10计算材料物理-第四章

随机抽样方法
Random Sampling methods involve in the random generation of a large number of structures on PES;
AIRSS (ab initio random structure searching)
http://www.cmmp.ucl.ac.uk/~ajm/airss/airss.html http://iopscience.iop.org/0953-8984/23/5/053201
Predictions of the energetically stable/metastable structures at given chemical compositions and external conditions (e.g., pressure) for clusters, 2D layers, surfaces, and 3D crystals.
该算法最初是受到鸟群活动的规律性启发，进而利用群体 智能建立的一个简化模型。粒子群优化算法利用群体中的 个体对信息的共享使整个群体的运动在问题求解空间中产 生从无序到有序的演化过程，从而获得最优解。
PSO同遗传算法类似，是一种基于迭代的优化算法。系统 初始化为一组随机解，通过迭代搜寻最优值。但是它没有 遗传算法用的交叉(crossover)以及变异(mutation)，而是 粒子在解空间追随最优的粒子进行搜索。同遗传算法比较， PSO的优势在于简单容易实现并且没有许多参数需要调整。 目前已广泛应用于函数优化，神经网络训练，模糊系统控 制以及其他遗传算法的应用领域。
USPEX
Universal Structure Predictor: Evolutionary Xtallography
http://www.cmmp.ucl.ac.uk/~ajm/airss/airss.html
Chris J Pickard
State University of New York at Buffalo
XtalOpt runs on a workstation and supports using GULP, VASP, pwSCF (Quantum ESPRESSO), and CASTEP for geometry optimizations.
http://xtalopt.openmolecules.net/wiki/index.fcgi/ http://avogadro.cc/wiki/Main_Page David C. Lonie, Eva Zurek; XtalOpt: An Open-Source Evolutionary Algorithm for Crystal Structure Prediction, Computer Physics Communications 182 (2011) pp. 372-387
社会性动物群体所拥有的这种特性能帮助个体很好地适 应环境，个体所能获得的信息远比它通过自身感觉器官 所取得的多，其根本原因在于个体之间存在着信息交互 能力。
粒子群优化算法
（ Particle Swarm Optimization）
1995年由J. Kennedy, R. C. Eberhart等人提出
The CALYPSO package is protected by the Copyright Protection Center of China with the registration No. 2010SR028200 and classification No. 61000-7500.
遗传算法(genetic algorithms; GA) 粒子群优化算法(particle swarm
optimization; PSO) 蚁群优化算法(ant colony optimization; ACO)
遗传算法
Swarm Intelligence 群体智能
Swarm可被描述为一些相互作用相邻个体的集合体，蜂 群、蚁群、鸟群都是Swarm的典型例子。
Freely distributed on Academic use under the regulations termed in the CALYPSO_LICENCE.
http://www.calypso.cn/
马琰铭 教授 吉林大学 超硬材料国家重点实验室
王彦超
吕健
朱黎
CALYPSO
WHAT IS THE FEATURE?
Major Techniques Employed
Structural evolution through PSO algorithm. PSO is best-known for its ability to conquer large
barriers of energy landscapes by making use of the swarm intelligence and by self-improving structures. Both global and local PSO algorithms have been implemented. The global PSO has the advantage of fast convergence, while local PSO is good at avoiding premature convergence and thus enhance the capability of CALYPSO in dealing with more complex systems.
2D layers by Wang, Miao, et al, in 2012
2D surface reconstruction by Lu et al, in 2014
Structure searching efficiencies of isolated systems have been substantially improved by the CALYPSO team (Lv, Wang, Zhu & Ma) in 2012, where the success of this application has been backed up with the introduction of various efficient techniques (e.g., bond characterization matrix for fingerprinting structures, symmetry constraints on structure generation, etc.).
结构搜索和预测程序
AIRSS
Ab initio Random Structure Searching
GASP
Genetic Algorithm for Structure and Phase Prediction
CALYPSO
Crystal structure AnaLYsis by Particle Swarm Optimization
Design of novel functional materials, e.g., superhard materials.
Options for the structural evolutions using global or local PSO.
Structure searches with automatic variation of chemical compositions.
鱼聚集成群可以有效地逃避捕食者，因为任何一只鱼发 现异常都可带动整个鱼群逃避。
蚂蚁成群则有利于寻找食物，因为任一只蚂蚁发现食物 都可带领蚁群来共同搬运和进食。
一只蜜蜂或蚂蚁的行为能力非常有限，它几乎不可能独 立存在于自然世界中，而多个蜜蜂或蚂蚁形成的Swarm 则具有非常强的生存能力，且这种能力不是通过多个个 体之间能力简单叠加所获得的。
翻越势垒方法
模拟退火算法(simulated annealing; SA) 盆地跳算法(Basin-hopping) minima hopping metadynamics algorithm
模拟退火算法
minima hopping
Basin hopping
metadynamics
演化(进化)算法
http://xtalopt.openmolecules.net/globalsearch/docs/tut-xo.html
The Genetic algorithm for structure prediction – GASP – predicts the structure and composition of stable and metastable phases of crystals, molecules, atomic clusters and defects from firstprinciples. The GASP program is interfaced to many energy codes including: VASP, LAMMPS, MOPAC, Gulp, JDFTx and can efficiently run on parallel architectures.
Structure predictions with fixed cell parameters, or fixed space groups, or fixed molecules.
CALYPSO is currently interfaced with GAUSSIAN, DFTB+, VASP, CASTEP, Quantum Espresso, GULP, SIESTA and CP2K codes. The interface with other total energy codes can also be implemented by users' request.
计算材料物理
专题 结构搜索和预测2
Energy
Why is Structure Prediction Hard?
Local minima Global minimum True structure
Atomic positions
Accurate Potential Energy Surface ---- ab initio Huge number of local minima ---- how?
CALYPSO (Crystal structure AnaLYsis by Particle Swarm Optimization) is an efficient structure prediction method and its same-name computer software.
Histowk.baidu.comy of CALYPSO
The CALYPSO team independently initialized the idea of applying PSO algorithm into structure prediction in 2006 (Ma and Wang)
first application of PSO algorithm into structure prediction of 3D crystals by Wang, Lv, Zhu & Ma in 2010,
XtalOpt is a free and truly open source evolutionary algorithm designed to predict crystal structures. It is implemented as an extension to the Avogadro molecular editor.