Bootstrap Embedding for Molecules, Materials and Electrocatalysis

用于分子、材料和电催化的自举嵌入

• 批准号: 2154938
• 负责人: Troy Van Voorhis
• 金额: $ 51万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2154938&HistoricalAwards=false
• 关键词: Bootstrap; Embedding; Molecules; Materials; Electrocatalysis

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.

马萨诸塞州技术研究所的Troy Van Voorhis教授得到了化学理论，模型和计算方法（CTMC）计划的奖励，用于研究计算方法，以结合对小分子碎片计算的计算方法，以预测有关复杂材料的预测。主要工具是一种称为Bootstrap嵌入的概念，它使研究人员首次将大型系统（例如数千原子）分为许多重叠的片段（每个包含十个原子），然后将这些计算拼接在一起，以了解整个系统的属性。最终的工具将适用于各种分子和材料，范沃尔人将专门使用这些工具来研究燃料电池催化剂。近几十年来，计算工具彻底改变了化学，该提案的工作将训练下一代精通计算机的化学家的一部分。作为提案的一部分，范沃里希（Van Voorhis）将开展旨在改善妇女和代表性不足的少数民族从事科学职业的活动。在这个项目中，我们将开发新的量子机械片段嵌入工具，这些工具专门设计以准确处理复杂的分子和固体。工作的起点是Bootstrap嵌入（BE），该方法从根本上解决了嵌入重叠片段的问题。在这个项目中，我们将延伸，同时提高其在处理大型基集和分子间相互作用方面的准确性和效率。通过合并周期性的边界条件，我们将在平行努力中实施扩展系统（例如表面和固体）。引导条件也自然会导致一种新形式的边界条件（我们称之为“杂质边界条件”），该条件近似于单个底物在半无限表面反应的情况。作为这些工具的签名应用，我们将研究O2结合的能量和随后的质子耦合电子传递（PCET）步骤，以一组潜在的ORR催化剂。由于ORR的半反应是所有现代燃料电池的速率和潜在决定步骤，因此该领域的进步可能会对未来的燃料电池技术产生重大影响。从直接意义上讲，此处概述的工作将有助于培训该项目的本科，研究生和博士后学者。从更广泛的意义上讲，该项目提出了一系列教育，培训和外展活动，旨在增加妇女和代表性不足的STEM领域的参与。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响来评估的珍贵的支​​持。