CAREER: CDS&E: Nonlocal and Periodic Density Embedding

纽瓦克罗格斯大学的米歇尔·帕瓦内洛获得了化学理论、模型和计算方法项目的支持，以开发一种新的计算化学方法和软件。现代理论化学的目标是能够在昂贵的实验之前预测材料的性质和分子的反应性。这导致了量子力学的重新表述，称为密度泛函理论或DFT。尽管目前的DFT实现比任何其他量子化学方法的适用性都要广泛得多，但它们在实际大小的模型系统中的应用仍然存在问题。这个项目正面解决了这些问题，并探索了一种称为子系统DFT的DFT替代方案。子系统离散傅里叶变换是离散傅里叶变换的一种形式，它潜在地能够逼近更大的系统规模，而不会明显降低模拟的精度。该项目有三个主要目标：1)开发新的子系统DFT计算机软件；2)将该软件应用于水、光伏电池和催化系统等基础系统；3)培养理论化学和计算机编程领域中代表性不足的学生。其影响是提高理论化学方法的准确性和效率，并在培训未来劳动力的同时使用新方法更好地理解基本的现实世界系统。该项目的中心是将电子密度划分为子系统贡献，从而得出DFT的子系统公式。这导致了一种新的计算框架，该框架基于能够模拟半导体、导体和块体系统的平面波基集合。其他项目活动包括开发动能泛函和交换相关能泛函，目的是使半局部和混合Kohn-Sham DFT以外的子系统DFT具有预测性和定量化。具体地说，科学影响是计算/算法的进步，目标是输出能够以前所未有的效率利用电子结构局部性的大规模并行代码，并适用于广泛类别的模型系统。

Michele Pavanello of Rutgers University, Newark is supported by an award from the Chemical Theory, Models and Computational Methods program to develop a novel computational chemistry methods and software. The goal of modern theoretical chemistry is to be able to predict properties of materials and molecular reactivity ahead of costly experiments. This has led to a reformulation of quantum mechanics called Density Functional Theory or DFT. Although current implementations of DFT find much broader applicability than any other quantum chemistry method, their application to realistically sized model systems is still problematic. This project tackles these problems head-on and explores an alternative to DFT called subsystem DFT. Subsystem DFT is a reformulation of DFT potentially capable of approaching much larger system sizes with no appreciable loss of accuracy of the simulations. There are three main goals of this project: 1) develop new subsystem DFT computer software, 2) apply the software to fundamental systems such as water, photovoltaic cells, and catalysis systems, 3) train students from underrepresented backgrounds in the fields of theoretical chemistry and computer coding. The impacts are to advance the accuracy and efficiency of theoretical chemistry methods and to use the new methods to better understand fundamental real-world systems while training the future workforce. The project centers on partitioning the electron density into subsystem contributions leading to a subsystem formulation of DFT. This results in a new computational framework based on a plane waves basis set capable of modeling semiconductors, conductors and bulk systems. Additional project activities include developing functionals of the kinetic energy and the exchange-correlation energy aimed at making subsystem DFT predictive and quantitative beyond semilocal and hybrid Kohn-Sham DFT. Specifically, the scientific impacts are computational / algorithmic advances with the goal of outputting a massively parallel code capable of exploiting the locality of electronic structures with an unprecedented efficiency and for a wide class of model systems.