CAREER: Electron correlation and optical spectra with a nonlocal energy-optimized (NEO) kernel

非技术总结 该职业奖支持理论和计算研究和教育，旨在改进计算分子和材料性质的理论和计算方法。PI旨在开发一种计算效率高且有用的精确校正，以提出基于密度泛函理论从组成原子开始计算材料性质的计算方法。该方法呼吁在另一个理论公式的量子力学描述的许多相互作用的粒子，这将是非常昂贵的计算评估的近似。这种近似被称为随机相位近似。PI的方法应具有更高的精度和计算成本较低的许多目前现有的方法相比。它还应该能够更准确地计算系统，其中电子的配置导致比系统的最低或基态能量更高的能量。太阳能电池的操作提供了研究将探索的例子。PI将通过计算材料特性以及与其他理论和计算方法以及实验结果的比较来测试她的方法。该奖项支持以研究生、本科生和高中生为重点的教育活动。这项活动的重点与培训高中教师的TUTeach计划有关。该项目的学生是物理专业的学生，他们将作为PI的学习助理，了解PI的研究。这些学生也是高中的外联大使。TUTeach的学生将与PI合作，为高中生提供计算物理讲座。PI还将在当地教务长的本科生研究经验计划中指导学生。PI教育计划的另一个重要组成部分是开发一个新的基于主动学习的计算材料物理课程。技术总结这个职业奖支持理论和计算研究和教育，以开发更准确的基于密度泛函理论的基态能量和激发态材料性质的计算。通过这个项目，PI有两个目标：（1）发展一个计算效率高的无规相位近似的基态关联能校正。如果没有修正，无规相位近似将不够精确，无法成为化学和材料科学的基准。目前存在的一些校正是准确的，但代价是高计算成本。(2)使计算效率高的含时密度泛函理论在精度上与更复杂的量子多体技术竞争。含时密度泛函理论（英语：Time-dependent density functional theory）是将密度泛函理论扩展到含时势的一种方法。含时密度泛函理论已经成为计算激发能的一个非常流行的工具。 它是计算效率高，但其精度是中等相比，量子多体绿色的功能为基础的方法。最常用的绝热局域密度核忽略了激子效应。PI将进一步开发一个非局部能量优化的内核模型，该模型计算效率高，可以捕获这些影响。对于基态和激发态，相同的非局域交换相关核被添加到库仑电子-电子相互作用核中的基态的频率依赖的线性响应函数。非局部能量优化的内核将被应用到分子和材料。核校正将被测试和应用到许多基态性质，如原子化能，内聚能，结构相变，集群和吸附问题。对含时密度泛函理论的核修正将应用于激发能，包括半导体中的激发能，特别关注太阳能电池应用的光伏材料。该奖项支持以研究生、本科生和高中生为重点的教育活动。这项活动的一个重点是与培训高中教师的TUTeach计划有关。该项目的学生是物理专业的学生，他们将作为PI的学习助理，了解PI的研究。这些学生也是高中的外联大使。TUTeach的学生将与PI合作，为高中生提供计算物理讲座。PI还将在当地教务长的本科生研究经验计划中指导学生。PI教育计划的另一个重要组成部分是开发一个新的基于主动学习的计算材料物理课程。

NONTECHNICAL SUMMARY This CAREER award supports theoretical and computational research and education aimed to improve theoretical and computational methods for computing properties of molecules and materials.The PI aims to develop a computationally efficient and usefully accurate correction to present computational methods of calculating the properties of materials starting from constituent atoms based on the density-functional-theory. The approach appeals to an approximation within another theoretical formulation of the quantum mechanical description of many interacting particles that would be computationally very expensive to evaluate. The approximation is known as the random phase approximation. The PI's method should have a higher accuracy and be computationally inexpensive compared to many currently existing methods. It should also enable higher accuracy calculations of systems in which the configuration of electrons leads to a higher energy than the lowest or ground state energy of the system. The operation of a solar cell provides examples which the research will explore. The PI will test her method through calculations of materials properties and comparisons with results from other theoretical and computational methods, and experiments. .This award supports an educational activity focused on graduate, undergraduate and high-school students. A thrust of this activity is linked to the TUTeach program which trains high-school teachers. The students in this program are physics majors, who will work as learning assistants for the PI and learn about the PI's research. These students are also outreach ambassadors in the high schools. TUTeach students will work with the PI to deliver computational physics lectures to high-school students. The PI will also mentor students within the local provost's research-experiences-for-undergraduates program. Another significant component of the PI's education program is to develop a new active-learning-based Computational Materials Physics course.TECHNICAL SUMMARYThis CAREER award supports theoretical and computational research and education to develop more accurate density functional theory-based calculations of ground-state energies and excited state properties of materials. The PI has two goals through this project: (1) To develop a computationally efficient correction to the ground-state correlation energy of the random phase approximation. Without a correction, the random phase approximation would not be accurate enough to become a benchmark in chemistry and materials science. Some of the currently existing corrections are accurate, but the price is a high computational cost.(2) To make the computationally efficient time-dependent density functional theory competitive in accuracy with more complex quantum many-body techniques. Time-dependent density functional theory is an extension of density functional theory to time-dependent potentials. Time-dependent density functional theory has become a very popular tool to compute excitation energies. It is computationally efficient, but its accuracy is moderate compared to quantum many-body Green's function-based methods. The most commonly used adiabatic local density kernel misses excitonic effects. The PI will further develop a nonlocal energy-optimized kernel model that is computationally efficient and can capture these effects. Both for ground and excited states the same nonlocal exchange-correlation kernel is to be added to the Coulomb electron-electron interaction kernel in the frequency-dependent linear response function of the ground state. The nonlocal energy-optimized kernel will be applied to molecules and materials. The kernel correction will be tested and applied to many ground-state properties, such as atomization energies, cohesive energies, structural phase transitions, clusters and adsorption problems. The kernel correction to time-dependent density functional theory will be applied to excitation energies including those in semiconductors with a particular focus on photovoltaic materials for solar cell applications.This award supports an educational activity focused on graduate, undergraduate and high-school students. A thrust of this activity is linked to the TUTeach program which trains high-school teachers. The students in this program are physics majors, who will work as learning assistants for the PI and learn about the PI's research. These students are also outreach ambassadors in the high schools. TUTeach students will work with the PI to deliver computational physics lectures to high-school students. The PI will also mentor students within the local provost's research-experiences-for-undergraduates program. Another significant component of the PI's education program is to develop a new active-learning-based Computational Materials Physics course.