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

Krishnan Raghavachari获得了化学理论、模型和计算方法项目的奖励，为材料和表面化学领域的最新应用开发了一套分层量子化学方法。层次概念涉及在小系统上使用高度精确的方法，以验证用于研究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广泛适用的方法：(1)“基于连接的层次”，一种用于中型有机分子和生物分子的精确热化学方法，将用于自由基和离子，并针对涉及氨基酸和肽的应用进行校准；(2)在成功的ONIOM框架基础上，将开发新的能量和梯度方法，包括电子嵌入和电荷转移效应，以建立精确的QM/QM嵌入模型；(3)将为包括电子包埋在内的广义多层“分子中分子”片段方法开发高效的分析梯度。这些发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。在这个项目中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，也可以在PI的网站上免费获得一组代码。这些方法有望被广泛的研究人员广泛使用。该项目涉及方法开发和应用，并将为培养下一代量子化学研究人员提供一个极好的机会

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