RUI: Disorder and bonding dynamics in superionic solids

非技术总结该奖项支持旨在为发现所有固态电池的新材料做出贡献的计算和理论研究。与所有固态电池相比，传统的锂离子电池存在火灾危险和低能量密度。固态电池将更安全，并推动电动汽车和可再生能源技术的进步，但它们在商业上尚不可行，因为大多数固体电池不像传统电池中使用的液体或聚合物凝胶那样导电离子。电池需要一种称为电解液的隔膜来传导离子，而不是电子。为了预测具有极快离子导电性的材料，需要在固体中离子导电性的基本理解方面取得进展。晶态和非晶态上离子电解液的发现将改变电池技术，这种电解液的制造成本更低，可以提高电池的稳定性。该项目将使用对已知固体电解质中离子导电性的大规模模拟，以促进对材料结构和组成与导电性之间关系的基本知识。为确定这些关系而开发的工具将用于筛选新材料。硕士和本科生将在旧金山州立大学接受这个项目的培训，旧金山州立大学是美国最多元化的机构之一。PI将她的研究纳入计算和物理化学课程以招收学生。学生积极参与前沿研究将丰富他们的教育，并为他们在科学领域的专业生涯做好准备，其中许多人来自代表性不足的群体。该研究团队是Girls-Who-Code的志愿者，这是一个开创性的组织，向高中生介绍计算机科学，激发他们的兴趣并建立信心。技术总结该奖项支持使用大规模从头算分子动力学模拟的计算研究，以促进成键和结构无序对离子导电性影响的基础知识。该项目的目标是预测固体材料中的离子传导性，并使用高通量筛选来发现新的快离子电解质。这项研究测试了一种假设，即锂的键的断裂和形成，即成键动力学，显著影响锂的导电性，特别是通过相关的运动。大多数以前的锂在电解液中的电导率理论都假设锂保持恒定的离子键性质，并且运动是不相关的。确定锂-阴离子键性质为离子或极性共价是本研究的一种新方法。研究小组将比较许多已知快速锂导体之间的相关运动和成键动力学，从而开发出预测更高电导率电解液的通用分析工具。以前大多数预测新固体电解质的尝试都集中在晶体材料上。该研究小组的目标是确定无序对非晶态电解液中锂电导率的影响，使用经验和从头算分子动力学模拟来比较晶态和非晶态电解液。PI将包括这个计算项目的所有方面的硕士和本科生：执行分子动力学，编写脚本分析数据，以及构建比较模拟以获得对传导性的洞察。PI将编程、模拟和电化学融入到她的课程中，以激励和招募学生进入研究和科学职业生涯。研究小组将自愿向当地高中生介绍这项研究和计算科学。

NONTECHNICAL SUMMARYThis award supports computational and theoretical research aimed to contribute to the discovery of new materials for all solid-state batteries. In contrast to all solid-state batteries, conventional lithium-ion batteries suffer from fire hazards and low energy-density. Solid-state batteries will be safer and enable advances in electric vehicle and renewable energy technologies, but they are not yet commercially viable because most solids do not conduct ions as well as the liquids or polymer gels used in conventional batteries. Batteries require a separator that conducts ions, but not electrons, called an electrolyte. Advances in the fundamental understanding of ion conductivity in solids are needed to predict materials with very fast ion conductivity, superionic electrolytes. Battery technology will be transformed by the discovery of crystalline and amorphous superionic electrolytes, which are cheaper to manufacture and can improve battery stability. The project will use large-scale simulations of ion conductivity in known solid electrolytes to advance fundamental knowledge of the relationship between a material's structure and composition and conductivity. The tools developed to identify these relationships will be used to screen for new materials. Master's and undergraduate students will receive training in this project at San Francisco State University, one of the most diverse institutions in the nation. The PI incorporates her research into computational and physical chemistry courses to recruit students. Active participation of students in frontier research will enrich their education and prepare them, many from under-represented groups, for professional careers in the sciences. The research team volunteers with Girls-Who-Code, a pioneering organization that introduces high school students to computer science, kindling their interest and building confidence. TECHNICAL SUMMARYThis award supports computational research using large-scale ab-initio molecular dynamics simulations to advance fundamental knowledge of the effect of bonding and structural disorder on ionic conductivity. The project goal is to predict ionic conductivity in solid materials and use high-throughput screening to discover new superionic electrolytes. This research tests the hypothesis that the breaking and forming of bonds to lithium, bonding dynamics, significantly affects lithium conductivity, especially through correlated motion. Most previous theories of lithium conductivity in electrolytes assume that lithium retains a constant ionic bond character and motion is uncorrelated. Identification of the lithium-anion bond character as ionic or polar-covalent is a novel approach of this research. The research team will compare correlated motion and bonding dynamics among many known fast lithium conductors, leading to the development of generalized analysis tools for predicting higher conductivity electrolytes. Most previous attempts to predict new solid electrolytes have focused on crystalline materials. The research team aims to identify the effect of disorder on lithium conductivity in amorphous electrolytes, using both empirical and ab-initio molecular dynamics simulations to compare crystalline and amorphous electrolytes. The PI will include master's and undergraduate students in all aspects of this computational project: performing the molecular dynamics, writing scripts to analyze data, and constructing comparative simulations to gain insight into conductivity. The PI incorporates coding, simulation, and electrochemistry into her courses, to inspire and recruit students into research and into science careers. The research team will volunteer to introduce local high school students to this research and computational science.