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

我们开发高性能的计算方法来探索潜在的 能量表面（PES，数学函数，描述能量如何 当分子的几何形状改变时，分子改变），从而提供 分子结构和化学反应性研究的基础。成功实施 这一提议将创造一套独特的计算工具， 分子结构、过渡态和反应路径， 以及数百个原子系统的模拟。这些工具 这对加拿大和其他地区的研究人员来说非常重要。 我们的方法之一模仿DFT，并给出了一个计算加速 4到6个数量级。它将使纳米合金的研究 在催化和数据存储设备中具有潜在的应用。 从我们最近发现的笼子里得到线索， 我们将寻找新的更大的全金属笼子。 PES的极小值是分子的平衡几何形状;鞍点是 过渡状态;连接鞍点到最小值的最陡下降线是反应路径; 最陡下降线附近的低能区是重要的 反应机制的详细模型。我们将继续尽 量子化学和密度泛函理论 (DFT)结合我们自己的计算机代码，研究PES。 学生将得到培训的研究项目，联合收割机方法的发展 和应用程序，并将获得各种技能： 和量子化学软件，编程和shell脚本，数学 建模和一般科学素养。这些项目旨在 各级解决本科生的需求和能力， 研究生和博士后学生。 我们将在三个方面研究纳米合金， 性质和在催化和信息技术中的潜在用途。 (1)全局优化。进化计算方法，如遗传学 算法（遗传算法），将开发，以确定几何结构 纳米合金团簇。 (2)反应机制。粒子群优化算法（PSO） 在没有人类监督的情况下， 在化学反应过程中发生在分子中的化学反应（“反应机制”）。我们将 创造一种新的方法，基于化学直觉和优化技术，找到先验 （没有任何DFT计算）反应机理。我们会发现，在一个 在个案基础上，这种机制是否是一个很好的近似， 最低能量的反应路径（真正的机制），并将相应地分类化学反应。 (3)原子模拟。我们开发了一种新的拟合方法， 高维PES是完全自动化的，不需要 用户输入函数形式，并且其实际上适用于任何 化学成分该PES函数模拟精确方法（DFT），并提供 相对于DFT的4到6个数量级的加速。我们将用它来执行 精确的蒙特卡罗（AIMC）模拟，其中PES与“重要性抽样”一起使用 来提供更快的计算速度。我们也会双管齐下 到全局优化，我们使用PES函数进行筛选 大量的几何结构，并生成一个小得多的子集 计算DFT能量。 在这三个方面工作，我们将试图揭示的原则， 控制着相对稳定性和几何结构，以及磁性， 团簇的电子和化学性质。基于这些 原则，和新颖的方法，我们的小组独特的，我们将设计稳定的 纳米合金在催化和磁性方面的可能应用 数据存储设备。

We develop high performance computational methods to explore potential energy surfaces (PES, mathematical functions that describe how the energy of molecules changes when the geometry of the molecule changes), thus providing the foundation for studies of molecular structure and chemical reactivity. Successful implementation of this proposal will create a unique set of computational tools for studying molecular structures, transition states, and reaction paths, and for the simulation of systems with hundreds of atoms. These tools will 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 nanoalloys with 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 are transition states; steepest descent lines connecting saddle points to minima are reaction paths; low energy regions in the vicinity of steepest-descent lines are important for detailed models of reaction mechanisms. We will continue to make expert 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 development and applications and will acquire a variety of skills: expertise in UNIX and quantum chemistry software, programming and shell scripting, mathematical modeling, and general scientific literacy. The projects are designed at various levels to address the needs and capabilities of undergraduate, postgraduate, and postdoctoral students. We will work on three fronts to study nanoalloys that have interesting properties and potential use in catalysis and information technologies. (1) Global optimization. Evolutionary computing methods, like Genetic Algorithms (GA), will be developed to determine the geometric structure of nanoalloy clusters. (2) Reaction mechanisms. We have used Particle Swarm Optimization (PSO) to discover, without human supervision, the sequence of geometric transformations that occur in molecules during chemical reactions (``reaction mechanisms''). We will create 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 the lowest-energy reaction path (the true mechanism), and will classify chemical reactions accordingly. (3) Atomistic simulations. We developed a new fitting method for creating high-dimensional PES that is fully automated, does not require the user to input a function form, and which works for practically any chemical composition. This PES function mimics an accurate method (DFT) and offers a speed-up of 4 to 6 orders of magnitude relative to DFT. We will use it to carry out accurate 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 approach to global optimization where we use the PES function for screening a large number of geometric structures and generate a much smaller subset for which the DFT energy gets calculated. Working on those three fronts we will try to uncover the principles that govern the relative stability and geometric structure, and the magnetic, electronic and chemical properties of bimetallic clusters. Based on these principles, and novel methods unique to our group, we will design stable nanoalloys for possible applications in catalysis and magnetic data storage devices.