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

职业:将量子蒙特卡罗与能源和信息技术材料的隐式溶剂模型耦合

基本信息

  • 批准号:
    1542776
  • 负责人:
  • 金额:
    $ 15.72万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-05-01 至 2017-05-31
  • 项目状态:
    已结题

项目摘要

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.

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Implicit self-consistent electrolyte model in plane-wave density-functional theory
  • DOI:
    10.1063/1.5132354
  • 发表时间:
    2019-12-21
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Mathew, Kiran;Kolluru, V. S. Chaitanya;Hennig, Richard G.
  • 通讯作者:
    Hennig, Richard G.
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Richard Hennig其他文献

Benchmarking of Fast and Interpretable UF Machine Learning Potentials
快速且可解释的 UF 机器学习潜力的基准测试
  • DOI:
  • 发表时间:
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pawan Prakash;Richard Hennig
  • 通讯作者:
    Richard Hennig

Richard Hennig的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Richard Hennig', 18)}}的其他基金

DMREF: AI-Accelerated Design of Synthesis Routes for Metastable Materials
DMREF:亚稳态材料合成路线的人工智能加速设计
  • 批准号:
    2118718
  • 财政年份:
    2021
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Continuing Grant
SI2-SSE: Software for Semiconductor and Electrochemical Interfaces (SSEI)
SI2-SSE:半导体和电化学接口 (SSEI) 软件
  • 批准号:
    1740251
  • 财政年份:
    2017
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
Database of Dopants and Defects in 2D Materials
二维材料中的掺杂剂和缺陷数据库
  • 批准号:
    1748464
  • 财政年份:
    2017
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
Collaborative Research: SusChEM: Understanding Hydrogen Interactions with Metastable Surfaces for Tunable Catalysis Systems
合作研究:SusChEM:了解可调谐催化系统的氢与亚稳态表面的相互作用
  • 批准号:
    1665310
  • 财政年份:
    2017
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Continuing Grant
SI2-SSE: Genetic Algorithm Software Package for Prediction of Novel Two-Dimensional Materials and Surface Reconstructions
SI2-SSE:用于预测新型二维材料和表面重建的遗传算法软件包
  • 批准号:
    1440547
  • 财政年份:
    2015
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
FRG: Unit Defect and Microstructural Processes at Metal/Dielectric Interfaces: An Integrated Experimental and Simulation Approach
FRG:金属/电介质界面的单元缺陷和微观结构过程:综合实验和模拟方法
  • 批准号:
    1207293
  • 财政年份:
    2012
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Continuing Grant
CAREER: Coupling Quantum Monte Carlo with implicit solvent models for materials in energy and information technologies
职业:将量子蒙特卡罗与能源和信息技术材料的隐式溶剂模型耦合
  • 批准号:
    1056587
  • 财政年份:
    2011
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Continuing Grant
IGERT: A Graduate Traineeship in Materials for a Sustainable Future
IGERT:可持续未来材料研究生实习
  • 批准号:
    0903653
  • 财政年份:
    2009
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Continuing Grant
Collaborative Research: CMG: Quantum Monte Carlo Calculations of Deep Earth Materials
合作研究:CMG:地球深部材料的量子蒙特卡罗计算
  • 批准号:
    0703226
  • 财政年份:
    2006
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
Collaborative Research: CMG: Quantum Monte Carlo Calculations of Deep Earth Materials
合作研究:CMG:地球深部材料的量子蒙特卡罗计算
  • 批准号:
    0530301
  • 财政年份:
    2005
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant

相似国自然基金

基于外泌体TRPV4-Nox4 coupling途径探讨缺氧微环境调控鼻咽癌转移侵袭和血管新生的机制研究
  • 批准号:
  • 批准年份:
    2021
  • 资助金额:
    10.0 万元
  • 项目类别:
    省市级项目

相似海外基金

Quantum Hall plasmon resonator-based qubit sensing and multi-qubit coupling
基于量子霍尔等离子体谐振器的量子位传感和多量子位耦合
  • 批准号:
    24K06915
  • 财政年份:
    2024
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Iron-Catalyzed Cross Coupling: Quantum Control on Multi-spin Pathways
铁催化交叉偶联:多自旋路径的量子控制
  • 批准号:
    23H01959
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Grant-in-Aid for Scientific Research (B)
Collaborative Research: EAGER: Quantum Manufacturing: Vertical Coupling and Cross-Talk Shielding of Superconducting Quantum Devices
合作研究:EAGER:量子制造:超导量子器件的垂直耦合和串扰屏蔽
  • 批准号:
    2240246
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
Coupling of light to vibration in quantum materials
量子材料中光与振动的耦合
  • 批准号:
    2882106
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Studentship
Collaborative Research: EAGER: Quantum Manufacturing: Vertical Coupling and Cross-Talk Shielding of Superconducting Quantum Devices
合作研究:EAGER:量子制造:超导量子器件的垂直耦合和串扰屏蔽
  • 批准号:
    2240245
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Standard Grant
Construction of an innovative photoreaction fields that possess quantum coherent strong coupling and study of its fundamental principle
具有量子相干强耦合的创新光反应场的构建及其基本原理研究
  • 批准号:
    23H05464
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Grant-in-Aid for Scientific Research (S)
Exploring novel quantum phenomena induced by spin-orbit coupling and quantum interference effects
探索自旋轨道耦合和量子干涉效应引起的新颖量子现象
  • 批准号:
    23KJ0783
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Grant-in-Aid for JSPS Fellows
Exploration of the strong coupling regime between the 3D cavity and super conducting quantum bits for low-mass wave-like dark matter searches
探索 3D 腔和超导量子比特之间的强耦合机制,用于低质量波状暗物质搜索
  • 批准号:
    23K13093
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Detecting the Invisible: Nanoscale Light Coupling to Quantum Materials
探测不可见事物:纳米级光与量子材料的耦合
  • 批准号:
    2883956
  • 财政年份:
    2023
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Studentship
Understanding quantum materials based on 4d-5d transition metal oxides through spin orbital coupling and dimensionality
通过自旋轨道耦合和维度了解基于 4d-5d 过渡金属氧化物的量子材料
  • 批准号:
    EP/W005786/1
  • 财政年份:
    2022
  • 资助金额:
    $ 15.72万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了