Bootstrap Embedding for Molecules, Materials and Electrocatalysis

麻省理工学院的Troy Van Voorhis教授获得了化学系化学理论、模型和计算方法（CTMC）项目的奖励，他研究了结合小分子片段计算来预测复杂材料的计算方法。主要工具是一个被称为Bootstrap嵌入的概念，它允许研究人员第一次将一个大系统（比如有数千个原子）分成许多重叠的片段（比如每个包含10个原子），然后将这些计算结果拼接在一起，以了解整个系统的属性。由此产生的工具将适用于广泛的分子和材料，Van Voorhis将专门使用这些工具来研究燃料电池催化剂。近几十年来，计算工具已经彻底改变了化学，本提案中的工作将培养部分下一代精通计算机的化学家。作为该提案的一部分，Van Voorhis将参与旨在改善妇女和代表性不足的少数民族从事科学事业的活动。在这个项目中，我们将开发新的量子力学片段嵌入工具，专门设计用于精确处理复杂分子和固体。这项工作的出发点是自举嵌入（Bootstrap Embedding， BE），一种从根本上解决重叠片段嵌入问题的方法。在这个项目中，我们将扩展BE，同时提高其在处理大基集和分子间相互作用方面的准确性和效率。与此同时，我们将通过结合周期边界条件，对扩展系统（如曲面和固体）实现BE。自举条件也自然地导致了一种新的边界条件（我们称之为“杂质边界条件”），它近似于单一底物在半无限表面上反应的情况。作为这些工具的典型应用，我们将研究一系列潜在的ORR催化剂中O2结合和随后的质子耦合电子转移（PCET）步骤的能量学。由于ORR半反应是所有现代燃料电池的速率和潜力的决定步骤，因此该领域的进展有可能对未来的燃料电池技术产生重大影响。从直接意义上说，这里概述的工作将有助于培养参与该项目的本科生、研究生和博士后学者。从更广泛的意义上说，该项目提出了一套教育、培训和推广活动，旨在提高妇女和代表性不足的少数民族在STEM领域的参与度。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Professor Troy Van Voorhis of Massachusetts Institute of Technology is supported by an award from the Chemical Theory, Models and Computational Methods (CTMC) program in the Division of Chemistry to study computational methods for combining calculations on small molecular fragments to make predictions about complex materials. The primary tool is a concept known as Bootstrap embedding, which allows researchers for the first time to divide a large system (say with thousands of atoms) into a number of overlapping fragments (each containing, say, ten atoms) and then stitch together those calculations to understand properties of the whole system. The resulting tools will apply to a wide range of molecules and materials and Van Voorhis will specifically use these tools to study fuel cell catalysts. Computational tools have revolutionized chemistry in recent decades and the work in this proposal will train part of the next generation of computer-savvy chemists. As part of the proposal, Van Voorhis will engage in activities aimed at improving women and under-represented minorities pursuing careers in science. In this project, we will develop new quantum mechanical fragment embedding tools that are specifically designed to be able to accurately treat both complex molecules and solids. The starting point for the work is Bootstrap Embedding (BE), a method that fundamentally solves the issue of embedding overlapping fragments. In this project, we will extend BE by while improving its accuracy and efficiency in treating large basis sets and intermolecular interactions. In a parallel effort, we will implement BE for extended systems (e.g. surfaces and solids) by incorporating periodic boundary conditions. The bootstrap conditions also naturally lead to a new form of boundary conditions (which we call “impurity boundary conditions”) that approximate the situation in which a single substrate reacts at a semi-infinite surface. As a signature application of these tools, we will study the energetics of O2 binding and subsequent proton coupled electron transfer (PCET) steps in a set of potential ORR catalysts. As the ORR half-reaction is the rate- and potential- determining step in all modern fuel cells, advances in this area have the potential for significant impacts in future fuel cell technologies. In a direct sense, the work outlined here will contribute to the training of the undergraduate, graduate and postdoctoral scholars involved in the project. In a wider sense, the project proposes a set of education, training and outreach activities aimed at increasing the participation of women and underrepresented minorities in STEM fields.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.