NSF/DMR-BSF: Stochastic Electronic Structure Approaches Applied to Study Low-Dimensional Black-Phosphorene Systems

NSF/DMR-BSF：应用于研究低维黑磷烯系统的随机电子结构方法

• 批准号: 1611382
• 负责人: Daniel Neuhauser
• 金额: $ 51.16万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1611382&HistoricalAwards=false
• 关键词: NSF; DMR; BSF; Stochastic; Electronic

NONTECHNICAL SUMMARYThe National Science Foundation and the United States -- Israel Binational Science Foundation (BSF) jointly support this collaboration between a US-based researcher and an Israel-based researcher. The NSF Divisions of Materials Research and Chemistry fund this award jointly. The award supports computational research and education on the mechanical and electronic properties of black phosphorene. Black phosphorene is a material composed of elemental phosphorous that has been discovered and synthesized only recently. It is very similar to graphene, it forms a two-dimensional sheet, but it offers a significant advantage in that it behaves as a semiconductor: it exhibits a sizeable energy gap while supporting at the same time high-mobility charge carriers. In addition, it turns out that the electronic properties of black phosphorene can be readily tuned by applying mechanical stress and other methods. Therefore, just as silicon emerged as an ideal material for three-dimensional electronics, black phosphorene seems to emerge as the ideal infrastructure material for two-dimensional electronics technology. The principal goal of this project is to study, understand, and eventually predict the properties of black phosphorene and its derivatives using theoretical and computational methods. Because of the way two-dimensional black phosphorene responds to mechanical stresses and to chemical perturbations, studying its properties using conventional computational methods is a highly challenging task, requiring the simulation of exceedingly large systems. Therefore, the first challenge the project will need to overcome is to build a computational tool that tackles large electronic systems containing thousands of atoms, and apply it to the study of black phosphorene. This challenge can be met by using methodologies developed by the PIs that can generally be described as stochastic computational techniques. These approaches are akin to statistical methods used in polling, and make it possible to accurately simulate material properties for much larger systems than is possible with traditional, non-stochastic approaches. Once the tools are developed, the PIs will use them to study realistic two-dimensional black-phosphorene sheets, providing a theoretical framework for fundamental understanding and for guiding future experiments on this material.The theoretical tools developed and used in this project will be made available to the community, with an aim to increase access to the developed methodology. The educational component of the project emphasizes the use of computational tools relevant for the research for the training and education of graduate students and postdoctoral fellows. Undergraduate and high school students will be involved in the research, especially in the running of large-scale simulations. All will benefit from close interactions with the Israeli collaborators.TECHNICAL SUMMARYThe National Science Foundation and the United States -- Israel Binational Science Foundation (BSF) jointly support this collaboration between a US-based researcher and an Israel-based researcher. The NSF Divisions of Materials Research and Chemistry fund this award jointly. The award supports computational research and education on the mechanical and electronic properties of black phosphorene. Traditional large-scale simulations of these properties are prohibitively expensive either for accurate density functional theory with exact exchange (DFT), or for highly accurate electronic structure methods based on Green's function (GW). This project will explore hitherto inaccessible regimes using the stochastic formulations of traditional DFT and GW. The stochastic formulations replace some, or all of the multitude of summations over orbitals inherent in electronics structure methods with a stochastic sampling of combinations of these orbitals. The stochastic approaches are designed to calculate from first principles the atomic and electronic structure of systems containing 10,000 atoms or more. Sizes of that magnitude are necessary for establishing realistic environments, which enable the study of anisotropic properties. Such capability allows the construction of a theoretical framework for fundamental understanding of black phosphorene, which in turn will help in guiding experiments and synthetic efforts by pointing out possible directions to achieve desired properties. The unique ability to accurately simulate large black-phosphorene systems allows the exploration of electronic structure under a variety of experimental conditions, which include temperature, strain, and optical excitation. Using a combination of stochastic DFT and Langevin dynamics, the structure and phonon dispersion curves of large, layered black-phosphorene nanoribbons and nanotubes will be investigated, with and without mechanical stress. The structure of defects and adsorbates on the surface and perimeters will be studied as well.The theoretical tools developed and used in this project will be made available to the community, with an aim to increase access to the developed methodology. The educational component of the project emphasizes the use of computational tools relevant for the research for the training and education of graduate students and postdoctoral fellows. Undergraduate and high school students will be involved in the research, especially in the running of large-scale simulations. All will benefit from close interactions with the Israeli collaborators.

美国国家科学基金会和美国-以色列两国科学基金会（BSF）共同支持美国研究人员和以色列研究人员之间的合作。NSF材料研究和化学部门共同资助了该奖项。该奖项支持有关黑磷烯的机械和电子性质的计算研究和教育。黑磷烯是一种由元素磷组成的材料，最近才被发现和合成。它非常类似于石墨烯，它形成二维薄片，但它提供了一个显着的优势，因为它表现为半导体：它表现出相当大的能隙，同时支持高迁移率的电荷载流子。此外，事实证明，黑色磷烯的电子性质可以很容易地通过施加机械应力和其他方法进行调节。因此，正如硅作为三维电子技术的理想材料出现一样，黑磷烯似乎也成为二维电子技术的理想基础设施材料。该项目的主要目标是研究，理解，并最终预测黑磷烯及其衍生物的性质，使用理论和计算方法。由于二维黑色磷烯对机械应力和化学扰动的反应方式，使用传统的计算方法研究其性质是一项极具挑战性的任务，需要模拟非常大的系统。因此，该项目需要克服的第一个挑战是建立一个计算工具，处理包含数千个原子的大型电子系统，并将其应用于黑磷烯的研究。这一挑战可以通过使用PI开发的方法来应对，这些方法通常可以被描述为随机计算技术。这些方法类似于投票中使用的统计方法，并且可以准确地模拟比传统的非随机方法更大的系统的材料特性。一旦工具开发出来，PI将使用它们来研究真实的二维黑磷烯片，为基本理解和指导未来对这种材料的实验提供理论框架。该项目中开发和使用的理论工具将提供给社区，旨在增加开发方法的可及性。该项目的教育部分强调使用与研究有关的计算工具，以培训和教育研究生和博士后研究员。本科生和高中生将参与研究，特别是在大规模模拟运行。所有人都将从与以色列合作者的密切互动中受益。技术概述美国国家科学基金会和美国-以色列两国科学基金会（BSF）共同支持美国研究人员和以色列研究人员之间的这项合作。NSF材料研究和化学部门共同资助了该奖项。该奖项支持有关黑磷烯的机械和电子性质的计算研究和教育。传统的大规模模拟这些属性是昂贵的，无论是精确的密度泛函理论与精确交换（DFT），或基于绿色函数（GW）的高度精确的电子结构方法。这个项目将探索迄今无法使用传统的DFT和GW的随机配方制度。随机公式取代了一些，或所有的电子结构方法中固有的轨道与这些轨道的组合的随机采样的众多总和。随机方法被设计成从第一原理计算包含10，000个或更多原子的系统的原子和电子结构。这个量级的尺寸对于建立真实的环境是必要的，这使得能够研究各向异性特性。这种能力允许构建一个理论框架，用于对黑磷烯的基本理解，这反过来将有助于通过指出实现所需性质的可能方向来指导实验和合成工作。精确模拟大型黑磷烯系统的独特能力允许在各种实验条件下探索电子结构，包括温度，应变和光激发。使用随机DFT和Langevin动力学的组合，大的，分层的黑色磷烯纳米带和纳米管的结构和声子色散曲线将进行研究，有和没有机械应力。此外，还将研究表面和周边的缺陷和吸附物的结构。该项目中开发和使用的理论工具将提供给社区，目的是增加对开发方法的访问。该项目的教育部分强调使用与研究有关的计算工具，以培训和教育研究生和博士后研究员。本科生和高中生将参与研究，特别是在大规模模拟运行。所有人都将受益于与以色列合作者的密切互动。