A hierarchy of composite quantum chemical models for applications in materials and surface Chemistry

用于材料和表面化学应用的复合量子化学模型的层次结构

基本信息

  • 批准号:
    1266154
  • 负责人:
  • 金额:
    $ 47.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-07-01 至 2017-06-30
  • 项目状态:
    已结题

项目摘要

Krishnan Raghavachari is supported by an award from the Chemical Theory, Models and Computational Methods program to develop a set of hierarchical quantum chemical methods for state-of-the-art applications in materials and surface chemistry. The hierarchical concept involves the use of highly accurate methodology on small systems to validate more approximate and computationally cost effective methodologies for investigating complex systems. Building on prior work in the PI's research group, Raghavachari and coworkers are developing more sophisticated and broadly applicable methods in three areas: (1) The "connectivity-based-hierarchy", an accurate thermochemical method for medium-sized organic and biomolecules, will be developed for radicals and ions, and calibrated for applications involving amino acids and peptides; (2) New energy and gradient methods including electronic embedding and charge transfer effects will be developed for an accurate QM/QM embedding model based on the successful ONIOM framework; (3) Efficient analytical gradients will be developed for a generalized multilayer "molecules-in-molecules" fragment-based method including electronic embedding . These developments will be used in a range of applications on silicon and silica surfaces as well as for investigating biomolecular systems such as peptides.Accurate treatment of complex systems is one of the main challenges in quantum chemistry. The new methods being developed will fill a critical need to treat medium-sized and large molecules accurately, providing systematic well-tested models for the study of materials and surface systems. The computer codes developed in this program will be available to the scientific community as part of the Gaussian software package as well as in a set of freely available codes on the PI's website. The methods are expected to be widely used by a broad range of investigators. The project involves both method development and applications, and will provide an excellent opportunity for training the next generation of researchers in quantum chemistry
Krishnan Raghavachari获得了化学理论,模型和计算方法计划的奖项,以开发一套分层量子化学方法,用于材料和表面化学的最新应用。分层概念涉及在小型系统上使用高度精确的方法,以验证用于调查复杂系统的更近似和计算成本有效的方法。在PI研究小组先前工作的基础上,Raghavachari及其同事正在三个领域开发更复杂和更广泛适用的方法:(1)“基于连接性的层次结构”,一种用于中等大小有机分子和生物分子的精确热化学方法,将针对自由基和离子开发,并针对涉及氨基酸和肽的应用进行校准;(2)将在成功的ONIOM框架的基础上开发包括电子嵌入和电荷转移效应在内的新能量和梯度方法,以获得准确的QM/QM嵌入模型;(3)将开发有效的分析梯度,用于包括电子嵌入在内的基于片段的广义多层“分子中分子”方法。这些进展将用于硅和二氧化硅表面的一系列应用,以及研究生物分子系统,如肽。复杂系统的精确处理是量子化学的主要挑战之一。正在开发的新方法将满足精确处理中型和大型分子的关键需求,为材料和表面系统的研究提供系统的经过良好测试的模型。该计划开发的计算机代码将作为高斯软件包的一部分提供给科学界,并在PI网站上提供一套免费代码。预计这些方法将被广泛的调查人员广泛使用。该项目涉及方法开发和应用,并将为培训下一代量子化学研究人员提供绝佳机会

项目成果

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Krishnan Raghavachari其他文献

Krishnan Raghavachari的其他文献

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{{ truncateString('Krishnan Raghavachari', 18)}}的其他基金

A Hierarchy of Fragment-based Quantum Chemical Models Incorporating Machine Learning for Applications in Nanoscale Systems
基于片段的量子化学模型的层次结构结合了机器学习在纳米级系统中的应用
  • 批准号:
    2102583
  • 财政年份:
    2021
  • 资助金额:
    $ 47.5万
  • 项目类别:
    Standard Grant
A hierarchy of composite quantum chemical models for applications in materials chemistry and nanoscience
用于材料化学和纳米科学应用的复合量子化学模型的层次结构
  • 批准号:
    1665427
  • 财政年份:
    2017
  • 资助金额:
    $ 47.5万
  • 项目类别:
    Continuing Grant
Quantum chemical investigations of surface chemistry with a hierarchy of cluster models
使用簇模型层次结构对表面化学进行量子化学研究
  • 批准号:
    0911454
  • 财政年份:
    2009
  • 资助金额:
    $ 47.5万
  • 项目类别:
    Continuing Grant
Quantum chemical investigations of surface chemistry with a hierarchy of cluster models
使用簇模型层次结构对表面化学进行量子化学研究
  • 批准号:
    0616737
  • 财政年份:
    2006
  • 资助金额:
    $ 47.5万
  • 项目类别:
    Continuing Grant

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