Alfa Aesar.A simple solution adopted to regulate the ClogP of butenolide was the incorporation of an amine group into this side chain to allow for modification of the amine group.Incorporation of the amine side chain into the furan ring was initially targeted before investigating modification of the amine group and elongation of the carbon side chain (Figure 1)in order to explore the SAR of the side chain in more detail.The methods used to synthesize these compounds are detailed in Schemes 1–4in Supplementary information [Supplementary information is available via a multi-media link on the online article webpage](see also Blakemore et al.1998,1999;Molander and StJeanFigure 1.Design and overall strategy for synthesis of butenolides.858Y.Li et al.D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 20122002).Based on this approach,N-Boc protecting amine alkyl iodides 2a-c were reacted with 2-trimethyl-siloxyfuran in the presence of silver trifluoroacetate to give rise to compounds 3a-c (Scheme S1,Table S2in Supplementary information)(Jefford et al.1988).Removal of the N-Boc protecting group from com-pounds 3a-f yielded compounds 4a-f .The presence of various acyl groups at the amine terminal of the side chain was also investigated.The reaction of com-pounds 4a and 4b with an excess of the appropriate carboxylic acid resulted in amides 5a-10a and 5b-10b (Table S1in Supplementary information).All the target compounds (Figure 2)were subjected to 1H and 13C NMR and HRESI-MS analysis (NMR and MS data are shown in Supplementary information)to determine the criteria for their chemical structure or purity (495%)before biological testing.Anti-larval settlement assayAdults of Balanus amphitrite were collected from Pak Sha Wan,Hong Kong (228190N,1148160E)while adults of Bugula neritina were collected from sub-merged rafts at fish farms in Yung Shue O,Hong Kong (228240N,1148210E).Larvae were collected and cul-tured according to the method described by Dobretsov et al.(2007).Fresh competent larvae (capable of attachment and metamorphosis)were used in the bioassay.Anti-larval attachment activities were eval-uated using cyprid larvae of B.amphitrite and swimming larvae of B.neritina .Larval settlementassays were performed using 24-well polystyrene plates (Becton Dickinson 353047).Each compound was first dissolved in a small amount of dimethyl sulfoxide (DMSO)at a concentration of 25.0mg ml 71before being diluted with 0.22m M of filtered seawater (FSW)to achieve a final concentration of 25.0m g ml 71for the preliminary anti-larval settlement activity test.The active compounds were diluted with FSW to 50.0,25.0,10.0,5.0,2.0,1.0,0.5,0.2and 0.1m g ml 71for further bioassay.About 15–20competent larvae were gently transferred into each well with 1ml of the testing solution while wells containing larvae in FSW with 0.1%DMSO served as the negative control.There were three replicates for each test solution.The plates for B.amphitirte were incubated for 48h at 258C while those for B.neritina were incubated for 24h at 258C.The effects of the compounds on larval settlement were determined by observing the plates under a dissecting microscope to check for (1)settled larvae,(2)swim-ming larvae,and (3)dead larvae.The number of settled larvae was expressed as a percentage of the total number of larvae per well.To calculate the EC 50and LC 50values of each compound,a concentration–response curve was initi-ally plotted,followed by the construction of a trend line for each compound.EC 50was calculated as the concentration at which 50%of the larval population was inhibited from settling,compared with that in the negative control while LC 50was calculated as the concentration at which 50%of the larval population died.Each compound was tested using threedifferentFigure 2.Structure of synthetic butenolide analogues.Biofouling859D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012batches of larvae to determine the mean and standard deviation (SD)of the EC 50and LC 50values.Results and discussionAnti-larval settlement activity against B.amphitrite Impact of the nature of the side chain on anti-larval settlement activityBarnacles are among the most predominant marine fouling organisms and their hard shells make it extremely difficult to remove them from marine installations (Khandeparker and Anil 2007).The barnacle B.amphitrite is one of the primary model organisms used extensively in screening for AF substances.To explore the SAR of butenolides with modified side chains,anti-larval settlement activity in two series of analogues containing modified side chains was evaluated through an anti-larval settlement bioas-say.These two series of analogues were 2-furanone derivatives with a 5or 6carbon alkyl amine substituent at the 5-position.The results show that the Boc carbamate analogues (3a and 3b )exhibited the best anti-larval settlement efficacy with EC 50values of 5.43+0.67and 4.00+0.85m M,respectively (Table 1,Figure 3).SAR analysis indicates that the Boc group was the optimal terminal group as a substituent at the N-terminal,with Boc (3a and 3b ,EC 50¼5.43and 4.00m M)4COCF 3(7a and 7b ,EC 50¼9.00and 7.80m M)4COCH 3(6a and 6b ,EC 50¼16.8and 18.0m M)4CHO (5a and 5b ,EC 50¼40.3and 26.3m M)4H (4a and 4b ,EC 50¼444and 225m M)in terms of anti-larval settlement activity.Increases in bioactivity appear to be related to the lipophilicity of the substituents.The bioactivity of compounds 8a-b was comparable to that of 3a-b ,respectively,whereas the bioactivity in 9a-b and 10a-b was significantly lower.The anti-larval settlement activity for aromatic analogues 8-10a and 8-10b was not enhanced compared with that in Boc analogues.Increases in bioactivity in C5and C6alkyl side chain analogues (3-5a ,3-5b )appear to be related to the length of their alkyl side chains,which also affected compound lipophilicity.Furthermore,a high degree of hydrophilic substitution in the side chain resulted in a loss of bioactivity,as exemplified by 4a and 4b ,which further suggests that the lipophilicity of the side chain might be a key factor in compound bioactivity,which is consistent with a previous study (Xu et al.2010).Impact of the length of the carbon side chain on anti-larval settlement activityAs seen in previous side chain variations,the Boc group was the optimal terminal group.Variation in the length of the alkyl amine side chain from 6carbons to 10carbons resulted in a series of carbamate analogues within the Boc group and their amine and formic amide analogues (see Supplementary information).[Supplementary information is available via a multi-media link on the online article webpage.]Table 2provides the anti-larval settlement data for all of theseTable 1.Anti-larval settlement activities of butenolide analogues (3-10a and 3-10b)against the barnacle B.amphitrite .RCompoundEC 50(m M)LC 50/EC 50CompoundEC 50(m M)LC 50/EC 503Boc 3a 5.43+0.674353b 4.00+0.854464H 4a 444+17UD 4b 225+31UD 5CHO 5a 40.3+5.7465b 26.3+6.2496COCH 36a 16.8+3.14146b 18.0+5.74127COCF 37a 9.00+1.784217b 7.80+1.8242388a 4.07+0.694418b 6.06+0.5942699a 12.4+2.04159b 14.4+2.534241010a9.56+1.4141710b6.43+1.22424Figure 3.Anti-larval settlement activities of butenolide analogues 3-10a and 3-10b against the barnacle B.amphitrite .860Y.Li et al.D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012analogues.As seen in the variation of 4,an increase in the number of carbons in the side chain of an amine analogue from C5to C10significantly increased the anti-larval settlement activity (all p 50.05)(Figure 4).Similar tendencies were also exhibited in amide analogues (5a -f ),which suggests that the enhancement of larval settlement inhibition is correlated with an increase in the number of carbons in the alkyl side chain.With respect to the variation of compound 3,increases in the anti-larval settlement activity of compounds 3a -c depended on the number of carbons in the alkyl side chain moiety (Figure 5).The bioactivity of compounds 3d-e was comparable to that of compound 3c ,whereas compound 3f was significantly less effective (p 50.05).No enhancement in anti-larval settlement efficacy was observed when the number of carbons in the alkyl chain side was increased beyond pared with the positive control 5-octylfuran–2(5H)-one (butenolide)and Sea-nine 211,compounds 3c-e all exhibited significantly greater activity (p 50.05),with EC 50values of 2.13+0.54, 2.22+0.73and 2.44+0.78m M,pounds 3a-b ,with EC 50values of 5.43+0.67and 4.00+0.85m M,respectively,were comparable to 5-octylfuran-2(5H)-one (butenolide),but significantly less effective than compounds 3c-e (p 50.05).Therefore,varying the length of the alkyl side chain had a notable effect on the biological activity of these compounds,with an alkyl side chain comprising seven to eight carbons being optimal.Table 2.Anti-larval settlement activities of butenolide analogues (3a-f ,4a-f and 5a-f )against the barnacle B.amphitrite .Side chain Compound EC 50(m M)LC 50/EC 50Compound EC 50(m M)LC 50/EC 50Compound EC 50(m M)LC 50/EC 50n ¼13a 5.43+0.674354a 444+17UD 5a 40.3+5.76n ¼23b 4.00+0.854464b 225+32UD 5b 26.3+6.29n ¼33c 2.13+0.544614c 108+15UD 5c 23.0+1.910n ¼43d 2.22+0.734734d 36.1+4.275d 14.3+1.915n ¼53e 2.44+0.784634e 22.0+1.9105e 7.50+0.1626n ¼63f 4.57+1.084324f 16.7+2.5135f5.48+0.8130Butenolide5.96+1.56443Seanine2115.76+1.05Table 3.Anti-larval settlement activities of compounds synthesized against the bryozoan B.neritina .Compound EC 50(m M)LC 50/EC 50CompoundEC 50(m M)LC 50/EC 503b 76.6+13.2455e 47.0+10.4443c 10.1+4.04205f 21.5+1.24103d 9.8+2.44357b 88.4+10.0463e 6.21+1.584398b 27.4+5.3473f9.71+1.3042610b36.8+11.5417Figure 4.Anti-larval settlement activities of compounds 4a–f and 5a–f against the barnacle B.amphitrite.Figure 5.Anti-larval settlement activities of synthesized compounds 3a–f and positive control group 5-octylfuran-2(5H)-one (A)and Seanine 211(B)against the barnacle B.amphitrite .The histogram data are expressed as means.Biofouling861D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012Impact of physico-chemical properties on anti-settlement activityLipinski’s seminal investigation leading to the ‘rule of five’has become one of the tools most widely used to assess the relationships between structures and drug-like properties (Lipinski et al.1997).Drug-like proper-ties such as median ClogP and aqueous solubility have a substantial influence on the ADME (absorption,distribution,metabolism and excretion)properties of drugs and the environmental fate of chemicals,such as their uptake,bioaccumulation and sediment-water partition coefficients (Kubinyi et al.1979;Cronin et al.2006;Leeson and Springthorpe 2007).In addition to the notable effect that varying the side chain has on biological activity,the side chain SAR described above also reveals a potential correlation between lipophili-city and biological activity.Given the variety of butenolide analogues at hand,the authors conducted a Pearson correlation analysis (SPSS 16.0)to investi-gate the relative impact of physico-chemical para-meters (Table S3in Supplementary information)[Supplementary information is available via a multi-media link on the online article webpage]on anti-larval settlement efficacy (Table 4).Molecular weight (MW)and lipophilicity,as calculated by ClogP,were negatively correlated with the natural logarithm of the EC 50value (LnEC 50),whereas the latter had a positive correlation with aqueous solubility (ALOGpS).Individual correlation analysis showed a significant negative correlation between ClogP and LnEC 50(R ¼70.921,p 50.001;Figure 6).These results indicate that the higher the degree of lipophi-licity,the lower the EC 50concentration.However,lipophilicity had a limited positive effect on anti-larval settlement efficacy (LogP 55.0)in accordance with Lipinski’s ‘rule of five’.A similar negative correlation between MW and LnEC 50(R ¼70.871,p 50.001;Figure 7)might be a result of the positive association between MW and lipophilicity (ClogP)(R ¼70.914,p 50.001).In this study,modified target compounds 3c and 3d within a median ClogP and MWarrangement complied with Lipinski’s ‘rule of five’and showed the desirable physico-chemical space considered essential for aqueous bioavailability/cell permeability.These data indicate that lipophilicity is the most important parameter contributing to the activity of butenolide analogues.One of the other key parameters observed here was aqueous solubility.Table 4.Correlation coefficients (below diagonal)and uncorrected P -values (above diagonal)between bioactivity (Ln (EC 50))and physico-chemical parameters a (MW,CLogP a ,ALOGpS,HBA,HBD and RingAr).Ln(EC 50)MW CLogP ALOGpS HBA HBD RingAr Ln(EC 50)50.001*50.001*50.001*0.0020.2980.115MW 70.871*50.001*50.001*50.001*0.0220.004CLogP 70.921*0.914*50.001*0.2370.030.361ALOGpS 0.791*70.895*70.791*0.0240.0960.011HBA 70.5690.636*0.668*70.3770.00350.001*HBD 0.10570.38370.1410.25470.5010.003RingAr70.2340.4930.36170.430.65*70.531*show significant correlation coefficients and P -values after Bonferroni correction;a physico-chemical parameters detailed in Supplementaryinformation.Figure 6.Correlation plot of natural logarithm of EC 50value (LnEC 50)with calculated partition coefficientClogP.Figure 7.Correlation plot of natural logarithm of EC 50value (LnEC 50)and molecular weight (MW).862Y.Li et al.D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012Anti-larval settlement activity against the bryozoan Bugula neritinaThe bryozoan B.neritina is a common and highly abundant soft fouling organism found worldwide.The animals tolerate high levels of pollution,including copper,which makes it difficult for copper-based AF paints to control them (Piola and Johnston 2006).To explore the AF potency of the butenolide derivatives synthesized in this study in more detail,the ability of all of the derivatives to inhibit larval settlement was investigated.The results (Table 3)show that a 9-carbon alkyl side chain with a Boc substituent on the terminal remained optimal,as exemplified by com-pound 3e (7.21+0.58m M).This further supports the argument that the side chain of a compound has a profound effect on its bioactivity.ConclusionThis study analyzed the synthesis of butenolide analogues with a potent ability to inhibit anti-larval settlement of both B.amphitrite and B.neritina .Representative analogue butenolides 3c and 3d with desirable physico-chemical properties (median ClogP and MW)were found to be the most potent antifoulants,with AF activity EC 50values of 2.13+0.54and 2.22+0.73m M against B.amphi-trite ,respectively.An analysis of structure–activity relationships revealed that the anti-larval settlement efficacy differed significantly according to the structur-al properties of the side chain.The positive association between lipophilicity and bioactivity was also illu-strated using a Pearson correlation analysis.The results of this study indicate that researchers should consider modifying the side chains and the lipophilicity of bioactive compounds when developing effective antifoulants.AcknowledgementsThis study was supported by a grant (DY125-15-T-02)from the China Ocean Mineral Resources Research and Develop-ment Association,a joint research grant from the Research Grants Council of the HKSAR and the National Natural Science Foundation of China (N_HKUST602/09),and award SA-C0040/UK-C0016from the King Abdullah Uni-versity of Science and Technology to P.Y.Qian.ReferencesBellas parative toxicity of alternative antifoul-ing biocides on embryos and larvae of marine inverte-brates.Sci Total Environ 367:573–585.Blakemore PR,Cole WJ,Kocienski PJ,Morley A.1998.Astereoselective synthesis of trans-1,2-disubstituted al-kenes based on the condensation of aldehydes with metallated 1-phenyl-1H -tetrazol-5-yl sulfones.Synlett 1:26–28.Blakemore PR,Kocienski PJ,Morley A,Muir K.1999.Asynthesis of herboxidiene.J Chem Soc Perk T 1:955–968.Blihoghe D,Manzo E,Villela A,Cutignano A,Picariello G,Faimali M,Fontana A.2011.Evaluation of the anti-fouling properties of 3-alyklpyridine compounds.Bio-fouling 27:99–109.Camp D,Davis RA,Campitelli M,Ebdon J,Quinn RJ.2012.Drug-like properties:Guiding principles for the design of natural product libraries.J Nat Prod 75:72–81.Champ MA.2000.A review of organotin regulatory strate-gies pending actions,related costs and benefits.Sci Total Environ 258:21–71.Clare AS.1996.Marine natural product antifoulants:statusand potential.Biofouling 9:211–229.Cronin DMT.2006.The role of hydrophobicity in toxicityprediction.Curr Comp Aided Drug Des 2:405–413.Dobretsov S,Dahms HU,Qian PY.2006.Inhibition ofbiofouling by marine microorganisms and their metabo-lites.Biofouling 22:43–54.Dobretsov S,Xiong HR,Xu Y,Levin LA,Qian PY.2007.Novel antifoulants:inhibition of larval attachment by proteases.Mar Biotechnol 9:388–397.Eberhard A,Burlingame AL,Eberhard C,Kenyon GL,Nealson KH,Oppenheimer NJ.1981.Structural identi-fication of autoinducer of Photobacterium fischeri lucifer-ase.Biochemistry 20:2444–2449.Fusetani N.2004.Biofouling and antifouling.Nat Prod Rep21:94–104.Fusetani N.2011.Antifouling marine natural products.NatProd Rep 28:400–410.Jefford CW,Sledeski AW,Boukouvalas J.1988.Regioselec-tive alkylation of 2-trimethylsiloxyfuran:direct access to 4-substituted but-2-en-4-olides.J Chem Soc Chem Commun 5:364–365.Kahns AH,Bundgaard H.1991.N-Acyl derivatives asprodrug forms for amides:chemical-stability and enzy-matic-hydrolysis of various N-acyl and N-alkoxycarbo-nyl amide derivatives.Int J Pharm 71:31–43.Khandeparker L,Anil AC.2007.Underwater adhesion thebarnacle way.Int J Adhes Adhes 27:165–172.Kitano Y,Akima C,Yoshimura E,Nogata Y.2011.Anti-barnacle activity of novel simple alkyl isocyanides derived from citronellol.Biofouling 27:201–205.Kitano Y,Yokoyama A,Nogata Y,Shinshima K,Yoshi-mura E,Chiba K,Tada M,Sakaguchi I.2003.Synthesis and anti-barnacle activities of novel 3-isocyanotheonellin analogues.Biofouling 19:187–192.Konstantinou IK,Albanis TA.2004.Worldwide occurrenceand effects of antifouling paint booster biocides in the aquatic environment:a review.Environ Int 30:235–248.Kubinyi H.1979.Nonlinear dependence of biologicalactivity on hydrophobic character:the bilinear model.Farmaco Sci 34:248–276.Leeson PD,Springthorpe B.2007.The influence of drug-likeconcepts on decision-making in medicinal chemistry.Nat Rev Drug Discov 6:881–889.Li YX,Wu HX,Xu Y,Shao CL,Wang CY,Qian PY.Forthcoming 2012.Secondary metabolites isolated from marine organisms along Chinese coastal areas as larval settlement inhibitors of the barnacle Balanus amphitrite .Mar Biotech.Lipinski CA,Lombardo F,Dominy BW,Feeney PJ.1997.Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings.Adv Drug Deliver Rev 23:3–25.Biofouling863D o w n l o a d e d b y [H a r b i n I n s t i t u t e o f T e c h n o l o g y ] a t 00:40 26 O c t o b e r 2012。
The adsorption of a single polymer chain onto a solid surface
Molecular dynamics simulation study of adsorption of polymer chains with variable degree of rigidity.I.Static propertiesE.Yu.KramarenkoPhysics Department,Moscow State University,Moscow,117234RussiaR.G.WinklerDepartment of Theoretical Physics,University of Ulm,Ulm,89069GermanyP.G.KhalaturDepartment of Physical Chemistry,Tver State University,Tver,170002RussiaA.R.KhokhlovPhysics Department,Moscow State University,Moscow,117234RussiaP.ReinekerDepartment of Theoretical Physics,University of Ulm,Ulm,89069Germany͑Received26September1995;accepted5December1995͒The adsorption of a single polymer chain onto a solid surface is investigated by molecular dynamicssimulations.The chain is composed of mass points interacting via a truncated Lennard-Jonespotential,i.e.,the excluded volume interaction is taken into account,and grafted to the surface withone end.The average adsorption degree is calculated for various chain lengths͑Nϭ16,32,64,128͒and adsorption energies.In addition,the scaling behavior of the adsorption degree and the radius ofgyration is investigated.The adsorption degree and the average length of loops and tails are obtainedfor chains of various stiffnesses.In this context,wefind that stiffer chains adsorb more easily.Moreover,the distribution of the mass points perpendicular to the surface as well as the orientationof the bonds with respect to the surface is discussed for various adsorption energies and stiffnesses.©1996American Institute of Physics.͓S0021-9606͑96͒51110-8͔I.INTRODUCTIONThe phenomenon of polymer chain adsorption on aflat surface has been of theoretical and experimental interest for many years due to its scientific significance and wide appli-cations in technology.Adsorption of macromolecules on sur-faces plays a major role in polymer adhesion,chromatogra-phy,and stabilization of colloidal dispersions.1Most theoretical works have focused on the static prop-erties of a single polymer chain near an attractive plane that corresponds to the adsorption from very dilute polymer so-lutions.It is a reasonablefirst step towards the understanding many-chains adsorption.Both lattice and continuous models were explored.It appeared that the exact analytical descrip-tion is possible only for the case of single-chain adsorption insolvents2,3while polymer chains with excluded volume were considered only approximately by using mean-field approach,4,5scaling arguments,6–9and renormalization group calculations.10The main attention has been paid to the case of a weak adsorption and to the behavior near the transition from the nonadsorbed to the adsorbed state.In the paper,11 the analogy between the polymer adsorption problem and the n-vector model of a magnet with a free surface in the limit n→0was explored to derive scaling forms for various ther-modynamic quantities of the adsorbed chain near the critical point as well as the scaling exponents.In addition to analytical calculations,intensive computer simulation studies have been performed11–25to test the theo-retical puter simulations,with its versions of molecular dynamics͑MD͒and Monte Carlo͑MC͒,are powerful tools to investigate microscopic processes.In most of the simulations on chain adsorption lattice,the lattice MC method was used.Whereas for ideal chains,the results of computer simulations perfectly coincide with the theory;for chains with excluded volume interactions there exist some discrepancies.In particular,the value of the critical crossover exponentfound by Eisenriegler,Kremer,and Binder11is equal to0.58Ϯ0.02while the value ofϭ0.53Ϯ0.001was obtained by Livne and Meirovitch,13where the scanning method used has allowed to simulate rather long chains͑up to1000monomer units͒.The adsorption and self-organization of short n-alkane chains from a solution onto a solid surface was recently stud-ied by MD simulations.20,21The investigations demonstrate, that the whole adsorption process can be simulated,i.e.the diffusion of the alkanes to the surface,the distribution of the highly structured solvent layers near the surface,and the physisorption on the solid.A series of MD simulations to elucidate the structural and dynamical properties of short chain molecules confined between solid surfaces have also been performed.These simulations yield valuable insight in the adsorption phenomena,but do not consider the transition from the nonadsorbed to the adsorbed state as a function of the surface attraction.In this paper we apply continuous MD simulations to the adsorption problem.It will allow us to obtain an independent estimate of the scaling exponents and to test the universality of the adsorption transition.On the other hand,we are going to pay significant attention to the behavior of the chain,notonly near the transition point but in the highly adsorbed state.Furthermore,we simulate chains with various stiffnesses to find out how this internal property of a chain influences its adsorption.Up to now the main features of the stiff chain adsorption were practically out of consideration although some analytical results based on a lattice model have been obtained recently.26Lattice MC simulations of adsorption of ideal stiff chains were performed in Refs.24and 25.In the present paper we shall discuss static properties only.Dynamic properties will be considered in a separate publication.In the next section we describe the model and the method of simulation.The results are presented in Sec.III:in Secs.III A and III B,we perform scaling analysis for the fraction of the adsorbed units and components of the radius of gyration near the transition point.In Sec.III C we discuss the structure of the adsorbed chain and the specific features of the stiff chain adsorption.II.THE MODELWe represent the polymer chain as a sequence of N beads with coordinates r i ϭ(x i ,y i ,z i )and unit masses m i ϭm ϭ1(i ϭ1,2,...,N ).Their connection into a chain is specified by a bond potential acting between nearest-neighbor beads i and i ϩ1.It is defined as the combination of two truncated and shifted Lennard-Jones ͑LJ ͒potentials 27U b ͑r i ,i ϩ1͒ϭΆ⑀bͫͩbr i ,i ϩ1ͪ12Ϫ2ͩbr i ,i ϩ1ͪ6ϩ1ͬ,r i ,i ϩ1рb ⑀bͫͩb 2b Ϫr i ,i ϩ1ͪ12Ϫ2ͩb2b Ϫr i ,i ϩ1ͪ6ϩ1ͬ,r i ,i ϩ1Ͼb ,͑1͒where r i ,i ϩ1is the distance between monomers number i and i ϩ1,i.e.,r i ,i ϩ1ϭ͉r i ϩ1Ϫr i ͉;b and ⑀b are LJ parameters;b defines the equilibrium value of the bond length.The valency angle between two consecutive pairs of bonds is determined by the angle-dependent potential.It has been chosen in the same form as the bond potential but act-ing between monomer units number i and i ϩ2U l ͑r i ,i ϩ2͒ϭΆ⑀lͫͩlr i ,i ϩ2ͪ12Ϫ2ͩlr i ,i ϩ2ͪ6ϩ1ͬ,r i ,i ϩ2рl ⑀lͫͩl2l a Ϫr i ,i ϩ2ͪ12Ϫ2ͩl2l a Ϫr i ,i ϩ2ͪ6ϩ1ͬ,r i ,i ϩ2Ͼl ,͑2͒where l is the equilibrium distance between atoms i and i ϩ2.The value of l defines the magnitude of the valence angle .If the value of ⑀l is high,i.e.,the potential is stiff and deviations of from the equilibrium value 0is small,then the following expression for is valid:Ϸ0ϭ2arcsin ͑l /2b ͒.͑3͒By changing the value of l ͑and hence )we can vary the stiffness of the chain.The measure of the chain flexibility is its Kuhn segment length which is expressed as 9A ϭb ͑1ϩcos 0͒/͑1Ϫcos 0͒.͑4͒Finally,we simulate excluded volume interactions by a truncated and shifted LJ potential acting between monomers i and j more than three bonds apart from each other ͑i.e.,͉i Ϫj ͉у4)U ͑r i ,j ͒ϭͭ⑀ͫͩr i ,jͪ12Ϫ2ͩr i ,jͪ6ϩ1ͬ,r i ,j р0,r i ,j Ͼ.͑5͒We assume that the polymer chain is immersed in a good solvent,so we take into account only the repulsive part of the LJ potential.Note that for ⑀b Ϸ⑀l Ϸ⑀the time scale of the intrachain vibrational motion is not shorter than the one of the transla-tional motion of the monomer units.27Thus the characteristic unit of time,t ,is ϭͱm /⑀.The surface is represented by a plane at z ϭ0.Based on pairwise LJ interactions ͓cf.Eq.͑5͔͒and on the translational symmetry of the crystalline solid forming the surface plane,the surface potential can be written as a series expansion with the leading term 28U a ͑z i ͒ϭ͚i ϭ1N⑀a ͫ1512z i10Ϫ6z i 4ϩ1ͬ,͑6͒where ⑀a is the adsorption energy of a monomeric unit.At low adsorption energies,the chain can desorb and diffuse into the bulk of the solution away from the surface.To avoid this we assume that the first atom of the chain is grafted to the surface.This fact does not influence signifi-cantly conformations of the chain at high adsorption ener-gies,but facilitates the computer realization of our simula-tions.The calculations are performed in standard reduced units,i.e.,length are measured in units of ,energies in units of ⑀,and time in units of ϭͱm /⑀.The temperature,T ,is expressed in energy units,i.e.,in units of ⑀.The potentials define the forces acting on every atom of the chain.In molecular dynamics simulation,we solve the classical equations of motion for the system of N atoms in-teracting via the potentials defined by Eqs.͑1͒–͑6͒.To inte-grate the equations of motion we use the so-called half-step leap-frog scheme which is well-known modification of the standard Verlet algorithm.29This scheme has the following form:ͭr ͑t ϩ␦t ͒ϭr ͑t ͒ϩ␦t v ͑t ϩ1/2␦t ͒v ͑t ϩ1/2␦t ͒ϭv ͑t Ϫ␦/2͒ϩ␦t a ͑t ͒,͑7͒where r (t ),v (t ),a (t )are,respectively,positions,velocities and accelerations of atoms at time t .The integration step ␦t is chosen to be 0.002reduced units.4807Kramarenko et al.:Adsorption of polymer chains with variable rigidityWe perform isothermal MD simulations.In order to maintain a given reference temperature,T0,during the simu-lation we use the velocity rescaling procedure according to Berendsen30which mimics frequent collisions of the atoms with much lighter virtual particles of an external heat bath. More specifically,all velocities are rescaled with the relax-ation timeT,if the temperature of the system,T(t),calcu-lated from the velocities at a given time t deviates from the prescribed value T0.The numerical value of the parameterT was set to Tϭ0.1.The reference temperature of the heat bath was cho-sen to be T0ϭ2.The parameters b,⑀b and⑀l were set to unity.At a given chain length,N,the initial configuration was selected at random but without the overlapping of non-bonded atoms.After the long equilibration of the system at constant⑀a,up to107configurations were generated.To calculate average values of the chain parameters,we use only independent configurations,i.e.,the time between conse-quent configurations saved for further analysis was greater than the maximal correlation time in the system.An estima-tion of the statistical errors was made by dividing the runsinto4–5short subruns and comparing the results of theseshort runs with the value of the total run.Each subrun waslong enough to change the positions of the atoms and theconformation of the chain many times.III.RESULTS AND DISCUSSIONWe start with the analysis of the behavior of the chainnear the transition temperature,and by following papers,11–13we derive scaling laws for such quantities as the fraction ofadsorbed units and the mean square radius of gyration.A.Adsorption degreeThefirst parameter on which we are focusing our atten-tion is the average adsorption degree⌰of the chain.It char-acterizes the relative number of chain monomers in the ad-sorbed state.Unlike discrete lattice models in continuousMD methods,the width z0of thefirst sublayer is not exactlyspecified,so the natural question arises:Which monomer canbe considered as an adsorbed one?Here,we use the follow-ing definition.We choose the value of z0to be close to thevalue of the potential well width,in particular,in all calcu-lations below we use z0ϭ1.5reduced units.The adsorbed monomers are those whose z coordinates are smaller thanz0.Of course,in such a way we obtain a⌰value whichdepends on z0,but it is clear that small variations in z0donot influence significantly the qualitative behavior of⌰as afunction of the parameters of the system.In Fig.1we plot the adsorption degree⌰as a functionof1/N for different adsorption energies⑀a.Extrapolating 1/N→0we can obtain the value of the adsorption degree for an infinite chain⌰ϱϭlim N→ϱ⌰.For⑀a less than some criti-cal value⑀c the extrapolation gives negative⌰ϱ,so in this region(⑀aϽ⑀c)the infinite chain does not adsorb at all.On the other hand,for⑀aу⑀c the value of⌰ϱbecomes positive and grows with the increase of⑀a.In Fig.2we show the dependences of⌰on⑀a for the different chain lengths Nϭ16,32,64,128.We also present the extrapolation curve forN→ϱ.It is clearly seen that in the case of an infinite chaina phase transition occurs at⑀aӍ2.In accordance with the theory,4the transition seems to be of the second order.Forthe chains offinite length the transition always has a nonzerowidth.In Fig.3we present the log–log plot of the averagenumber of contacts with the plane⌰N vs N for differentvalues of⑀a.From the slopes of these curves we can extract the value of the critical exponent in the dependence ⌰NϳN.The function(⑀a)is shown in Fig.4.One can see that at low adsorption energies the number of contacts is very low and very weakly depends on the chain length.Al-ternatively,at high adsorption energies when⌰is close to unity,the chain isflattened out on the surface and thenumber FIG.1.Fraction of the adsorbed monomer units,⌰,as a function of1/N for different adsorption energies,⑀aϭ0.5͑͒;1.0͑᭹͒;2.0͑᭡͒;2.5͑᭢͒;3.0͑ࡗ͒;3.5͑*͒;4.0͑ϫ͒.FIG.2.Dependence of the fraction of the adsorbed monomer units,⌰,onthe adsorption energy⑀a for Nϭ16(ࡗ),32(᭡),64(᭹),128(),the dotted line is the extrapolation curve for N→ϱ.4808Kramarenko et al.:Adsorption of polymer chains with variable rigidityof contacts is proportional to N .At the transition point ͑i.e.,at ⑀c Ӎ2as has been obtained above ͒we have ϭ0.57Ϯ0.05.A more exact estimation of the transition temperature and the exponent can be done with the help of the scaling law⌰ϭN Ϫ1h ͑N ͒,͑8͒which should be valid near the transition point,below which a finite fraction of monomers is in the adsorbed state.h (x )is a scaling function and ϵ(⑀c Ϫ⑀a )/(⑀a ).11The dependence of ⌰/N Ϫ1on the scaling variable N is shown in Fig.5.We tried the values of in the interval 0.5–0.6.The data seem to fall on one master curve most perfectly for ⑀c ϭ2and ϭ0.58,although scaling is not very sensitive to the value of in the range 0.53–0.58.The value of obtained here is in good agree-ment with the above result ϭ0.57.As it has been predicted in Ref.11the function h (x )in Eq.͑8͒has the following asymptotic forms:h ͑x ͒ϳͭx Ϫ1,x →ϱconst,x →0͉x ͉͑1Ϫ͒/,x →Ϫϱ.͑9͒In Fig.6the log–log plot of ⌰/N Ϫ1vs N is pre-sented.In the adsorption region scaling behavior is reached nicely.The slope is close to that corresponding to ϭ0.58.Thus,our MD simulations data confirm previous exact enu-meration estimates of by Ishinabe 31as well as MC calcu-lations of this crossover exponent based on lattice models.11On the other hand,these results contradict de Gennes’sug-gestion of ϭ1ϪӍ0.41.32Note,in addition,that the value of presented above is in quite reasonable agreement with approximate calculations by ⑀-expansion methods carried out to the second order which gave Ӎ0.605.10FIG.3.Log–log plot of the average number of contacts with the plane,⌰N ,vs N for ⑀a ϭ1.0͑͒;1.5͑᭹͒;2.0͑᭡͒;2.5͑᭢͒;3.0͑ࡗ͒;3.5͑ϫ͒;4.0͑*͒.FIG.4.The exponent in the dependence ⌰N ϳN as a function of the adsorption energy ⑀a.FIG.5.Plot of the scaling function ⌰/N Ϫ1vs scaling variable N with ⑀c ϭ2.0and ϭ0.58.FIG.6.Log–log plot of the scaling function ⌰/N Ϫ1vs scaling variable N .The straight line gives the asymptotic slope that corresponds to ϭ0.58.4809Kramarenko et al.:Adsorption of polymer chains with variable rigidityB.Radius of gyrationWe have made the similar scaling analysis for the per-pendicular,͗R g 2͘Ќ,and parallel,͗R g 2͘ʈcomponents of themean square radius of gyration,͗R g 2͘ϭ͗R g 2͘Ќϩ͗R g 2͘ʈof the chain͗R g 2͘Ќϭ12N 2ͳ͚i ϭ1N͚j ϭ1N ͑z i Ϫz j ͒2ʹ,͑10͒͗R g2͘ʈϭ12N 2ͳ͚i ϭ1N͚j ϭ1N ͑x i Ϫx j ͒2ϩ͑y i Ϫy j ͒2ʹ.͑11͒According to the scaling theory 11their behavior near the transition point depends on the scaling variable N and onthe correlation length exponents d ϭ3ϭϭ0.59and d ϭ2ϭ0.75for three (d ϭ3)and two (d ϭ2)dimensions,respectively,͗R g 2͘ЌϭN 2h 12͑N ͒,͑12͒͗R g 2͘ʈϭN 2h 22͑N ͒,͑13͒where the scaling functions h 1(x )and h 2(x )have the fol-lowing asymptotic behavior:h 1͑x ͒ϳͭconst,x →ϱconst,x →0͉x ͉Ϫ/,x →Ϫϱ,͑14͒FIG.7.Plot of the scaling function of the parallel component of the squared radius of gyration vs scaling variable N with ⑀c ϭ2.0and ϭ0.58.FIG.8.Log–log plot of the scaling functions of the perpendicular and the parallel components of the squared radius of gyration vs scaling variable N with ⑀c ϭ2.0and ϭ0.58.The straight line gives the asymptotic slope that corresponds to ϭ0.58.FIG.9.Dependence of the fraction ⌰of the adsorbed monomers on the adsorption energy ⑀a for the chains with N ϭ64and various Kuhn segment length A ϭ1.3͑͒;4.2͑᭹͒;9.1͑᭡͒.FIG.10.The average length of the train sections L t as a function of the adsorption energy ⑀a for N ϭ64and various Kuhn segment length A ϭ1.3͑᭡͒;4.2͑᭹͒;9.1͑͒.4810Kramarenko et al.:Adsorption of polymer chains with variable rigidityh 2͑x ͒ϳͭconst,x →ϱconst,x →0͉x ͉͑d ϭ2Ϫ͒/,x →Ϫϱ.͑15͒Note that ͗R g 2͘ϭN 2h 32(N )and h 3(x )ϳh 2(x ).The scaling plot for ͗R g 2͘ʈversus the scaling variable N for various chain length is shown in Fig.7.In Fig.8wepresent the log–log plot for ͗R g 2͘Ќand ͗R g 2͘ʈ.Note that we use the value of ϭ0.58obtained above.As we can see thedata for ͗R g 2͘Ќand ͗R g 2͘ʈcan be fitted by the corresponding master curves.The scaling analysis performed here for two components of the gyration radius reconfirms the results of previous MC simulations.11This allows us to assert that the behavior ob-served near the critical point is universal since it does not depend on the model and on the method of calculation.C.Conformation of the chain in the adsorbed stateIn this section we analyze the conformations of the chain in the adsorbed state and study the influence of the chain rigidity on its adsorption behavior.The exact solution to the problem of adsorption of stiff ideal polymer chains on a planar surface were presented re-cently in Ref.26.The calculations were performed within the framework of the lattice model.Here,we compare the results of MD simulations with the analytical calculations.In Fig.9we present the dependence of ⌰on ⑀a for chains with N ϭ64and various stiffnesses.We conclude that the stiffer chains adsorb more easily.Their adsorption degree is always higher and the transition is more pronounced.These facts correspond to the results of analytical calculations.26In the adsorbed state the polymer chain consists of alter-nating sequences of adsorbed,or train,sections flatten out on the surface and nonadsorbed sections that form loops and a tail over the surface.The average lengths of these sections strongly depend on the adsorption energy and on the chain stiffness.In Fig.10we plot the average length L t of train sections as a function of ⑀a for N ϭ64and for different chain stiff-nesses.One can see that L t grows rapidly with the increase of ⑀a ,i.e.,the chain tends to flatten on the surface.At con-stant ⑀a the stiffer chain has longer trains.The reason is connected with a high disadvantage of bending for stiff chains ͑cf.Ref.26͒.As we mentioned above the nonadsorbed monomer units can belong either to loop sections of the chain or to tail sections.The dependencies of the average length L l of loop sections and the fraction ⌰t of monomers in the tail on ⑀a are shown in Figs.11and 12,respectively.The adsorption of the chain leads to the energy gain from contacts with the surface and to entropy loss due to the confinement of the chain in the narrow layer near the surface.At ⑀a Ͻ⑀c the average number of contacts with the plane is very low,the entropic effects dominate,and the chain tends to avoid the surface.Due to the attachment of the first atom it cannot diffuse into the bulk of the solution away from the surface,but most of the chain is in its tail (⌰t is close to unity ͒.Conversely,at high ⑀a the fraction of monomers in the tail is very low;for longchainsFIG.11.The average length of the loop sections L l as a function of the adsorption energy ⑀a for ͑a ͒A ϭ1.3and N ϭ32͑᭡͒;64͑᭹͒;128͑͒;͑b ͒N ϭ128and A ϭ1.3͑͒;4.2͑᭹͒;9.1͑᭡͒.FIG.12.Fraction of monomers in the tail ⌰t vs ⑀a for A ϭ1.3and N ϭ32͑᭡͒;64͑᭹͒;128͑͒.4811Kramarenko et al.:Adsorption of polymer chains with variable rigidityit is close to zero.It is worth noting that at the transition point ⌰t ϭ0.5.This result is consistent with the representa-tion of the chain at the transition point as a free coil sliced by a surface,that was used for ideal chains.It seems,that this representation is approximately valid also for chains with excluded volume near the adsorption point ͑cf.Ref.4͒.The average length of loops L l shows a nonmonotonic behavior with the change of ⑀a .It grows first due to the decrease of the chain tail at ⑀a Ͻ⑀c and then diminishes rap-idly in the adsorption region.Thus at high ⑀a most of the loops consist of only a few monomer units.The value of L l is smaller for stiffer chains ͓see Fig.11͑b ͔͒.At the same time train sections increase with increasing chain stiffness.This result confirms the conclusion of Ref.26that for stiff chains the deviation from the plane occurs in the form of small ‘‘hairpins.’’The above results are in qualitative agreement with pre-vious lattice MC simulations 24,25of ideal chains.Thus the excluded volume interaction does not significantly effect the adsorption behavior of a single chain.Our MD simulations of ideal chains show that the adsorption degree near the tran-sition point is slightly higher for these chains.In the high adsorption energy regime the adsorption degree is the same for both ideal and excluded volume chains,respectively within the accuracy of the simulation.Monomer density profiles (z )͓(z )is the average number of monomer units of the chain at the distance z from the adsorbing surface ͔for N ϭ64and various ⑀a are shown in Fig.13.With the increase of ⑀a the center of mass moves closer to the surface.At high ⑀a the chain is confined in the narrow layer of the thickness equal to the bond length b .In should be noted that in the intermediate range of ⑀a the func-tion (z )has two maxima,the distance between these maxima is close to the value of b .The appearance of the second peak is connected with the partial occupancy of the first sublayer and excluded volume interactions of the chain atoms.Another quantity of interest is the chain segment orien-tation.We characterized it by the order parameter ϭ32͗cos 2␣͘Ϫ12,͑16͒where ␣is the angle between the z axis and the vector con-necting atoms i and i ϩ2.The values of ϭϪ0.5and ϭ1correspond to the chain segment orientations parallel and perpendicular to the XY plane,while ϭ0corresponds to the case when the segments are randomly oriented.In Fig.14we present the dependence of averaged over all segments of the chain on ⑀a for N ϭ64and various values of the Kuhn segment length A .At low adsorption energies the segments are randomly oriented,that is ϭ0.Adsorption transition is accompanied by the appearance of the order in the bond orientation.In the adsorbed state the segments are predominantly parallel to XY plane.The degree of ordering is higher for stiffer chains for all ⑀a .We also calculated the average orientation of the seg-ments as a function of their distance from the surface.The plot of (z )is presented in Fig.15.The order in the segment orientation decreases in the direction away from the surface;Ϸ0is already reached for z ϭ5.0.For the segments near the surface the value of tends to Ϫ0.5with increasing adsorption strength,which corresponds to the orientation parallel to the surface.IV.CONCLUSIONIn this paper we performed isothermal MD simulations of a single polymer chain with excluded volume near an impenetrable attractive flatsurface.FIG.13.Monomer density profiles for different ⑀a and different chain flex-ibility.FIG.14.Order parameter as a function of ⑀a for N ϭ64and A ϭ1.3͑͒;4.2͑᭹͒;9.1͑᭡͒.4812Kramarenko et al.:Adsorption of polymer chains with variable rigiditySpecifically the scaling behavior of the fraction of the adsorbed monomers and the two components of the mean square radius of gyration near the transition temperature has been investigated.Our simulations confirm the scaling be-havior predicted in Ref.11.It should be mentioned that in MD simulations the asymptotic behavior is reached for rather short chains.The scaling exponent is found to be ϭ0.58Ϯ0.05.The good agreement of the results of the continuous MD method with previous lattice MC simulations confirms once again the universality of the adsorption tran-sition.We also investigated the influence of the chain stiffness on the adsorption.In this connection the morphology of the adsorbed chain with variable stiffness has been studied in detail.In particular,such quantities as average length of loop and train sections,monomer density profiles,and segment orientation were calculated.ACKNOWLEDGMENTSThe support of the Deutscher Akademischer Austaus-chdienst ͑DAAD ͒is gratefully acknowledged ͑E.Yu.K.͒.This work has been carried out in the framework of the Sonder-forschungsbereich 230. E.Yu.K.is grateful also to Royal Swedish Academy of Sciences and International Center for Fundamental Physics in Moscow.A.R.Kh.,P.G.Kh.,and E.Yu.K.are grateful to Russian Foundation for Fundamental Research and International Science Foundation for financial support.1T.Cosgrove,B.Vincent,and M.A.Cohen-Stuart,Adv.Colloid Interface Sci.24,143͑1986͒.2E.A.DiMarzio andF.L.McCrackin,J.Chem.Phys.43,539͑1965͒.3C.A.J.Hoeve,E.A.DiMarzio,and P.Peyser,J.Chem.Phys.42,2558͑1965͒.4I.M.Lifshiz,A.Yu.Grosberg,and A.R.Khokhlov,Rev.Mod.Phys.50,683͑1978͒.5J.M.H.M.Scheutjens and G.J.Fleer,J.Phys.Chem.83,1619͑1979͒.6P.G.de Gennes,Scaling Concepts in Polymer Physics ͑Cornell Univer-sity,Ithaca,1979͒.7P.G.de Gennes and P.Pincus,J.Phys.Lett.44,L-241͑1983͒.8P.G.de Gennes,Macromolecules 14,1637͑1981͒.9A.Yu.Grosberg and A.R.Khokhlov,Statistical Physics of Macromol-ecules ͑AIP,New York,1993͒.10H.W.Diehl and S.Dietrich,Phys.Rev.B 24,2878͑1981͒.11E.Eisenriegler,K.Kremer,and K.Binder,J.Chem.Phys.77,6296͑1982͒.12y,Phys.Rev.E 49,5420͑1994͒.13S.Livne and H.Meirovitch,J.Chem.Phys.88,4498,4507͑1988͒.14A.T.Clark,l,M.A.Turpin,and K.A.Richardson,Discuss.Faraday Soc.15,189͑1975͒.15T.Cosgrove,N.A.Finch,and J.R.P.Webster,Macromolecules 23,3353͑1990͒.16A.C.Balazs,C.P.Siemasko,and ntman,J.Chem.Phys.94,1653͑1991͒.17S.Beltran,H.H.Hooper,H.W.Blanch,and J.M.Prausnitz,Macromol-ecules 24,3178͑1991͒.18A.C.Balazs,M.C.Gempe,and Z.Zhou,Macromolecules 24,4918͑1991͒.19S.M.King and T.Cosgrove,Macromolecules 26,5414͑1993͒.20R.Hentschke and R.G.Winkler,J.Chem.Phys.99,5528͑1993͒.21T.K.Xia and ndman,Science 261,1310͑1993͒.22R.G.Winkler,A.Gerstmair,P.Reineker,D.Y .Yoon,and T.Matsuda,Int.J.Quantum Chem.52,437͑1994͒.23K.Konstadinidis,S.Prager,and M.Tirrel,J.Chem.Phys.97,7777͑1992͒.24A.M.Skvortsov,T.M.Birshtein,and E.B.Zhulina,Vysokomol.Soedin.,Ser.A 28,1993͑1976͒.25A.M.Skvortsov and T.M.Birshtein,Vysokomol.Soedin.,Ser.A 28,2479͑1976͒.26A.R.Khokhlov,F.F.Ternovsky,and E.A.Zheligovskaya,Makromol.Chem.Teor.Simul.2,151͑1993͒.27P.G.Khalatur,Yu.G.Papulov,and A.S.Pavlov,Mol.Phys.58,887͑1986͒.28W.A.Steele,Surf.Sci.36,317͑1973͒.29L.Verlet,Phys.Rev.159,98͑1967͒.30H.J.C.Berendsen,J.P.M.Postma,W.F.van Gunsteren,A.Di Nola,and J.R.Haak,J.Chem.Phys.81,3684͑1984͒.31T.Ishinabe,J.Chem.Phys.76,5589͑1982͒.32P.G.de Gennes,J.Phys.͑Paris ͒37,1445͑1976͒.FIG.15.Two-bond orientation vs the distance from the surface.4813Kramarenko et al.:Adsorption of polymer chains with variable rigidity。
二氧化硅工艺中颗粒污染的解决方案
二氧化硅工艺中颗粒污染的解决方案杨旭敏;施国勇【摘要】在亚微米的半导体生产制造技术中,二氧化硅工艺中的颗粒污染会造成漏电流形成击穿电压,已经成为产品良率的主要影响因素.文章主要针对目前市面上流行的TEL Alpha-8SE的立式APCVD二氧化硅炉管制造工艺中所遇到的颗粒污染问题进行研究.通过大量的对比性实验,进行排查与分析,并利用各种先进的实验设备和器材,炉管、高倍度电子扫描设备、先进的光学仪器和缺陷分析设备等,找到产生颗粒污染的原因,并且找到解决问题的方案.在减少机台停机时间的同时,提高了机台的使用率,而且改善了颗粒污染的状况,最终获得良率的提升,优化了制造工艺.【期刊名称】《电子与封装》【年(卷),期】2013(013)001【总页数】4页(P34-37)【关键词】颗粒;APCVD;二氧化硅;炉管【作者】杨旭敏;施国勇【作者单位】上海交通大学微电子学院,上海200240【正文语种】中文【中图分类】TN3051 引言有效控制半导体制造工艺中的颗粒污染是一个长期的问题。
本文从应用角度出发，提供了一种可较好控制炉管APCVD二氧化硅工艺中颗粒污染的方法。
2 炉管二氧化硅工艺的颗粒污染问题分析2.1 二氧化硅工艺介绍二氧化硅制备工艺通常在等同常压的条件下在反应腔体内通入反应气体氧气和催化剂（H2，DCE）来生成二氧化硅，反应温度一般为920～1 150 ℃，见图1。
图1 TEL Alpha-8SE立式炉管示意图二氧化硅的工艺有三种方式：干氧氧化，湿氧氧化，催化剂氧化。
干氧氧化 Si（固体）+O2（气体）→SiO2，此过程为干氧，无任何催化剂。
湿氧氧化是在干氧氧化的基础上通入氢气（H2），在点火装置的作用下使氢气和氧气反应生成水蒸汽，同时通入的氧气过量在硅表面进行氧化反应。
它的优点是具有比干氧氧化高得多的氧化速率。
湿氧氧化具有较高速率的基本原理是，与氧相比水有更高的扩散系数和比氧大得多的溶解度（亨利常数）。