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

我们开发高性能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。这些工具对加拿大和其他地区的研究人员非常重要。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。它将允许研究在催化和数据存储设备中具有潜在应用的纳米合金。从我们最近发现的铁笼中寻找线索，我们将寻找新的更大的全金属笼子。PES的最小值是分子的平衡几何形状;鞍点是过渡态;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量区域对于详细的反应机制模型是重要的。我们将继续利用量子化学和密度泛函理论（DFT）的专业知识，结合我们自己的计算机代码，研究PES。学生将接受联合收割机方法开发和应用相结合的研究项目的培训，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。这些项目是在各个层次设计的，以满足本科生，研究生和博士后学生的需求和能力。我们将在三个方面研究纳米合金，这些合金具有有趣的特性，并在催化和信息技术中具有潜在的用途。 (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簇的几何结构。 (2)反应机制。我们使用粒子群优化（PSO）来发现，没有人的监督，在化学反应（“反应机制”）过程中发生在分子中的几何变换的序列。我们将创建一个新的方法，基于化学直觉和优化技术，找到一个先验的（没有任何DFT计算）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，该方法是完全自动化的，不需要用户输入函数形式，并且适用于几乎任何化学成分。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，以提供更大的计算速度。我们还将采取双管齐下的方法来进行全局优化，其中我们使用PES函数来筛选大量的几何结构，并生成一个更小的子集，用于计算DFT能量。在这三个方面的工作，我们将试图揭示的原则，支配的相对稳定性和几何结构，以及磁性，电子和化学性质的双原子团簇。基于这些原理，以及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。

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.