RUI: Disorder and bonding dynamics in superionic solids

RUI：超离子固体中的无序和键合动力学

• 批准号: 1710630
• 负责人: Nicole Adelstein
• 金额: $ 15.44万
• 依托单位: San Francisco State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1710630&HistoricalAwards=false
• 关键词: RUI; Disorder; bonding; dynamics; superionic

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.

该奖项支持旨在为所有固态电池发现新材料做出贡献的计算和理论研究。与所有固态电池相比，传统的锂离子电池具有火灾危险和低能量密度。固态电池将更安全，并使电动汽车和可再生能源技术取得进步，但它们在商业上还不可行，因为大多数固体不能像传统电池中使用的液体或聚合物凝胶那样传导离子。电池需要一种能传导离子而不能传导电子的隔膜，称为电解质。需要在固体中离子电导率的基本理解方面取得进展，以预测具有非常快的离子电导率的材料，即超离子电解质。电池技术将因晶体和非晶超离子电解质的发现而改变，这些电解质的制造成本更低，并且可以提高电池的稳定性。该项目将使用已知固体电解质中离子电导率的大规模模拟，以推进材料结构、成分和电导率之间关系的基础知识。为确定这些关系而开发的工具将用于筛选新材料。硕士和本科生将在美国最多样化的机构之一--旧金山弗朗西斯科州立大学接受该项目的培训。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（许多来自代表性不足的群体）在科学领域的职业生涯做好准备。研究团队在Girls-Who-Code做志愿者，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。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，以推进键合和结构无序对离子电导率影响的基础知识。该项目的目标是预测固体材料中的离子电导率，并使用高通量筛选来发现新的超离子电解质。这项研究测试的假设，即断裂和形成的债券，锂，键合动力学，显着影响锂的导电性，特别是通过相关的运动。大多数以前的电解质中锂导电性的理论假设锂保持恒定的离子键特征，并且运动是不相关的。确定锂-阴离子键是离子键还是极性共价键是本研究的一个新方法。研究小组将比较许多已知的快速锂导体之间的相关运动和键合动力学，从而开发用于预测更高电导率电解质的通用分析工具。 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无定形电解质中锂电导率的影响，使用经验和从头算分子动力学模拟来比较结晶和无定形电解质。PI将包括硕士和本科生在这个计算项目的各个方面：执行分子动力学，编写脚本来分析数据，并构建比较模拟，以深入了解电导率。PI将编码，模拟和电化学纳入她的课程，以激励和招募学生从事研究和科学事业。研究小组将自愿向当地高中生介绍这项研究和计算科学。

项目成果

Alloying Effects on Superionic Conductivity in Lithium Indium Halides for All-Solid-State Batteries

• DOI: 10.1063/1.5011378
• 发表时间: 2018-02
• 作者: N. Adelstein

Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach

• DOI: 10.1038/s41524-021-00681-8
• 发表时间: 2021-12
• 期刊: npj Computational Materials
• 影响因子: 9.7
• 作者: T. Heo;Andrew C. Grieder;Bo Wang;M. Wood;Tim Hsu;S. Akhade;L. Wan;Long-qing Chen;N. Adelstein-N.-Ad