CAREER: Coupling Quantum Monte Carlo with implicit solvent models for materials in energy and information technologies

该职业奖由材料研究部和网络基础设施办公室资助。它支持计算和理论研究和教育，以开发界面的计算方法，特别是在固体和液体之间。PI将开发一种结合量子蒙特卡罗方法和基于液体和固体之间静电相互作用的隐式溶剂描述的技术。本文将通过与实验数据和以往计算研究的对比来检验该方法的准确性。为了确定其适用范围，该方法将解决现有方法存在困难的三个材料问题，这些问题对能源和信息技术很重要，并且可以回答溶剂如何影响材料性质的基本问题。这些问题包括：(1)电解质如何改变燃料电池催化剂上有机分子的氧化速率；(2)有机溶剂如何改变碳纳米结构的分散相互作用；(3)有机电子材料中陷阱态的光激发如何受到周围分子的影响。理解如何将溶剂效应纳入量子蒙特卡罗方法的基本原理，将使溶剂对反应速率、分散相互作用和电子激发的影响的定量研究成为可能。这将最终使更好地控制催化，改进自组装材料的设计，提高有机电子材料的性能。PI旨在提供先进的计算概念和量子化学和密度功能技术的替代方法。在这项工作中开发的方法和获得的知识可以直接转移到其他技术上重要的材料，这些材料由它们的界面控制，如生物分子系统和储氢材料。该项目将建立一个坚实的知识基础，使未来对这些和其他材料系统的基础工作成为可能。这些方法将通过在广泛使用的代码中实现而提供给广泛的社区。该研究项目通过整合材料科学、电化学、有机化学和凝聚态物理等科学学科的计算和实验合作，将为各级学生提供独特的教育体验，并为他们在不断发展的计算材料科学领域的职业生涯做好准备。该计划的主要教育目标是向K-12，本科生和研究生介绍计算材料科学的跨学科领域，并扩大代表性不足的少数民族的参与。PI将通过指导学生从大一到研究生阶段的研究，并将研究整合到本科和研究生阶段的课程中，培养本科生和研究生未来在材料科学领域的工作。为了吸引年轻学生，特别是代表性不足的少数族裔学生，学习STEM学科，PI将为初高中学生建立一个随机数字的扩展外展项目“科学”，并将其分发到锡拉丘兹和纽约市种族多样化的市中心学校，并将其添加到康奈尔大学面向中学女生的“扩展你的视野”项目的研讨会中。为了开发、评估和分发教学模块，PI将与康奈尔材料研究中心和工程学院多样性项目办公室提供的平台合作。该职业奖由材料研究部和网络基础设施办公室资助。它支持计算和理论研究和教育，以开发计算机技术来解决涉及界面的材料问题，特别是固体材料与液体的界面。界面，特别是固体和液体之间的界面，由于其非均质性、液体的统计性质、分子间强弱力的重要性以及两边的高原子密度，对许多计算方法提出了挑战。该项目旨在开发一种新的固/液界面计算方法，建立其准确性并将其应用于选择材料问题。这个计算材料科学程序解决了溶剂对基本物理和化学过程的影响的基本问题。PI将开发一种计算方法，将求解量子力学方程的随机抽样方法与基于液体和固体之间静电相互作用的溶剂模型相结合。本文将通过与实验数据和以往计算研究的对比来检验该方法的准确性。为了确定其适用范围，该方法将用于解决现有方法存在困难的三个材料问题，这些问题对能源和信息技术很重要，并且可以回答溶剂如何影响材料性质的基本问题。这项研究推进了计算机和计算的使用，以预测材料的性质，以推进基本的理解和开发新技术。该研究项目通过整合材料科学、电化学、有机化学和凝聚态物理等科学学科的计算和实验合作，将为各级学生提供独特的教育体验，并为他们在不断发展的计算材料科学领域的职业生涯做好准备。该计划的主要教育目标是向K-12，本科生和研究生介绍计算材料科学的跨学科领域，并扩大代表性不足的少数民族的参与。PI将通过指导学生从大一到研究生阶段的研究，并将研究整合到本科和研究生阶段的课程中，培养本科生和研究生未来在材料科学领域的工作。为了吸引年轻学生，特别是代表性不足的少数族裔学生，学习STEM学科，PI将为初高中学生建立一个随机数字的扩展外展项目“科学”，并将其分发到锡拉丘兹和纽约市种族多样化的市中心学校，并将其添加到康奈尔大学面向中学女生的“扩展你的视野”项目的研讨会中。为了开发、评估和分发教学模块，PI将与康奈尔材料研究中心和工程学院多样性项目办公室提供的平台合作。

Technical SummaryThis CAREER award is funded through the Division Materials Research and the Office of Cyberinfrasructure. It supports computational and theoretical research and education to develop a computational approach for interfaces, particularly between solid and liquid. The PI will develop a technique that combines quantum Monte Carlo methods with an implicit solvent description based on the electrostatic interaction between the liquid and the solid. The accuracy of the method will be tested by comparison with experimental data and previous computational studies. To establish its range of applicability, the method will address three material problems that present difficulties for existing methods, are important for energy and information technologies and can answer fundamental questions of how solvents affect materials properties. The problems are: (1) How does the electrolyte change the rate of oxidation of organic molecules on fuel cell catalysts, (2) how do organic solvents modify the dispersion interaction of carbon nanostructures, and (3) how are optical excitations of trap states in organic electronic materials affected by the surrounding molecules.Understanding the fundamental principles of how to incorporate solvent effects into quantum Monte Carlo methods will enable the quantitative study of solvent effects on reaction rates, dispersion interactions and electronic excitations. This will ultimately enable better control of catalysis, improve the design of materials for self-assembly and enhance the performance of organic electronic materials. The PI aims to provide advanced computational concepts and an alternative approach to quantum chemistry and density functional techniques. The methods developed and the knowledge gained in this work can directly be transferred to other technologically important materials that are controlled by their interfaces, such as biomolecular systems and hydrogen storage materials. The project will build a solid knowledge base that will enable future fundamental work on these and other materials systems. The methods will be made available to the broad community by implementation into widely used codes. This research program, through integration of computation and experimental collaborations across the scientific disciplines of materials science, electrochemistry, organic chemistry and condensed-matter physics, will provide a unique educational experience for students of all levels and prepare them for careers in the growing area of computational materials science. The primary educational objectives of this program are to introduce K-12, undergraduate, and graduate students to the interdisciplinary field of computational materials science and to broaden the participation of underrepresented minorities. The PI will train undergraduate and graduate students for future jobs in materials science, both through mentoring students from freshman to graduate level in research and by integrating the research into undergraduate and graduate level courses. To attract young students, particularly underrepresented minorities, to STEM disciplines the PI will build an extended outreach program Science with random numbers for middle and high-school students and distribute it to racially diverse inner-city schools in Syracuse and New York City and add it into a workshop for Cornell University's Expanding Your Horizon program for middle school girls. For the development, evaluation and distribution of the teaching module, the PI will work with the platforms provided by the Cornell Center for Materials Research and the College of Engineering Diversity Programs Office.Non-Technical SummaryThis CAREER award is funded through the Division Materials Research and the Office of Cyberinfrasructure. It supports computational and theoretical research and education to develop techniques for computers to solve materials problems involving interfaces, specifically interfaces of solid materials with liquids. Interfaces, particularly between solids and liquids, challenge many computational approaches due to their heterogeneity, the statistical nature of the liquid, the importance of both strong and weak forces among molecules and the high atomic density on both sides. The PI aims to develop a novel computational method for solid/liquid interfaces, establish its accuracy and apply it to selective materials problems. This computational materials science program addresses essential fundamental questions on the effects of solvents on fundamental physical and chemical processes. The PI will develop a computational approach that combines random sampling methods for solving the equations of quantum mechanics with a model for the solvent based on the electrostatic interaction between the liquid and the solid. The accuracy of the method will be tested by comparison with experimental data and previous computational studies. To establish its range of applicability, the method will be used to address three material problems that present difficulties for existing methods, are important for energy and information technologies and can answer fundamental questions of how solvents affect materials properties. This research advances the use of computers and computation to predict the properties of materials to advance fundamental understanding and develop new technologies.This research program, through integration of computation and experimental collaborations across the scientific disciplines of materials science, electrochemistry, organic chemistry and condensed-matter physics, will provide a unique educational experience for students of all levels and prepare them for careers in the growing area of computational materials science. The primary educational objectives of this program are to introduce K-12, undergraduate, and graduate students to the interdisciplinary field of computational materials science and to broaden the participation of underrepresented minorities. The PI will train undergraduate and graduate students for future jobs in materials science, both through mentoring students from freshman to graduate level in research and by integrating the research into undergraduate and graduate level courses. To attract young students, particularly underrepresented minorities, to STEM disciplines the PI will build an extended outreach program Science with random numbers for middle and high-school students and distribute it to racially diverse inner-city schools in Syracuse and New York City and add it into a workshop for Cornell University's Expanding Your Horizon program for middle school girls. For the development, evaluation and distribution of the teaching module, the PI will work with the platforms provided by the Cornell Center for Materials Research and the College of Engineering Diversity Programs Office.