电解去溢料工序参数对IC封装体第二焊线区分层的影响
浅谈IC封装材料对产品分层的影响及改善
浅谈IC封装材料对产品分层的影响及改善蔺兴江;张宏杰;张易勒【摘要】IC封装不仅要求封装材料具有优良的导电性能、导热性能以及机械性能,还要求具有高可靠性、低成本和环保性,这也是引线框架、环氧树脂成为现代电子封装主流材料的主要原因,其市场份额约占整个封装材料市场的95％以上.由于环氧树脂封装是非气密性封装,对外界环境的耐受能力较差,尤其是受到湿气侵入时,产品会出现一些可靠性问题,最容易发生的现象是分层.简要分析了框架和环氧树脂对产品可靠性的影响,在此基础上提出一些改善措施.【期刊名称】《电子工业专用设备》【年(卷),期】2013(042)012【总页数】6页(P1-5,30)【关键词】环氧树脂;封装;分层【作者】蔺兴江;张宏杰;张易勒【作者单位】天水华天科技股份有限公司,甘肃天水741000;天水华天科技股份有限公司,甘肃天水741000;天水华天科技股份有限公司,甘肃天水741000【正文语种】中文【中图分类】TN604微电子器件封装中往往都要使用多种不同热膨胀系数的材料，由于材料间的热失配及制造和使用过程中的温度变化，使得各种材料及界面都将承受不同的热应力。
层间界面热应力和端部处的热应力集中常常造成封装结构的分层破坏，形成界面分层，从而导致封装结构的失效。
对封装件的应力分析是对封装材料、工艺和可靠性评价的重要内容之一，因而分析判断封装材料在封装和使用过程中产生应力的影响具有重要的意义，本文主要就引线框架和环氧树脂等主要封装材料对产品分层的影响进行分析和探讨。
框架是模塑封装的骨架，它主要由两部分组成：芯片焊盘（die paddle）和引脚（lead finger）。
其中芯片焊盘在封装过程中为芯片提供机械支撑，而引脚则是连接芯片到封装外的电学通路，就引脚而言，每一个引脚末端都与芯片上的一个焊盘通过引线相连接，该端称为内引脚（inner finger），引脚的另一端就是所谓管脚，它提供与基板或PC板的机械和电学连接。
电解工艺参数对氧化铝溶解的影响及优化
Trans.Nonferrous Met.Soc.China30(2020)3390−3403Effects of electrolysis process parameters onalumina dissolution and their optimizationWen-yuan HOU,He-song LI,Mao LI,Ben-jun CHENG,Yuan FENGSchool of Energy Science and Engineering,Central South University,Changsha410083,ChinaReceived12February2020;accepted27September2020Abstract:The Box–Behnken design and desirability approach were used to investigate and optimize the process parameters for aluminum reduction cells related to alumina dissolution.The bath temperature,alumina content,current and alumina temperature were chosen as the design parameters.The content of cumulative dissolved alumina(CCDA) and the relative deviation from the target content(RDTC)were adopted as the responses.The interactive influence results show that increasing the bath temperature and alumina temperature,as well as decreasing the alumina content, can increase CCDA.Increasing the bath temperature and lowering the current are beneficial for obtaining a more uniform alumina distribution.The optimal operating parameters were determined to be as follows:bath temperature of 958.8°C,alumina content of2.679wt.%,current of300kA and alumina temperature of200°C.Key words:aluminum reduction cell;alumina dissolution;response surface methodology;desirability approach;heat and mass transfer1IntroductionThe Hall−Héroult process is the major industrial process used for smelting primary aluminum from alumina[1,2].It involves dissolving alumina in the cryolite-based molten bath with complex heat and mass transfer, electrolyzing the molten salt bath,and driving the bath by anodic gases and electromagnetic forces, etc.Among these steps,alumina dissolution is the key process because the dissolution rate and the distribution uniformity of the alumina directly affect the stability of the electrolytic process.A lower alumina concentration in the anode−cathode distance(ACD)can lead to an anode effect, resulting in a significant increase in cell voltage and increase in greenhouse gas emissions(CF4,C2F6, etc).In addition,the low and locally non-uniform alumina concentration can cause spikes and other deformations on the bottom of the anodes[3−5]. Conversely,a higher alumina concentration can slow down the alumina dissolution rate,and the undissolved alumina can easily form sludge that is difficult to dissolve and erosive to the cathode. Therefore,the alumina concentration should be maintained in a certain range and evenly distributed.To accelerate the dissolution and diffusion of the alumina particles,many researchers have experimentally or numerically studied the dissolution process of alumina and established some models to describe the process.WALKER[6]and KUSCHEL and WELCH[7,8]studied the effect of the physical properties of alumina and operating conditions on alumina dissolution,as well as the alumina behavior after addition to cryolite-based electrolytes.JAIN et al[9]and HAVERKAMP andFoundation item:Project(2010AA065201)supported by the High Technology Research and Development Program of China;Project (2018zzts157)supported by the Fundamental Research Funds for the Central Universities of Central South University,ChinaWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−34033391WELCH[10]found that the dissolution time increased with increasing alumina concentration in the bath,which proves that a low alumina concentration is beneficial to the dissolution of alumina particles.Based on this phenomenon, WAI-POI et al[11]and VERHAEGHE et al[12,13] believed that the alumina concentration gradient is the driving force for alumina dissolution,and proposed a mass transfer model.KUSCHEL and WELCH[8],and YANG et al[14]found experimentally that a low superheat has a large impact on reducing the dissolution rate.Some researchers thought that superheat is the driving force for alumina dissolution and proposed a heat transfer model[15,16].Due to the high temperature and corrosion characteristics of the bath and the inability to directly observe dissolution and diffusion behavior for alumina in industrial cells,computational fluid dynamics(CFD)has become an important means to study the dissolution behavior.FENG et al[17,18] studied the effect of the side channel width and the ACD on the alumina dissolution distribution, finding that reducing the ACD or reducing the side channel width results in greater extremes for the alumina concentration.ZHAN et al[19]and ZHANG et al[20,21]simulated the alumina-mixing process and concluded that anode bubbles are the main driving forces for alumina dissolution,while electromagnetic forces(EMFs)promote the diffusion of alumina.LIU et al[3]obtained the distribution characteristics of alumina particles in aluminum reduction cells using a VOF-DPM model. HOU et al[22,23]established mathematical models to describe the alumina particle dissolution process with heat and mass transfer,as well as the uniformity of the alumina distribution.The temperature response during alumina dissolution was first simulated.In an industrial electrolytic cell,there are many factors that affect the dissolution and distribution of alumina.Some parameters can be controlled by the on-site process,including the bath temperature, alumina content,current and alumina temperature, etc.The above investigations are mainly based on a single factor,while alumina dissolution shows characteristics of multivariable nonlinear and strong coupling.LIANG et al[24]proposed a three-factor promoted in the BALCO Aluminum Plant, achieving significant results.The optimized parameters are bath temperature,liquidus temperature and superheat.In fact,the fundamental reason for the change in the liquidus temperature is a change in the bath composition,such as alumina content.The superheat is the difference between bath temperature and liquidus temperature. Therefore,it is necessary to carry out studies on the effects of basic controllable parameters on the alumina dissolution and distribution,which can provide theoretical guidelines for optimization design and process control for aluminum reduction cells to achieve better results.Response surface methodology(RSM)is widely used to explore the interactive effects among different parameters,and desirability approach is employed for multi-objective optimization[25−29]. In this work,CFD was used to simulate the alumina dissolution and distribution based on our previous work[22,23].A four-factor three-level Box−Behnken design and desirability function were used to explore and optimize the process parameters for an aluminum reduction cell.The major controllable parameters include bath temperature, alumina content,current and alumina temperature. The content of cumulative dissolved alumina (CCDA)and relative deviation from target content (RDTC)were adopted as responses.The parametric influence on the responses was analyzed using2D contour plot and3D response surface.The optimal parameters for the aluminum reduction cell were achieved to acquire maximal CCDA,minimal RDTC and superheat within a certain range.2Mathematical model2.1Physical modelIn this study,the dissolution process of alumina was simulated in a half of300kA aluminum electrolytic cell(Fig.1)under the action of anodic bubbles[22].The half-cell size is 3840mm×7400mm×180mm.The specific cell parameters are given in Table1.The alumina was fed into the feeding point.2.2Numerical methodAn Euler−Lagrange approach was used to simulate the alumina dissolution,in which aluminaWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China 30(2020)3390−34033392bath was treated as a continuum phase.Dissolved alumina was treated as a species in thebath.Fig.1Geometry model of a half of aluminum reduction cellTable 1Initial physical parameters for aluminum reduction cellParameter Value Feeding quantity/kg 1.8Feeding cycle/s 144Electrolyte level/mm180ACD/mm 42Anode size/mm 1550×660×620Inter-anode gap/mm 40Center channel distance/mm180Feeding zone/mm 160×160×20Bath temperature/°C 955Alumina content/wt.%3Current/kA 310Alumina temperature/°C3002.2.1Liquid phaseThe dissolution of alumina results in a decrease in bath temperature and an increase in alumina content,all of which have an effect on the dissolution rate of alumina.Therefore,the governing equations include the continuity equation,momentum equation,energy equation,and species transport equation.These equations can be expressed in the following general form:()()()L L L +φφSρϕ∇ρϕ∇Γ∇ϕτ∂⋅=+∂u (1)where τis the time,ρL is the bath density,u L is thevelocity of the bath,φis the general dependent variable,Γφis the effective diffusion coefficient and S φis the source term.The specific forms for the variables are listed in Table 2.In Table 2,μeff is the effective viscosity (the sum of the molecular viscosity,turbulent viscositypressure,S B is the bubble−bath interaction force,S m is the particle−bath momentum exchange term,c p ,L is the specific heat capacity of the bath,T L is the temperature of the bath,λL is the thermal conductivity of the bath,S T is the heat source term containing heating alumina and enthalpy change,w is the alumina content,and Γw is the effective diffusion coefficient.S 1w is the alumina dissolution rate and S 2w is the alumina consumption rate under the anode bottom [22]:2w 6IM S FV=-(2)where I ,M and F are the current,molar mass of alumina and Faraday constant,respectively;V is the volume between the anode bottom surface and the liquid aluminum interface in the anode−cathode distance.The larger the current,the larger the consumption rate of alumina.2.2.2Particle phaseThe particle trajectories of alumina were solved by Lagrangian approach.The governing equation can be expressed as follows:P sD P d d m m V ρτ=++u F g g(3)F D is the drag force and described as [30,31]()L P L PD D P L2C A ρ--=u u u u F (4)where C D is the drag coefficient related to the Reynolds number of alumina particles Re p ,and A P is the cross-sectional area.()P P 0.687D P P P 5P24/<0.52410.15/, 1<<5000.44, 500<<210, Re Re C Re Re Re Re =+⨯⎧⎪⎪⎨⎪⎪⎩(5)2.2.3Dissolution modelThe dissolution of alumina particles is controlled by both heat and mass transferWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China 30(2020)3390−34033393alumina particles under two mechanisms were established in our previous work [22].The alumina dissolution rate is the slowest under the two mechanisms of heat and mass transfer,because the slowest rate is the rate-controlling step.The shrinking sphere model under the mass transfer mechanism can be expressed as follows:()L sat S S2d()d k w w d ρτρ-=-(6)The shrinking sphere model under the heat transfer mechanism can be expressed as follows:()()()L liqS S Al L AlO diss 2d()d h T T d C T T H τρ-=--+∆(7)where k is the mass transfer coefficient;h is the convection heat transfer coefficient;C Al is the specific heat capacity of alumina;ΔH diss is the heat of dissolution for alumina;ρS is the density of the alumina particle;w sat is the saturation content of alumina;T AlO is the temperature of the alumina particle;T liq is the liquidus temperature of the bath [22,23].2.2.4SuperheatThe superheat is the difference between the bath temperature T L and liquidus temperature T liq .The liquidus temperature is closely related to the component content of the bath.The main component of the bath is cryolite,with a small amount of other components including AlF 3,Al 2O 3,MgF 2and CaF 2.The empirical formula for calculating the liquidus temperature was obtained by ZHANG et al [33].The formula is expressed as Eq.(8)and the component contents in the bath are listed in Table 3.The larger the alumina content,the larger the superheat.32liq AlF MgF 1003.3060.726 5.599 3.016T w w w =----2322CaF AlF 2.0320.186()0.178w w w -+-22322MgF CaF AlF 0.044()0.102()0.25w w w w --⋅-322AlF MgF AlF3CaF 0.0330.025w w w w ⋅-⋅-2222MgF CaF MgF CaF 0.5280.2290.166w w w w w w ⋅+⋅-⋅(8)where w AlF 3,w CaF 2and w MgF 2are the contents of AlF 3,CaF 2and MgF 2,respectively.Table 3Component contents in bath (wt.%)w AlF 3w CaF 2w MgF 2 2.2.5Numerical detailsBased on the OpenFOAM software platform,an alumina dissolution solution module was developed to solve the established equations and to obtain the alumina distribution and bath temperature,etc.The PIMPLE algorithm was used in the simulation to couple the velocity and pressure.The first-order implicit Euler scheme was chosen for time discretization.The space discretizations were central differences for the diffusion terms and second-order upwind for the convection terms,respectively.The time step was set to be 0.001s.The residuals for the transport and energy equations were set to be 1×10−8,while the residuals for the other equations were set to be 1×10−6.2.2.6Model validationTo verify the accuracy of the simulation,the simulation results were compared with the experimental results [34],as shown in Fig. DA was selected to validate the numerical methods and results.It can be seen that the simulation shows good agreement with the experimental results,indicating that the model established can be used to predict aluminadissolution.Fig.2Validation of numerical model3Box–Behnken design and desirability approachIt can be seen from Eqs.(6)and (7)that the alumina dissolution rate is related to the alumina content,bath temperature and temperature of the alumina particles.From Eq.(2),the alumina consumption rate is related to the current.Therefore,there are four important factors (bath temperature,Wen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China 30(2020)3390−34033394related to the alumina dissolution and alumina distribution,which are selected as the independent DA reflects the alumina dissolution rate and RDTC reflects the uniformity of the alumina distribution.They are evaluation indices for the dissolution of alumina [22].Thus,CCDA and RDTC were adopted as responses.There are several experimental designs for response surface methodology that can be chosen depending on the number of design factors,such as Box–Behnken design (BBD),and central composite design (CCD).In this work,BBD is employed to generate an experimental matrix in order to reduce the number of experiments and simulation time.A mathematical model generated by BBD defines the relationships between the independent variables and the responses.In this study,a modified two-factor interaction model is used to describe the interactive effect among the four factors on CCDA and is given as follows:10111nn ni i ij i j i i j i Y ββX βX X ε-===+=+++∑∑∑(9)A modified quadratic regression is used todescribe the interactive effect among the four factors on RDTC,which is given as follows:1201111nn nni i ij i j ii i i i j i i Y ββX βX X βX ε-===+==++++∑∑∑∑(10)where Y is the response of the experiment,X i and X j are independent variables,n is the number of variables,β0,βi ,βii and βij (i =0,1,2,…,n ;j =0,1,2,…,n )are the regression coefficients for the intercept,linear,quadratic and interaction terms,respectively,and εis the statistical error.The factors for the four variables are coded by A ,B ,C and D and the levels vary from −1to 1.The four variables and their levels are listed in Table 4.The range of parameters is obtained according to the control parameters of an aluminum reduction cell in Chongqing (China).The desirability approach is an effective method to realize multi-objective optimization.In the desirability objective function O (X ),each response Y i is converted to a dimensionless desirability value ranging from 0to 1(least to most desirable,respectively).If any of the responses or factors falls outside their desirability range,the varies from the least important (+),a value of 1,to the most important (+++++),a value of 5.The objective function is a function related to desirability and importance,which can be expressed as follows:1211111()in ii r n r r r r r i n i O o o o o '∑'∑'=⎛⎫=⨯⨯⨯= ⎪⎝⎭∏ (11)where n′is the number of responses.Table 4Ranges and levels of independent variables in BBD Code Variable Level −101A Bath temperature/°C 950955960B Alumina content/wt.%2.533.5C Current/kA 300310320DAlumina temperature/°C200300400For the goal of maximum,the desirability is defined by the following formulas:low,low,low,upper,upper,low,upper,0,,1,i i i i w i ii i i i i i ii i o Y Y Y Y o Y Y Y Y Y o Y Y=<⎧⎪⎪⎛⎫<⎪=≤≤ ⎪⎨ ⎪-⎪⎝⎭⎪=>⎪⎩(12)For the goal of minimum,the desirability is defined by the following formulas:low,upper,low,upper,upper,low,upper,1,,0,i i i i w i ii i i i i i ii i o Y Y Y Y o Y Y Y Y Y o Y Y=<⎧⎪⎪⎛⎫-⎪=≤≤ ⎪⎨ ⎪-⎪⎝⎭⎪=>⎪⎩(13)For the goal within range,the desirability willbe defined by the following equation:low,low,upper,upper,0,1,0,i i i i i i i i i io Y Y o Y Y Y o Y Y ⎧=<⎪=≤≤⎨⎪=>⎩(14)where w i is the weight ranging from 0.1to 10.Weights greater than 1give more emphasis to the goal,while weights less than 1give less emphasis to the goal.Y low,i and Y upper,i represent the lower andWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−34033395 4Results and discussionThe experimental matrix is obtained accordingto the Box–Behnken design and the responses arepresented in Table5.The values for CCDA andTable5Box–Behnken design arrangement andsimulation resultsNo.Factor ResponseA/°CB/wt.%C/kAD/°Cm CCDA/wt.%c RDTC/%1955331030083.45 1.25 2960 2.531030084.94 1.55 3960332030084.16 1.30 4950330030082.82 1.24 5955 2.531040083.93 1.60 6955 2.531020083.43 1.58 7955 2.532030083.79 1.62 8955332020083.52 1.35 9955330040083.62 1.23 10950332030082.72 1.41 11950 3.531030082.65 1.12 12960331020084.01 1.21 13955332040083.67 1.35 14960330030084.10 1.23 15955 3.530030083.17 1.07 16955 2.530030084.07 1.47 17960331040083.85 1.30 18950 2.531030082.61 1.67 19955 3.531040083.04 1.10 20960 3.531030083.46 1.08 21950331020082.70 1.35 22950331040083.18 1.36 23955330020083.43 1.18 24955 3.531020083.22 1.10 25955 3.532030083.09 1.19 26952.5 2.7530525083.06 1.41 27957.5 2.7530525083.97 1.35 28952.5 3.2530525083.09 1.17 29957.5 3.2530525083.52 1.13 30952.5 2.7531525082.99 1.55 31957.5 2.7531525083.94 1.42 32952.5 3.2531525083.00 1.27 33957.5 3.2531525083.47 1.20 34952.5 2.7530535083.26 1.37 35957.5 2.7530535084.15 1.36 36952.5 3.2530535083.07 1.17 37957.5 3.2530535083.49 1.21 38952.5 2.7531535083.29 1.47 39957.5 2.7531535084.23 1.44 40952.5 3.2531535083.08 1.25RDTC are obtained by numerical post-processing and their formulas are expressed as follows:m CCDA=m d/m f×100%(15) RDTC t/100%c c=⨯(16)where m d and m f are the dissolved mass and the feeding quantity of alumina,respectively.c is the alumina content of each node.c t is the initial concentration,which is selected as the target content.n″is the number of cells.4.1Analysis of variance(ANOV A)ANOVA is always used for descriptive statistics and statistical tests.In ANOVA,the significance and accuracy of the regression model will be discussed using the mean square value, F-value,p-value,Adeq precision,R2,Pred R2and Adj R2.Table6presents the results obtained from the analysis of variance test for CCDA.The Pred R2 value of0.9188is in reasonable agreement with the Adj R2value of0.9520because the difference between them is less than0.2.The Adeq precision measures the signal-to-noise ratio,with a ratio larger than4being desirable.The obtained ratio of 39.449indicates an adequate signal.As given in Table6,the regression model shows a large value for the goodness-of-fit(R2=0.9640).The p-value is less than0.05,which means that the model terms are significant.Therefore,the regression model has high accuracy for predicting CCDA.In addition,the main effects of bath temperature(A),alumina content(B)and alumina temperature(D),as well as the interaction effects of AC,AD and BD are statistically significant for CCDA.Table7presents the results obtained from the analysis of variance test for RDTC.The difference between the Pred R2and Adj R2values is0.0194, which indicates an acceptable agreement.The Adeq precision value of39.033indicates an adequate signal.The R2value of0.9833indicates that the regression model has a large value for the goodness-of-fit.As the p-value is less than0.05,the regression model has high accuracy for predicting23396Wen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−3403Table6Analysis of variance test results for CCDASource Sum of squares d f Mean square F-value p-value Significance Model10.0610 1.0180.25<0.0001*A 6.991 6.99557.68<0.0001*B 1.861 1.86148.39<0.0001*C 5.439×10−31 5.439×10−30.430.5151D0.1410.1411.450.0020*AB0.810.863.67<0.0001*AC8.201×10−318.201×10−30.650.4249AD0.08510.085 6.790.0141*BC 6.301×10−31 6.301×10−30.50.4838BD0.1610.1612.850.0012*CD7.813×10−417.813×10−40.0620.8045Residual0.38300.012Cor Total10.4340Adeq precision39.449R20.9640Pred R20.9188Adj R20.9520Table7Analysis of variance test results for RDTCSource Sum of squares d f Mean square F−value p−value Significance Model1140.072109.02<0.0001*A0.02710.02740.77<0.0001*B0.8610.861311.45<0.0001*C0.07810.078118.14<0.0001*D 1.502×10−31 1.502×10−3 2.280.1429AB 2.311×10−31 2.311×10−3 3.510.0721AC 4.651×10−31 4.651×10−37.070.0132*AD 4.061×10−31 4.061×10−3 6.170.0197*BC9.113×10−419.113×10−4 1.390.2498BD 6.125×10−51 6.125×10−50.0930.7627CD 1.361×10−31 1.361×10−3 2.070.1622A2 1.113×10−31 1.113×10−3 1.690.2047B20.01710.01726.32<0.0001*C2 4.084×10−41 4.084×10−40.620.4378D2 3.894×10−71 3.894×10−7 5.920×10−40.9808Residual0.01726 6.577×10−4Cor Total 1.0240Adeq precision39.033R20.9833Pred R20.9548Wen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−340333974.2Regression models for responsesThe regression models for CCDA and RDTC within the limits of the factors are obtained as follows:m CCDA=−328.71639+0.43879A+150.80313B−0.80044C+0.25710D−0.1598AB+8.1×10−4AC−2.61×10−4AD+7.1×10−3BC−3.59×10−3B D+1.25×10−5C D(17)c RDTC=369.71986−0.93251A−9.18767B+0.65519C−0.049449D+8.6×10−3AB−6.1×10−4AC+5.7×10−5AD−2.7×10−3BC+7×10−5BD−1.65×10−5CD+5.60484×10−4A2+0.22105B2−8.4879×10−5C2+2.62097×10−8D2(18)Figure3shows the comparison of the predicted results and simulation results.It can be seen that the predicted values lie close to a straight line,and the deviations between the numerical values and the predicted values for CCDA and RDTC are within±0.3%and±3.5%,respectively. This indicates that the regression model is effective and has good prediction performance.Thus,these two regression models can be used to predict CCDA and RDTC within the limits of the factors.4.3Interactive effect of parameters on CCDA 4.3.1Effects of bath temperature and aluminacontentFigure4presents the3D response surface and 2D contour plot for the interactive effect of the bath temperature and alumina content on CCDA for current of310kA and alumina temperature of 300°C.It can be seen that the alumina content has little effect on CCDA at lower bath temperature.As the bath temperature rises,CCDA increases with decreasing the alumina content.It can also be seen that the gradient of CCDA with bath temperature at high alumina content is smaller than that at low alumina content.The maximal CCDA can be achieved by increasing the bath temperature and decreasing the alumina content.4.3.2Effects of bath temperature and aluminatemperatureThe influence of bath temperature andalumina Fig.3Comparison of predicted results and simulation results:(a)CCDA;(b)RDTCWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−3403 3398temperature on CCDA for alumina content of 3wt.%and current of310kA is visualized by3D response surface and2D contour plot,as shown in Fig.5.It can be seen that the bath temperature has a greater impact than that of the alumina temperature because the gradient of CCDA is larger along the bath temperature DA increases with bath temperature and alumina temperature.An increment in bath temperature indicates an increase in superheat,thus accelerating the alumina dissolution to increase CCDA.When the bath temperature is higher,the effect of the alumina temperature on CCDA is negligible.However, when the bath temperature is lower,the higher the alumina temperature,the larger the CCDA. Therefore,when the bath temperature is high enough,the alumina temperature can be disregarded.4.3.3Effects of alumina content and aluminatemperatureThe influence of alumina content and alumina temperature on CCDA for bath temperature of 955°C and current of310kA is visualized in Fig.6.As the alumina content goes up,CCDA decreases. For large alumina content,CCDA remains relatively constant.When the bath temperature and current are fixed,reducing the alumina content and increasing the alumina temperature can increase CCDA.In conclusion,selecting appropriate parameters can effectively improve CCDA.Among the various process parameters,bath temperature and alumina content have larger contribution ratios towards CCDA.According to the3D response surface and 2D contour plot,low alumina content,high bath temperature and high alumina temperature are beneficial for increasing CCDA.4.4Interactive effect of process parameters onRDTC4.4.1Effects of bath temperature and currentFixing alumina content of3wt.%and alumina temperature of300°C,the influence of the bath temperature and current on RDTC is presented in Fig.7.The closer the value of RDTC is to0,the more uniform the alumina distribution is.It isclear Fig.5Effects of bath temperature and alumina temperature on CCDA:(a)3D response surface;(b)2D contourplotWen-yuan HOU,et al/Trans.Nonferrous Met.Soc.China30(2020)3390−34033399that an increase in current will increase RDTC, which means that the uniformity of the alumina distribution becomes worse.When the current is 300kA,RDTC is the smallest.When the current is low,the bath temperature has little effect on the uniformity of the alumina distribution.4.4.2Effects of bath temperature and aluminatemperatureThe influence of bath temperature and alumina temperature on RDTC for alumina content of 3wt.%and current of310kA is visualized in Fig.8. When the bath temperature is low,RDTC decreases with increasing the alumina temperature;while when the bath temperature is high,RDTC increases with increasing the alumina temperature.For a low alumina temperature,the RDTC changes significantly with bath temperature,and a higher bath temperature makes the alumina distribution more uniform.In one word,one needs to select the appropriate parameter to decrease RDTC to guarantee the uniformity of the alumina distribution.Among the various process parameters,bath temperature and current have larger contribution ratios towards RDTC.According to the3D response surface and2D contour plot,a high bath temperature and low current are beneficial for decreasing RDTC.4.5Multi-objective optimizationTo determine the optimized process parameters for the aluminum reduction cell,the desirability approach is used to carry out the multi-objective optimization.The bath temperature,alumina content,current and alumina temperature vary in the designed range.The CCDA should be as large as possible;at the same time,the RDTC should be as small as possible.To ensure normal operation for the reduction cell,it is necessary to ensure superheat at8−15°C.All variables and objectives are set to the same importance of3and same weight of1.The optimization criteria used for the process parameters for the aluminum reduction cell are listed in Table8.Fig.7Effects of bath temperature and current intensity on RDTC:(a)3D response surface;(b)2D contourplot。
半导体元器件引线框架封装之分层研究
半导体元器件引线框架封装之分层研究福建福顺半导体制造有限公司 陈 力本文主要对半导体元器件引线框架封装工艺及封装材料对元器件分层的影响进行研究与说明。
文章通过分析如何改善封装材料、改善封装工艺技术防止元器件内部分层。
引言：半导体引线框架封装为整个半导体元器件产业链的主要后段加工制程之一。
主要目的是为保护表面布满集成电路的半导体硅芯片免受外界机械或化学因素腐蚀，并采用引线框架作为导通介质，其引线框架的材质一般为铜材或铁材。
现行的半导体封装工艺技术中，元器件内部的分层是重大的质量缺陷。
引线框架封装塑封体为非密封型，暴露于空气中容易吸收空气中的湿气。
当塑封体经过回流焊或波峰焊的高温时，塑封体内部的蒸汽压力会增加，在特定情况下，内部的压力会造成封装体内部分层。
严重的分层现象致使电性功能的失效。
依据JEDEC的可靠性实验为判断半导体封装工艺的国际标准，在模拟各种环境状况下如高压、高温、高湿、高低温等条件，加速元器件的老化及破坏，进而推算是否符合元器件的使用寿命要求。
1 如下分层判定标准依据JEDEC标准(JEDEC 020-E)JEDEC 020-E MSL3：前处理过程，烘烤24小时（125℃）+ 恒温恒湿40小时（60℃ 60%RH MSL3）+ IR*3次（260℃）要求。
2 分层实验检测设备简介通过Scanning Acoustic Tomograph（SAT）超音波断层扫描设备，可以判定元器件内部是否产生了分层。
试验设备为日立扫描式超声波图像装置。
3 半导体封装原材料组成主要原材料组成内容：晶圆、引线框架、焊线、塑封料、焊料。
（1）晶圆：半导体集成电路制作光刻处理后的硅晶片。
在硅晶片上加工制作成各种电路元件结构，而成为有特定电性功能之IC 产品。
晶圆的原始材料是硅。
（2）引线框架：主要材料为铜，会在上面进行镀银、 NiPdAu 等材料。
提供电路连接和Die的固定作用。
（3）焊线：早期金线一般采用的是99.99%的高纯度金；目前封装行业基本均采用铜线、银合金、铝线工艺。
电池片各工序影响因素及异常情况
一次清洗影响因素1.温度温度过高，首先就是IPA不好控制，温度一高，IPA的挥发很快，气泡印就会随之出现，这样就大大减少了PN结的有效面积，反应加剧,还会出现片子的漂浮，造成碎片率的增加。
可控程度：调节机器的设置，可以很好的调节温度。
2.时间金字塔随时间的变化：金字塔逐渐冒出来；表面上基本被小金字塔覆盖，少数开始成长；金字塔密布的绒面已经形成，只是大小不均匀，反射率也降到比较低的情况；金字塔向外扩张兼并，体积逐渐膨胀，尺寸趋于均等，反射率略有下降。
可控程度：调节设备参数，可以精确的调节时间。
3.IPA1.协助氢气的释放。
2.减弱NaOH溶液对硅片的腐蚀力度，调节各向因子。
纯NaOH溶液在高温下对原子排列比较稀疏的100晶面和比较致密的111晶面破坏比较大，各个晶面被腐蚀而消融，IPA明显减弱NaOH的腐蚀强度，增加了腐蚀的各向异性，有利于金字塔的成形。
乙醇含量过高，碱溶液对硅溶液腐蚀能力变得很弱，各向异性因子又趋于1。
可控程度：根据首次配液的含量，及每次大约消耗的量，来补充一定量的液体，控制精度不高。
4.NaOH 形成金字塔绒面。
NaOH浓度越高，金字塔体积越小，反应初期，金字塔成核密度近似不受NaOH浓度影响，碱溶液的腐蚀性随NaOH浓度变化比较显著，浓度高的NaOH溶液与硅反映的速度加快，再反应一段时间后，金字塔体积更大。
NaOH浓度超过一定界限时，各向异性因子变小，绒面会越来越差，类似于抛光。
可控程度：与IPA类似，控制精度不高。
5.Na2SiO3SI和NaOH反应生产的Na2SiO3和加入的Na2SiO3能起到缓冲剂的作用，使反应不至于很剧烈,变的平缓。
Na2SiO3使反应有了更多的起点，生长出的金字塔更均匀，更小一点Na2SiO3多的时候要及时的排掉，Na2SiO3导热性差，会影响反应,溶液的粘稠度也增加，容易形成水纹、花蓝印和表面斑点。
可控程度：很难控制。
4#酸洗HCL去除硅片表面的金属杂质盐酸具有酸和络合剂的双重作用，氯离子能与多种金属离子形成可溶与水的络合物。
电解工序重要参数的检测及优化控制
1．3 氯气/氢气总管压力、电解槽气相压强差 氯气总管压力 PIZA216 正常值为 40 kPa，报警
值 为 43 kPa， 连 锁 值 为 50 kPa； 氢 气 总 管 压 力 PIZA226 正常值为 44 kPa，报警值为 47 kPa，连锁值 54 kPa； 二者气相压差 PDIZA－200 正常值为 4 kPa 左右，（4±2） kPa（即 2 kPa<PDIZA-200<6 kPa）以 外 报警，（4±5） kPa（即-1 kPa<PDIZA-200<9 kPa）以外 连锁。故必须确保对氯气、氢气及二者之间差压检测 的变送器 PT－216、PT－226、PDT－200 精确、真实、稳 定、可靠，避免因仪表检测不准达到连锁值而造成烧 碱装置停车。 1．4 烧碱溶液浓度
12
中国氯碱
精盐水 高位槽
FIT-231
FCV-231
去电解槽 （阳极室）
2009 年第 9 期
比值器2
从动量 FICA 265
FICZA 231
电解槽电流 比值器1 IIZA230
淡盐水槽 D-260
FIT-265
FCV-265
去电解槽 （阳极室）
图 1 进电解槽精盐水与返回电解槽淡盐水流量控制简图
（2）保护装置选用 SEL－351A、SEL－501－2 装置， 实现过负荷、过流、速断、低电压保护和故障录波、事 件记录以及工艺连锁保护等功能。
（3）测量、计量选用深圳中电的 PMC－560 装置， 对线路的电流、电压、功率因数、实时功率、实时功 率、电能等进行监测。其装置同时还具有 56 次谐波， 故障录波（36 周）和事件记录功能，通过 13 个 DI，实 现信号和状态的采集功能。
电解生产中各工艺参数的关系
4）.两水平
◆铝水的作用： ①作为阴极，防止铝在碳阴极表面上析出 ②传导阳极中心热量，调节热平衡 ③削弱电磁力稳定磁场 通常我们认为，适当提高铝液高度，可有效降低水平 电流，同时电解槽热容存储能力增强，可提高电解槽热稳 定性，从而提高电解槽电流效率。但是，过高的铝液水平 可能会造成槽侧部通过铝液层散热增加，易导致槽底沉淀 产生，增加槽帮结壳伸腿的厚度。 ◆电解质的作用： ①阴、阳极之间的导体 ②电化学反应的区域 ③电解槽热稳定的基础
◆过热度：控制较低窄的过热度（8--15℃），是获 得较高电流效率的必要条件。如果过热度较高，铝液与电 解质液面的表面张力减小 ，铝在电解质中的溶解度增大 ， 铝的二次损失就会增加，电流效率降低；但如果过热度过 低 ， 则会导致电解质发粘 ，电解质导电率下降，极距缩 小 ，另一方面 ，氧化铝的溶解性能变差 ，电解槽发冷， 槽况变差，电流效率也会降低。
五、我厂的工艺参数设置及要求
6）.效应系数
科学合理地利用阳极效应是保证电解槽正常生产的重要手段，同时 也能提高电流效率。利用效应可以校正氧化铝浓度，清洁电解质，清 理炉底沉淀，均衡电解槽各部位温度的，规整炉膛的作用。但效应也 对稳定生产破坏很大，效应发生时，电解温度迅速上升，炉帮熔化变 薄，增加了侧部硅砖被浸蚀的可能性，而且温度和炉帮要1小时左右才 能恢复正常值。有实验表明：当效应系数为1.0时，电流效率降低0.6---0.8%，直接增加能耗200KWH,考虑到电流效率的同时降低，一个阳 极效应（3分钟）会增Байду номын сангаас吨铝电耗300KWH。
2.电解槽电解质电压。电解槽的电解质电压，即极距电 压，一般在1.3V—1.8V之间，主要受电流强度、电解质温 度、电解质成分、极距高低影响。 3.电解槽气泡电压。一般来说，阳极下的气泡压降约为 150mV—250mV。 4.电解槽阳极组电压。电解槽的阳极组电压包括：夹具 压接压降、阳极导杆压降、阳极爆炸焊块连接压降、钢爪 压降、铁炭压降以及阳极炭块压降。 5.电解槽阴极电压。电解槽的阴极电压包括：阴极炭块 压降、炭块与阴极钢棒连接压降、阴极钢棒压降。 6.电解槽母线电压。电解槽母线压降包括：钢棒与阴极 母线过渡压降、阴极母线压降。
文献赏析：采用先进的两点法分析极片电阻率的各影响因素,元能科技（厦门）有限公司
1.分离电压电流线，排除电感对电压测量的影响，提⾼检测精度；
2.直径14mm圆盘电极，保证与样品有相对⼤的接触⾯积，减⼩测试误差；
3.直接测量真实极⽚纵向穿透电阻，即涂层电阻、涂层与集流体接触电阻、集流体电阻的总和；
4.可实时监控极⽚电阻、极⽚厚度和极⽚压密随压强的变化；
5.可精确控制施加压强，保证测试数据的⼀致性；
极⽚电阻可以较好地评价电极制作过程中电⼦导电⽹络的性能或电极微观结构的均匀性，助⼒研究和改进电极的配⽅以及混合、涂布和辊压⼯艺的控制参数。
参考⽂献
B.G. Westphal et al. Influence of high intensive dry mixing and calendering on relative electrode resistivity determined via an advanced two point approach. Journal of Energy Storage 2017, 11, 76–85。
高锂电解质对铝电解生产的影响及改善措施
摘要 ： 通 过 热 力 学 数 据 对 锂 盐 的存 在 形 式 及 反 应 过程 进行 计 算 ， 并 分 析 了 高 锂 电解 质 对 初 晶 温 度 及 氧 化 铝 溶 解 度 的 影 响 。最 后通 过对 某 铝 厂 ４ ０ ０ ｋ Ａ 系列高锂 电解 质体系 电解槽焙 烧启 动过程 、 启 动 后 期 管
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对电解工艺参数的影响
对电解工艺参数的影响
电解工艺参数是指在电解过程中，通过调整控制某些参数来影响电解效果和产品质量的因素。
以下是一些常见的电解工艺参数及其影响：
1. 电流密度：电流密度是指通过单位面积的电流量，它直接影响电解速度和产物的质量。
适当增大电流密度可以加快电化学反应速率，但过高的电流密度可能会导致产物质量下降和电解槽发热增加。
2. 温度：温度是电解反应速率的重要因素，一般情况下，温度升高有利于电解反应的进行。
较低的温度会降低反应速率和产物质量。
3. 电解时间：电解时间是指电解过程中所需的时间，它与电解产物的厚度和均匀性有关。
适当增加电解时间可提高产品的质量，但过长的电解时间可能会造成资源的浪费。
4. 电解液浓度：电解液浓度直接影响电解效果。
适宜的电解液浓度可以提高反应速率和产物质量。
5. 电解槽设计：电解槽的设计对电解过程有重要影响。
如槽体的材料、形状、尺寸等都会影响电解效果和产物质量。
6. 水质：电解过程中的水质也会对电解效果产生影响。
特别是对于需要电解制
备高纯度产品的工艺，如半导体材料制备等，水质的纯净度是非常重要的。
综上所述，电解工艺参数对电解效果和产品质量有重要影响。
因此，在电解过程中合理调整和控制这些参数是保证电解效果和产品质量的关键。
电解工艺对电解铜箔组织与性能影响的研究
电解工艺对电解铜箔组织与性能影响的探究电解工艺是现代铜箔生产过程中的重要环节之一，其能够直接影响铜箔的组织与性能。
本文通过分析不同电解工艺对电解铜箔组织与性能的影响，探究最优电解工艺的选取以及其对电解铜箔性能的影响。
在探究中发现，电解工艺对电解铜箔晶粒大小、晶体形态、晶格畸变、杂质率、电阻率等方面存在着较大的影响。
选择适合的电解工艺能够明显提高电解铜箔的延展性、屈服强度、表面质量等性能指标，为电解铜箔生产和应用提供了有效的技术支持。
关键词：电解工艺；电解铜箔；组织；性能；影响电解工艺对电解铜箔组织与性能影响的探究一、引言铜箔作为一种重要的工程材料，在电子、机械、传感器等领域得到了广泛的应用。
电解铜箔是指通过电化学方法在铜质基板上沉积出的一层薄膜，具有良好的延展性、导电性和热导率等性能。
电解工艺是决定电解铜箔组织与性能的重要环节之一，其优劣直接影响着电解铜箔的质量和应用效果。
随着电子行业的不息进步，对铜箔的性能要求也日益提高。
传统的电解工艺逐渐无法满足生产和应用的需求，因此需要进行一系列深度的探究。
近年来，国内外学者对电解工艺的影响进行了广泛的探究，发此刻不同电解工艺下，电解铜箔的组织与性能存在着差异。
因此，对电解工艺对电解铜箔的影响进行深度探究，对提高电解铜箔的质量和应用效果具有重要意义。
二、电解工艺对电解铜箔组织的影响（一）晶粒大小晶粒大小是衡量电解铜箔组织细度的重要指标之一，其大小直接干系到电解铜箔的延展性、焊接性和导电性能。
目前普遍接受的电解工艺为铜盐水解电解法、酸性电解法和硫酸电解法。
不同电解工艺对电解铜箔晶粒大小的影响存在明显差异。
铜盐水解电解法可以使电解铜箔晶粒细小而匀称，高参数下电化学活性增强，晶粒尺寸呈现出秀丽的形态，并且晶界位错密度较高；但是，该工艺存在电流效率低、耗能大、铜离子浓度难以控制等问题。
酸性电解法可以通过控制电解液的组成、温度等条件，使晶粒得到不息细化和匀称化，晶粒表面产生多种织构，杂质和静电荷载均得到有效控制；但是，该工艺存在铝和氧离子的腐蚀性较强、工艺复杂等问题。
LQFP塑封电路第二焊线区分层影响因素分析
LQFP塑封电路第二焊线区分层影响因素分析王津生;叶德洪;高伟;陈泉;郭会会【摘要】This paper discussed the effecting factors that may impact delamination between second bond and EMC in LQFP packages. The factors included assembly process control,package material, lead frame design, elc. Results of the experiments showed that the delamination between second bond and EMC was related to process control,but proper EMC selection and lead frame design could eliminate the delamination and improve it significantly after reliability testing. All the experimental conclusions were based on statistical analysis of the experimental data with JMP statistical analysis software.%讨论了在薄型四方扁平封装技术在封装形式中影响塑封胶材料和第二焊线区之间的分层因素,从封装工艺控制,封装材料的使用及框架设计等诸多影响因素中进行了分析实验.结果显示,虽然封装过程中的工艺参数会影响第二焊线区的分层,但通过选择更合适的塑封胶材料及引线框架,不仅可以消除封装后的分层,还可以显著改善可靠性试验后的分层结果.所有实验结论都是在统计分析软件对实验数据进行统计分析后得出的.【期刊名称】《电镀与精饰》【年(卷),期】2012(034)007【总页数】6页(P25-30)【关键词】薄型四方扁平封装技术;第二焊线区分层;塑封胶;电镀;焊线;引线框架【作者】王津生;叶德洪;高伟;陈泉;郭会会【作者单位】飞思卡尔半导体(中国)有限公司,天津 300385;飞思卡尔半导体(中国)有限公司,天津 300385;飞思卡尔半导体(中国)有限公司,天津 300385;飞思卡尔半导体(中国)有限公司,天津 300385;飞思卡尔半导体(中国)有限公司,天津 300385【正文语种】中文【中图分类】TQ320.6塑封集成电路(IC)是通过热固型环氧树脂把铜合金或具有镍、钯及金镀层的铜合金的引线框架和芯片的组合包封起来的一种封装形式。
半导体封装产品分层问题浅析-刘文强
半导体封装分层问题的浅析Analysis on the Delamination Issue of Semiconductor Packaging刘文强(江苏中鹏新材料股份有限公司）摘要：自1965年环氧模塑料（EMC）诞生以来，逐渐以其高可靠性、低成本、生产工艺简单等优越性替代了陶瓷和金属封装，成为目前封装材料的主流。
但是由于塑封料存在较高的吸湿性，而器件在生产和测试过程中，不可避免的要经过高温或高湿环境，潮气膨胀后会造成内部应力过大，形成分层，金线断裂等后果。
同时由于塑封料与Si、Cu等其他材质膨胀系数的差异，也很容易在较大的剪切应力下形成分层。
本文主要讲述塑封料与芯片、基岛和框架之间的分层，及其失效的原因与模式，并且对于分层提出了有效的改进措施。
Abstract:EMC,born in1965,with the advantages of high reliability,low cost and simple production process,gradually replace the ceramic and metal packages and become the main stream package material. However,for its water absorption sensitivity,it appears delamination and gold wire break while testing and producing because of high internal stress under inevitable high temperature and high moisture environment.At the same time,the CTE differences between EMC,Si and Cu also easily form a heavy stress and lead to delamination.This thesis focuses on the delamination between EMC and chip,pad and lead frame,as well as failure cause and mode.By analyzing these,this thesis points out some effective improvements.关键词：塑封料、电子封装、分层失效原因、失效检验、可靠性分析Key Words:Epoxy molding compound,Electrical packaging,failure analysis on delamination,failure inspection, reliability analysis1概述1.1塑封料概述环氧模塑料由邻甲酚醛环氧树脂、线性酚醛树脂、填充料二氧化硅粉（俗称硅微粉）、促进剂、偶联剂、改性剂、阻燃剂、着色剂等组分组成。
酸碱性去溢料产品的优缺点
酸碱性去溢料产品的优缺点第一篇：酸碱性去溢料产品的优缺点酸碱性去溢料产品的优缺点去溢料工序，是电镀前处理工序中看似简单实则重要的一步，其主要目的是去除引线框架上在塑封步骤残留的溢胶以及透明的蜡状物质。
如果在去溢料工艺没能把以上两种残留的溢料去除干净，在电镀过程中会造成露铜，镀层发花，焊接性不好等严重的不良。
因此去溢料工艺在电子封装工艺里是非常重要的前处理工序。
溢料的形成，主要是在塑封工艺中，由于引线框架和塑封模具之间的存在缝隙，因是使用高压把热熔的塑封料挤压去的，所以会有塑封材料从缝隙中渗漏出来，固化在引线体表面，形成黑色溢料，我们一般称之为胶渣。
还有部分溢料是由于塑封体本身的树脂渗出，而在塑封体周围形成的透明薄膜，我们称之为溢料。
透明的溢料在电镀前很难通过肉眼发现，一般都是在电镀后由于电镀漏镀露铜才能发现，所以造成的电镀不良率一般超过’胶渣’。
在去溢料工艺中，我们需要把以上两种溢料全部去除干净，来保证电镀质量。
在明白了溢料形成的原理后，我们可以针对溢料采取相应的工艺流程来去除溢料。
去溢料工艺有水喷沙法；电解+机械去除法和化学浸泡+机械去除法。
传统上使用水喷沙法：利用高压水，混合适硬度的’沙粒’喷出，去除溢料。
但这种工艺会对塑封体表面的状况有所改变，并且水压太大的话可能会对芯片产生影响。
一般使用在油墨印字的产品上，可提高油墨的附着力。
而目前大部分的去溢料流程属于后二者，包括软化和机械去除两步骤，其中以化学软化居多。
首先，利用化学品浸泡，使附着在引线框架上的胶渣和溢料充分软化，并与塑封体分离。
之后，再使用机械方法，将已软化的溢料去除。
软化流程一般是在加热的情况下，将材料浸泡在化学品溶液中，使溢料充分软化。
再经过高压水、雷射光或者使用铜刷将软化的溢料去除。
这种方法不会改变塑封体表面的状况，更适合激光镭射印字的产品。
当然，如果溢料非常严重，也可以先进行软化，再使用喷沙的方法对溢料进行去除，但需要进行实验以确认材料的可靠性。
电解参数对循环冷却水处理及倒极除垢效果的影响
电解参数对循环冷却水处理及倒极除垢效果的影响（图文无关）本文利用电化学法处理循环冷却水，探究电解参数对处理效果的影响，并探究不同倒极条件对阴极结垢的剥离效果和剥离方式。
结果表明，当水质硬度为800 mg/L、Cl-质量浓度为567.2 mg/L、电流密度为10 mA/cm2、水力停留时间为10 min时，硬度去除质量浓度为300 mg/L，Cl-去除质量浓度为140 mg/L，活性氯质量浓度为8.74 mg/L，电流效率为88.44%；在除垢时间为8 min，倒极电流密度为5 mA/cm2的条件下，阴极结垢剥离率达到了94.3%，以物理脱落为主。
倒极电流密度过高会造成水质硬度上升，除垢时间过长会造成电极腐蚀。
敞开式的循环冷却水系统在工业中的应用非常广泛，其在长期运行过程中存在腐蚀、结垢和生物黏泥等问题。
工业上主要通过添加阻垢剂来抑制系统结垢，但该方法存在化学试剂投加量大、容易造成二次污染等问题。
电化学法作为一种环境友好型技术，在循环冷却水处理中具有良好的工业应用价值。
目前，国内外对电解循环冷却水的研究主要集中在可行性研究、电极材料和电化学反应器的结构等方面，对电解参数和阴极结垢剥离方式的研究仍然存在不足。
传统的机械刮削法需要在阴极和阳极之间安装刮刀来周期性地刮除阴极上的结垢，但机械刮刀的安装需要占据较大的空间，并且增大了阴极和阳极的极间距，造成硬度去除效率降低，能耗增加。
本研究以人工配制的模拟硬水为研究对象，探究了不同电解参数对模拟硬水的处理效果，针对在电解过程中阴极结垢较严重的现象，采用倒极方法剥离阴极垢层，并探究了不同倒极电流密度和除垢时间下，阴极结垢的剥离效果和剥离方式。
1实验部分01实验装置及材料本研究采用的实验装置见图1。
图1 实验装置电解槽有效容积为500 mL，阳极采用钛基钌铱电极，阴极采用不锈钢电极，电极间距为1.5 cm，有效电解面积为24 cm2。
用NaHCO3和CaCl2按物质的量比为2:1的比例配制模拟硬水。
电解抛光主要缺陷
电解抛光主要缺陷1、铝材及铝件在电解抛光过程中最常见的缺陷是白霜或结霜现象。
白霜究竟是什么物质，成分如何，目前尚无定论，有人认为是磷酸铝析出物，也有人认为是铝表面形成的钝化膜。
白霜可在工件的局部形成，因为那里的氧化膜形成不够快，从而造成电解不足以取代阳极氧化。
若取出工件，清洗后并重新电解抛光时，氧化物会溶解，白霜也会随着消失，然而又可在别处产生。
调整溶液成分与改变处理工艺可控制这类缺陷的产生。
例如，在磷酸一硫酸溶液中电解抛光时，磷酸浓度过高、硫酸浓度过大或过小都可引起白霜，温度太低、电流密度不恰当也会诱发这类缺陷。
1.1溶液成分对白霜的影响磷酸在电鹂抛光过程中主要作用是溶解氧化膜与铝：AL(H2PO4 )3 在铝有面附近浓集，形成糖浆状粘性膜层，对工件表面抛光即整平与光亮起着决定性的作用，但也对白霜的形成有很大影响。
冯宝义等研究证明，在磷酸(3O％～4O％)一硫酸(2o％-30％)一PEG添加剂(20％～3O％)溶液中电解抛光(温度8o℃～90℃、电流密度30-4O 安每平方分米)时，增加磷酸浓度，可提高工件的光亮度、降低电流密度、减少电耗，但磷酸含量过高，会出现白霜”(表24)。
电解抛光液中的硫酸有如下的作用：稳定电解抛光过程，降低抛光温度，提高溶液电导率，降低工作电压，减少能源消耗，可增加铝的允许含量，延长槽液寿命。
然而，硫酸的含量超过一定限度后，会增强溶液的氧化能力，使电解抛光向着有利于阳极氧化过程的方向转变，从而在工件表面诱发白霜；硫酸含量过低，也可使铝表面产生白霜。
因此，应始终使溶液中的硫酸含量保持在工艺规程的允许最佳范围内。
大多数电解抛光液中都含有醇之类的添加剂，因为醇分子间可形成氢键而发生缔合作用，在被抛光工件表面形成粘性膜层，使其凹陷处处于稳定的钝化状态．而凸突处则以更快的速度溶解．最后获得平滑光亮的表面。
醇分子的缔台结构为：这就是小分子醇常常用作电解抛光溶液舔加剂的主要原因，但大分子多元醇聚合物也可作抛光液添加剂。
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２ ０ １ ３ 年１ ０ 月
电 镀 与 精 饰
第３ ５ 卷第 ｌ ０ 期（ 总２ ４ ７ 期） ・ ２ ７・
ｄ ｏ ｉ ： １ ０ ． ３ ９ ６ ９ ／ ｊ ． ｉ ｓ ｓ ｎ ． １ ０ ０ １ — ３ ８ ４ ９ ． ２ ０ １ ３ ． １ ０ ． ０ ０ ７
电解 去 溢 料 工序 参 数 对 Ｉ Ｃ封 装体 第 二 焊 线 区分 层 的 影 响
叶德 洪 ， 王 津 生
（ 飞思 卡尔半 导 体 （ 中 国） 有 限公 司 ， 天津 ３ ０ ０ ３ ８ ５ ）
摘要 ： Ｉ Ｃ封 装体 的 内部分层 是 封装 过 程 中常 见 的质 量 问题 。讨 论 了 引线框 架 电镀 工 艺 对 Ｉ ｃ封 装 体 第二 焊 线 区分层 的影 响 ， 并确 定 了电镀 工 艺的 电解 去 溢料 工序 是使 其 分 层 的 主要 因素 。通 过 实 验 分析 并验 证 了电解去 溢料 工序 的 电压 、 电解 电极 的极 性 、 电解 液 的类型及 其 浓度 对 第二 焊 线 区分
Ａｂｓ ｔ ｒ ａ ｃ ｔ ：Ｉ ｎ ｔ ｅ ｒ ｎ ａ ｌ ｄ ｅ ｌ ａ ｍｉ ｎ ａ ｔ ｉ ｏ ｎ ｉ ｓ ａ ｑ ｕ ａ ｌ ｉ ｔ ｙ ｐ ｒ ｏ ｂ ｌ ｅ ｍ ｕ ｓ ｕ ａ ｌ ｌ ｙ ｆ ｏ ｕ ｎ ｄ ｄ ｕ ｒ ｉ ｎ ｇ Ｉ Ｃ ｐ ｌ ａ ｓ ｔ ｉ ｃ ｐ ａ ｃ ｋ ａ ｇ ｉ ｎ ｇ ． Ｈｏ ｗ ｔ ｏ
ｇ ｅ ｒ ｗａ ｆ ｅ ｒ ． Ｔｈ ｅ ｓ ｅ ｅ ｖ ａ ｌ ｕａ ｔ ｉ ｏ ｎ ｒ ｅ ｓ ｕ ｌ ｔ ｓ ｗｉ ｌ ｌ ｃ ｏ ｎ ｔ ｉｂ ｒ ｕｔ ｅ ｍｏ ｒ ｅ ｔ ｏ ｔ ｈｅ ｐ ａ ｃ ｋ ａ ｇ ｅ ｄ ｅ ｓ ｉ ｇ ｎ ａ ｎ ｄ ａ ｓ ｓ ｅ ｍｂ ｌ ｙ ｉ ｎ ｔ ｈ ｅ ｆ ｕ ｔ ｕ ｒ ｅ ． Ｋｅ ｙ ｗｏｒ ｄｓ：Ｉ Ｃ ｐｌ ａ ｓ ｔ ｉ ｃ ｐ ａ ｃ ｋ ａ ｇ ｉ ｎｇ；ｓ ｅ ｃ ｏ ｎ ｄ ｂ ｏ ｎ ｄ ｄ ｅ ｌ ａ ｍｉ ｎａ ｔ ｉ ｏ ｎ； ｐ ｌ ａ ｔ ｉ ｎ ｇ； ｅ ｌ ｅ ｃ ｔ ｒ ｏ — ｄ ｅ ｌａ ｆ ｓ ｈ；ｌ ｅ ａ ｄ ｆ ｒ ａ ｍｅ
ａ ｖ ｅ ｌ ａ ｍ ｉ ｎ ａ ｔ ｉ ｏ ｎ ｉ ｓ ａ ｃ ｏ ｍｍ ｏ ｎ ｒ ｅ ｓ ｅ ａ ｒ ｃ ｈ ｓ ｕ ｂ ｊ ｅ ｃ ｔ ． Ｉ ｎ ｔ ｈ ｉ ｓ ｐ ａ ｐ ｅ ｒ ， ｔ ｈ ｅ ｉ ｍ ｐ ａ ｃ ｔ ｓ ｏ ｆ ｌ ｃ ａ ｄ
ｓ ｏ ｌ ｕ ｔ ｉ ｏ ｎ ． Ｃｏ ｍｐ ａ ｒ ｅ ｄ ｗｉ ｔ ｈ ｔ ｈ ｅ ２ｎ ｄ ｂ ｏ ｎ ｄ ｄ ｅ ｌ ａ ｍｉ ｎ ａ ｔ ｉ ｏ ｎ ｐ ｅ ｒ ｆ ｏ ｒ ｍａ ｎ ｃ ｅ ｉ ｎ ｄ ｉ ｆ ｆ ｅ ｒ ｅ ｎ ｔ ｐａ ｃ ｋ ａ ｇ ｅ ｄ ｅ ｓ ｉ ｇ ｎ ｓ ｗｉ ｔ ｈ ｔ ｈ ｅ ｓ ａ ｍｅ ｄ ｅ ｌａ ｆ ｓ ｈ ｃ ｏ ｎ ｄｉ ｔ ｉ ｏ ｎ． ｉ ｔ ｗａ ｓ ｏ ｂ ｔ ａ ｉ ｎ ｅ ｄ ｔ ｈａ ｔ ｅ ｌ ｅ ｃ ｔ ｒ ｏ ． ｄ ｅ ｌａ ｆ ｓ ｈ ｉ ｓ ｕ ｎ ｓ ｕ ｉ ｔ ａ ｂ ｌ ｅ ｏｒ ｆ ｓ ｏ ｍｅ ｓ ｍａ ｌ ｌ ｐａ ｃ ｋ ａ ｇ ｅ ｓ ｗｉ ｔ ｈ ｌ ａ ｒ —
层 的影 响 。通过 对 不 同封 装 体 第二 焊 线 区分层 程度 的 比较 ， 认 识 到 电解 去 溢料 对 一 些 大载 荷 小封 装的 Ｉ Ｃ封 装体 是 不适 用 的 ， 极 易引起 第． ２ － 焊 线 区分层 ， 从 而使 Ｉ Ｃ产 品存在 失 效的风 险。 实验评 估 的结果 为今后 的封装 体设 计及 生产 工 艺提供 了可借 鉴 的经验 。 关 键 词： Ｉ Ｃ封 装 ；第二焊 线 区分层 ；电镀 ；电解 去溢料 ；引线框 架 文献标 识码 ：Ｂ 中图分 类号 ： Ｔ Ｑ ３ ２ ０ ． ６
ＹＥ Ｄｅ — ｈ ｏ ｎ ｇ，Ｗ ＡＮＧ Ｊ ｉ ｎ — ｓ ｈ ｅ ｎ ｇ
（ Ｆ ｒ ｅ ｅ ｃ ａ ｌ ｅ Ｓ ｅ ｍ ｉ ｃ ｏ ｎ ｄ ｕ ｃ ｔ ｏ ｒ（ Ｃ ｈ ｉ ｎ ａ ）Ｌ ｉ ｍ ｉ ｔ ｅ ｄ ， Ｔ ｉ ａ ｎ ｊ ｉ ｎ ３ ０ ０ ３ ８ ５， Ｃ ｈ ｉ ｎ ａ ）
ｆ ｒ ａ ｍｅ ｐｌ ａ ｔ ｉ ｎ ｇ ｐ ｒ ｏ ｃ ｅ ｓ ｓ ｏ ｎ ｔ ｈ ｅ ２ ｎｄ ｂｏ ｎ ｄ ｄ ｅ ｌ ａ ｍｉ ｎａ ｔ ｉ ｏ ｎ ｆ ｏ ｒ Ｉ Ｃ ｐ ａ ｃ ｋ ａ ｇ ｅ ａ ｎ ｄ ｉ ｄ ｅ ｎ ｔ ｉ ｉｅ ｆ ｓ ｅ ｌ ｅ ｃ ｔ ｒ ｏ — ｄ ｅ ｌａ ｆ ｓ ｈ ａ ｓ ａ ｋ ｅ ｙ ｆ ａ ｃ ｔ ｏ ｒ ｉ ｎ ｔ ｈ ｅ ｐ ｌ ａ ｔ ｉ ｎ ｇ ｐ ｒ ｏ ｃ ｅ ｓ ｓ ｗｅ ｒ ｅ ｄｉ ｓ ｃ ｕ ｓ ｓ ｅ ｄ． Ｅｘ ｐ ｅ ｉｍｅ ｒ ｎ ｔ ｓ ｓ ｈ ｏ ｗ ｔ ｈ ａ ｔ ｔ ｈ ｅ ２ｎ ｄ ｂ ｏ ｎ ｄ ｄｅ ｌ ａ ｍｉ ｎ ａ ｔ ｉ ｏ ｎ ｉ ｓ ｒ ｅ ｌ ａ ｔ ｅ ｄ
Ｉ ｍｐ ａ ｃ ｔ ｓ ｏ ｆ Ｅｌ ｅ ｃ ｔ ｒ ｏ － ｄ ｅ ｌａ ｆ ｓ ｈ Ｐｒ ｏ ｃ ｅ ｓ ｓ ｉ ｎ ｇ Ｐａ ｒ ａ ｍｅ ｔ ｅ ｒ ｓ ｏ ｎ ２ ｎ ｄ
Ｂｏ ｎｄ Ｄｅ ｌ ａ ｍｉ ｎ ａ ｔ ｉ ｏ ｎ ｆ ｏ ｒ Ｉ Ｃ Ｐｌ ａ ｓ ｔ ｉ ｃ Ｐａ ｃ ｋａ ｇ ｉ ｎ ｇ