Computational methods for the exploration of potential energy surfaces with applications to nanoalloy materials.

探索势能表面的计算方法及其在纳米合金材料中的应用。

• 批准号: RGPIN-2014-05698
• 负责人: Fournier, Rene
• 金额: $ 2.48万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=632391
• 关键词: Computational; methods; exploration; potential; energy

We develop high performance computational methods to explore potentialenergy surfaces (PES, mathematical functions that describe how the energy ofmolecules changes when the geometry of the molecule changes), thus providing thefoundation for studies of molecular structure and chemical reactivity. Successful implementationof this proposal will create a unique set of computational tools for studyingmolecular structures, transition states, and reaction paths,and for the simulation of systems with hundreds of atoms. These toolswill be of great importance to researchers in Canada and beyond.One of our methods mimics DFT and gives a computational speed-up of 4 to 6 orders of magnitude. It will allow the study of nanoalloyswith potential applications in catalysis and data storage devices.Taking clues from our recent discovery of bimetallic cages,we will search for new and bigger all-metal cages.Minima of the PES are equilibrium geometries of molecules; saddle points aretransition states; steepest descent lines connecting saddle points to minima are reaction paths;low energy regions in the vicinity of steepest-descent lines are importantfor detailed models of reaction mechanisms. We will continue to makeexpert use of quantum chemistry and density functional theory(DFT), combined with our own computer codes, to investigate PES. Students will get trained in research projects that combine method developmentand applications and will acquire a variety of skills: expertise in UNIXand quantum chemistry software, programming and shell scripting, mathematicalmodeling, and general scientific literacy. The projects are designed atvarious levels to address the needs and capabilities of undergraduate, postgraduate, and postdoctoral students.We will work on three fronts to study nanoalloys that have interestingproperties and potential use in catalysis and information technologies. (1) Global optimization. Evolutionary computing methods, like GeneticAlgorithms (GA), will be developed to determine the geometric structureof nanoalloy clusters. (2) Reaction mechanisms. We have used Particle Swarm Optimization (PSO)to discover, without human supervision, the sequence of geometric transformationsthat occur in molecules during chemical reactions (``reaction mechanisms''). We willcreate a new method, based on chemical intuition and optimization techniques, to find a priori(without any DFT calculation) reaction mechanisms. We will find, on a case-by-case basis, whether this mechanism is a good approximation to thelowest-energy reaction path (the true mechanism), and will classify chemical reactions accordingly. (3) Atomistic simulations. We developed a new fitting method for creatinghigh-dimensional PES that is fully automated, does not requirethe user to input a function form, and which works for practically anychemical composition. This PES function mimics an accurate method (DFT) and offers aspeed-up of 4 to 6 orders of magnitude relative to DFT. We will use it to carry outaccurate Monte Carlo (AIMC) simulations where the PES is used with "importance sampling"to give great computational speed-up. We will also take a two-pronged approachto global optimization where we use the PES function for screeninga large number of geometric structures and generate a much smaller subsetfor which the DFT energy gets calculated.Working on those three fronts we will try to uncover the principles thatgovern the relative stability and geometric structure, and the magnetic,electronic and chemical properties of bimetallic clusters. Based on theseprinciples, and novel methods unique to our group, we will design stablenanoalloys for possible applications in catalysis and magneticdata storage devices.

我们开发了高性能的计算方法来探索势能面（PES，描述分子几何形状变化时分子能量如何变化的数学函数），从而为分子结构和化学反应性的研究提供了基础。这一提议的成功实施将为研究分子结构、过渡态和反应路径以及模拟具有数百个原子的系统创造一套独特的计算工具。这些工具将是非常重要的研究人员在加拿大和超越。我们的方法之一模仿DFT，并给出了4至6个数量级的计算速度。从我们最近发现的全金属笼出发，我们将寻找新的、更大的全金属笼，PES的极小值是分子的平衡几何，鞍点是过渡态，连接鞍点和极小值的最陡下降线是反应路径，最陡下降线是过渡态，最陡下降线是过渡态，最陡下降线是过渡态。最陡下降线附近的低能区对于反应机理的详细模型是重要的。我们将继续利用量子化学和密度泛函理论，结合我们自己的计算机程序，来研究PES。学生将在联合收割机方法开发和应用相结合的研究项目中接受培训，并将获得各种技能：UNIX和量子化学软件，编程和shell脚本，数学建模和一般科学素养的专业知识。这些项目是针对不同层次的本科生、研究生和博士后学生的需求和能力而设计的。我们将在三个方面开展工作，研究在催化和信息技术方面具有有趣特性和潜在用途的纳米合金。(1)全局优化。进化计算方法，如遗传算法（GA），将被开发来确定纳米合金团簇的几何结构。(2)反应机制。我们已经使用粒子群优化（PSO）发现，没有人的监督，几何transformationsthat发生在化学反应（“反应机制”）的分子序列。我们将创建一个新的方法，基于化学直觉和优化技术，找到一个先验（没有任何DFT计算）的反应机制。我们将根据具体情况来确定这种机制是否是最低能量反应路径（真正的机制）的一个很好的近似，并将相应地对化学反应进行分类。(3)原子模拟。我们开发了一种新的拟合方法，用于创建高维PES，是完全自动化的，不需要用户输入函数形式，并适用于几乎任何化学成分。该PES函数模拟了精确方法（DFT），并提供了相对于DFT的4到6个数量级的加速。我们将使用它来进行精确的蒙特卡罗（AIMC）模拟，其中PES与“重要性采样”一起使用，以提高计算速度。我们还将采取双管齐下的方法来进行全局优化，即使用PES函数筛选大量的几何结构，并生成一个小得多的子集来计算DFT能量。在这三个方面，我们将试图揭示控制团簇的相对稳定性和几何结构以及磁性，电子和化学性质的原则。基于这些原理和我们小组独有的新方法，我们将设计稳定的纳米合金，用于催化和磁性数据存储设备。