New Density Functional Solution for Nondynamic and Strong Correlation

田纳西中部州立大学(MTSU)的孔静教授获得了化学系化学理论、模型和计算方法项目的支持，为化学过程的计算机模拟开发更准确的理论模型。计算机能力的快速增长使通过模拟预测化学反应变得更加可行。模拟与实验相结合，可以加速科学发现，但这只有在基本的理论模型足够准确的情况下才可能实现。目前流行的电子相互作用模型对化学的许多领域(但不是所有领域)都是准确的。他们无法准确预测的物理效应对于准确描述催化、光学材料、半导体和超导系统是很重要的。这个项目的目标是在根本层面上建立更准确的理论模型。该项目的成功完成扩大了基于量子力学的模拟的范围，并提高了化学和其他物理科学研究的质量和生产率。这项工作是在MTSU一个新的计算科学项目的背景下进行的，该项目是一个跨学科的项目，为招收来自非化学背景的学生从事计算化学研究提供了一个独特的机会。本科生、少数民族学生和第一代大学生所占比例较高。本科生参与以分子活性为基准的计算，或通过编写部分方法的代码。目前正在为本科高年级学生开发一门新的分子建模课程，该项目的成果可用于新课程和其他本科课程的工作。强相关性问题是Kohn-Sham密度泛函理论(KS-DFT)的最后前沿。这是分子和材料体系密度泛函理论失效的主要原因。在这项工作中，正在发展一种基于单行列式KS-DFT的非动态/强相关性的精确处理。通用泛函处理与当前主流泛函处理弱关联分子和扩展系统相同程度的精确度的强相关性。它的设计使得它能够以足够的效率实施于常规化学应用中，并准确处理动态和非动态关联。为了实现这一目标，在满足精确条件的情况下，基于单决定KS方案，正在开发非动态关联的一般框架。这些条件是包括简并性在内的非动态关联的特定条件，并可作为开发新模型泛函的指南。随着用于非动态和强关联的广泛基准数据库的开发，以及用于有效实施的新算法的开发，这一功能显著地扩大了DFT在涉及所有强度的电子关联的化学和材料科学问题中的应用。本项目中产生的软件和相应功能通过开放源码程序和开放源码分发站点提供，以便它可以与其他程序一起使用。源代码的可获得性也方便了其他人开发新的DFT方法。这项研究预计将对MTSU新生的计算科学博士项目产生重大影响，该项目是美国为数不多的几个项目之一。

Professor Jing Kong of Middle Tennessee State University (MTSU) is supported by an award from the Chemical Theory, Models and Computational Methods Program in the Chemistry Division to develop more accurate theoretical models for computer simulations of chemical processes. The rapidly increasing power of computers is making it ever more feasible to predict chemical reactivity through simulations. Simulations, in concert with experiment, can accelerate scientific discovery, but this is only possible if the underlying theoretical model is sufficiently accurate. Current prevailing models for electronic interactions are accurate for many, but not all, areas of chemistry. The physical effects they fail to predict accurately are important for accurate descriptions of catalysis, optical materials, and semiconducting and superconducting systems. The goal of this project is to build more accurate theoretical models at the fundamental level. The successful completion of this project expands the scope of quantum-mechanical based simulations and improves the quality and productivity of research in chemical and other physical sciences. The work is being done in the context of a new Computational Science program at MTSU, which is an interdisciplinary program that provides a unique opportunity to recruit students from non-chemistry backgrounds to pursue research in computational chemistry. MTSU has a student body with high percentages of undergraduate, minority and first-generation college students. Undergraduate students participate in computations that benchmark the activity of molecules or by coding parts of the methods. A new molecular modeling course for upper-level undergraduates is being developed and the results of this project can be used for the new course and other undergraduate course work.The strong correlation problem is the last frontier of Kohn-Sham Density Functional Theory (KS-DFT). It accounts for most of the failures of DFT for molecular and material systems. In this work, an accurate treatment of nondynamic/strong correlation is being developed based on single-determinant KS-DFT. The general-purpose functional treats strong correlation to the same degree of accuracy as current mainstream functionals treat weakly correlated molecular and extended systems. It is designed so that it can be implemented with sufficient efficiency for routine chemical applications with accurate treatment of both dynamic and nondynamic correlations. To achieve this goal, a general framework for nondynamic correlation is being developed based on the single-determinant KS scheme, subject to exact conditions. These conditions are specific for nondynamic correlation with degeneracy included and serve as guidelines for the development of a new model functional. Together with the development of an extensive benchmark database for nondynamic and strong correlation, and a new algorithm for efficient implementation, this functional significantly broadens the application of DFT to chemical and materials science problems involving electron correlation of all strengths. The software and the corresponding features produced in this project are made available through open source programs and open source distribution sites such that it can be used with other programs. The availability of the source code also facilitates others to develop new DFT methods. This research is expected to have a major impact on the nascent Computational Science PhD Program at MTSU, one of a handful in the country.