CAREER: First-Principles Thermodynamics and Kinetics of Multi-Component Solids

技术总结：该职业奖支持一个综合的计算研究和教育计划，以开发一种严格的形式主义来预测易受有序-无序现象和结构相变影响的多组分晶体固体中的相稳定性和扩散。PI的目的是为预测合金、氧化物和半导体化合物中同时容易发生有序-无序反应和结构转变的相稳定性、扩散和相变动力学的第一性原理提供一个理论和计算框架。这将为对大多数技术上重要的多组分固体的热力学性质进行真正的第一性原理预测铺平道路。组态和非谐振动激发之间耦合的阐明将为发现新的相变记忆存储材料、电化学激活形状记忆材料和热电材料优化具有低导热系数铺平道路。置换扩散第一性原理理论的发展将使我们能够严格描述多组分固体相变过程中的扩散，并有助于更好地理解用于结构和微电子应用的异质结构中的退化机制。这项工作的另一个成果将是以用户友好的软件形式实施计算机模拟能力，用于热力学和动力学性质的第一原理预测，以服务于研究和教育的目标。该项目将把学生现有的计算能力与研究工作中开发的算法和建模能力联系起来，为学生提供前所未有的访问用户友好的原子模拟软件。课程开发是为了实现这一能力的教育效益，在宏观的长度尺度上解决真实的材料问题。PI将开发一门新的本科课程，将固体物理学的基本概念和工具与统计力学结合起来，重点放在真实材料上。本课程将涵盖固态物理的基础知识，并通过让学生使用用户友好的从头算电子结构代码计算和探索电子性质来强化概念。教育部分将扩展到涵盖统计力学的基本概念及其在将薛定谔方程与热力学相结合方面的作用。这允许处理配分函数、热力学平均值和对熵的统计机械解释。为了增强研究经验，学生将把课堂上学到的工具应用到他们在材料科学中设计的问题上。非技术总结：这个职业奖项支持一个综合的计算研究和教育计划，以发展一种严格的形式主义来预测晶体材料的稳定性和动力学。这一PI旨在生成一个理论和计算框架，用于预测合金和其他化合物中的稳定性、扩散和动力学，仅从组成原子的身份开始。这为准确预测大多数具有重要技术意义的多组分固体的热力学性质开辟了道路。这项研究为发现新的记忆存储材料、电化学激活的形状记忆材料和热电材料铺平了道路。这项工作的另一个成果将是热力学和动力学性质的第一原理预测软件，以服务于研究和教育的目标。课程开发是为了实现这一项目的教育效益。这包括开发一门新的本科课程，将固体物理学的基本概念和工具与统计力学相结合，重点放在真实材料上。本课程将涵盖固态物理的基础知识，并通过让学生使用用户友好的电子结构代码计算和探索电子性质来强化概念。教育部分将扩展到涵盖统计力学的基本概念及其在热力学中的作用。为了加强研究体验，学生们将把课堂上学到的工具应用到他们设计的材料科学问题上。

TECHNICAL SUMMARY:This CAREER award supports an integrated computational research and education program to develop a rigorous formalism to predict phase stability and diffusion in multi-component crystalline solids susceptible to both order-disorder phenomena and structural phase transformations. The PI aims to generate a theoretical and computational framework for the first principles prediction of phase stability, diffusion and phase transformation kinetics in alloys, oxides and semi-conducting compounds that are simultaneously susceptible to order-disorder reactions as well as structural transformations. This will open the way to a truly first-principles prediction of the thermodynamic properties of most technologically important multi-component solids. The elucidation of the coupling between configurational and anharmonic vibrational excitations will pave the way for the discovery of new phase-change materials for memory storage, electrochemically activated shape-memory materials and thermoelectrics optimized to have a low thermal conductivity. The development of a first-principles formalism for substitutional diffusion will allow a rigorous characterization of diffusion during phase transformations of multi-component solids and lead to a better understanding of degradation mechanisms in hetero-structures used in structural and micro-electronics applications. An additional outcome of this effort will be implementing the computer modeling capabilities in the form of user-friendly software for the first-principles prediction of thermodynamic and kinetic properties to serve the goals of both research and education. The project will connect existing computational power available to students with algorithms and modeling capabilities developed in the research effort to provide students with unprecedented access to user-friendly atomistic simulation software. Course development is undertaken to fulfill the educational benefit of this capability to solve real materials problems at the macroscopic length-scale. PI will be developing a novel undergraduate course that combines essential concepts and tools from solid-state physics with statistical mechanics with an emphasis on real materials. This course will cover the basics of solid-state physics and reinforce concepts by having students calculate and explore electronic properties with user-friendly ab initio electronic structure codes. The educational component will expand to cover elementary concepts of statistical mechanics and its role in coupling the Schroedinger equation to thermodynamics. This allows treatment of the partition function, thermodynamic averages and a statistical mechanical interpretation of entropy. To enhance the research experience students will apply the tools learned in class to a problem they design in material science.NON-TECHNICAL SUMMARY:This CAREER award supports an integrated computational research and education program to develop a rigorous formalism to predict stability and dynamics of crystalline materials. This PI aims to generate a theoretical and computational framework for the prediction of stability, diffusion and dynamics in alloys and other compounds starting from only the knowledge of the identity of the constitutent atoms. This opens the way to true prediction of the thermodynamic properties of most technologically important multi-component solids. The research paves the way for the discovery of new materials for memory storage, electrochemically activated shape-memory materials and thermoelectrics. An additional outcome of this effort will be software for the first-principles prediction of thermodynamic and kinetic properties to serve the goals of both research and education. Course development is undertaken to fulfill the educational benefit of this project. This includes developing a novel undergraduate course that combines essential concepts and tools from solid-state physics with statistical mechanics with an emphasis on real materials. This course will cover the basics of solid-state physics and reinforce concepts by having students calculate and explore electronic properties with user-friendly electronic structure codes. The educational component will expand to cover elementary concepts of statistical mechanics and its role in thermodynamics. To enhance the research experience students will apply the tools learned in class to a problem they design in material science.