CAREER: Coarse-grained Theory and Simulation of Ion-containing Liquids: Study of Ion Solvation by Polymers and Ionic Liquids and between Nanoparticles

职业：含离子液体的粗粒理论和模拟：聚合物和离子液体以及纳米颗粒之间的离子溶剂化研究

• 批准号: 1944211
• 负责人: Issei Nakamura
• 金额: $ 49万
• 依托单位: Michigan Technological University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-07-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944211&HistoricalAwards=false
• 关键词: CAREER; Coarse; grained; Theory; Simulation

NONTECHNICAL SUMMARYThis CAREER project supports research and education to study properties of liquids containing charged molecules. This project is focused on advancing understanding of how charged molecules, also known as ions, are surrounded by liquid molecules. This solvation process is a crucial step in making novel materials for emerging technologies; the lithium-ion polymer battery is one example. Existing computer simulations are unable to access the scales of length and time required for an adequate understanding of ion solvation.In this project, the PI will develop simplified computational models, called coarse-grained models, which represent units containing multiple atoms as effective particles with effective interactions. This procedure reduces the computational intensity of simulations making them tractable, but at the expense of some accuracy. This method will enable more straightforward identification of the key parameters and general mechanisms of ion solvation in polymers, which are long chain-like molecules. The project is aimed to advance the current state-of-the-art of molecular simulations. The knowledge acquired in this study will also help to refine existing theory at the level of atoms and associated simulation methods. Using the developed methods, the PI will also study the role of various nanoparticles in ion solvation. The education component involves framing a pedagogy for both college and high school students, in which students can develop scientific problem-solving skills and cultivate interdisciplinary approaches to problems using computer simulations and visualization. Education objectives will be achieved through utilizing a combination of programming languages and open-source software with an aim to help students visualize mathematical expressions and bridge the gap between practice and theory while enriching their programming skills. The PI also aims to use education innovations developed in this CAREER project to bridge the gap in education between soft- and hard-condensed matter physics. To extend the reach of the project, the PI and his group will collaborate with a K-12 educator to develop and hold short summer programs on topics related to this research. These programs are designed to provide a taste of soft-matter physics to local secondary school students using open-source software, such as PhET and Physlets, and simulation techniques, along with introductory programming. Ultimately, the aim is to develop, evaluate, and disseminate these outreach program resources. TECHNICAL SUMMARYThis CAREER project supports research and education to study the thermodynamic and electrochemical properties of ion-containing liquids. When liquid mixtures, polymers, different time and length scales, and significant spatial inhomogeneity of dielectric responses appear together, electrostatic interactions become amazingly intricate making understanding ion-containing liquids challenging.This study is aimed to provide a deeper understanding of ion solvation at molecular and atomistic scales to enable the design of novel electrochemical materials for next-generation technologies. The PI will focus mainly on the solvation energy of ions and the solvation mechanism in polymers and ionic liquids. The solvation mechanism of nanometer-sized solid bodies, such as metal oxide nanoparticles and quantum dots, will also be investigated with an aim to evaluate the effect of Lifshitz forces. The PI will investigate the hypothesis that the key factors in determining physical properties of ion-containing liquids are: (1) the strong fluctuation of electrostatic potentials, (2) the spatial inhomogeneity of the dielectric response, (3) the synergy among specific interactions such as hydrogen bonding and aromatic interactions, and (4) van der Waals forces from solid bodies. The complexity of polymers, such as chain architecture and chain connectivity, often makes understanding the physical properties that arise from these factors challenging. To address this issue, the PI will develop coarse-grained molecular simulations by connecting dipolar and quadrupolar monomeric units. The PI will also develop effective force fields between uncharged nanoparticles, which account for the molecular interactions of polyelectrolytes and ionic liquids.The proposed education plan seeks to frame a pedagogy for soft-matter sciences in physics. The plan will use open-source software such as PhET, Physlets, and LAMMPS that can be executed on standard computers to ensure wide accessibility. The PI’s main aim is to minimize a gradually surging concern in physics education, specifically, ‘‘the gap in education between hard- and soft-condensed matter physics.’’ To further the impact of the CAREER project, the PI and his group will hold short summer programs based on the PI’s expertise to provide a taste of soft-matter physics to local secondary schools. Developed and delivered in coordination with a K-12 education specialist, these outreach sessions will use open-source software, such as PhET and Physlets, and associated simulation techniques along with introductory programming. The aim of the outreach component is to develop, evaluate, and disseminate resources for use in similar programs nationwide.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术性总结这个职业项目支持研究和教育，研究含有带电分子的液体的性质。这个项目的重点是促进对带电分子(也称为离子)是如何被液体分子包围的理解。这种溶剂化过程是为新兴技术制造新材料的关键一步；锂离子聚合物电池就是一个例子。现有的计算机模拟无法获得充分理解离子溶液所需的长度和时间尺度。在这个项目中，PI将开发简化的计算模型，称为粗粒度模型，将包含多个原子的单元表示为具有有效相互作用的有效粒子。这一过程降低了模拟的计算强度，使其易于处理，但代价是某些精度。这种方法将使人们能够更直接地识别聚合物中离子溶剂化的关键参数和一般机理，这些聚合物是长链状分子。该项目的目的是推进分子模拟的最新技术。在这项研究中获得的知识也将有助于在原子水平上提炼现有的理论和相关的模拟方法。利用开发的方法，PI还将研究各种纳米颗粒在离子溶剂化中的作用。教育部分包括为大学生和高中生制定一种教学方法，其中学生可以发展科学的问题解决技能，并利用计算机模拟和可视化培养跨学科的问题解决方法。将通过使用编程语言和开放源码软件的组合来实现教育目标，目的是帮助学生可视化数学表达式，并在丰富他们的编程技能的同时弥合实践和理论之间的差距。PI还旨在利用这一职业项目中开发的教育创新来弥合软凝聚态物理和硬凝聚态物理之间的教育差距。为了扩大该项目的影响范围，PI和他的团队将与一名K-12教育工作者合作，就与这项研究相关的主题开发和举办简短的暑期项目。这些项目旨在利用开放源码软件，如Phet和Physlets，以及模拟技术，以及介绍性编程，为当地中学生提供软物质物理的体验。最终，目标是开发、评估和传播这些外展计划资源。技术总结这个职业项目支持研究和教育，研究含离子液体的热力学和电化学性质。当液体混合物、聚合物、不同的时间和长度尺度以及介电响应的显著空间不均匀性一起出现时，静电相互作用变得令人惊讶地错综复杂，这给理解含离子液体带来了挑战。本研究旨在提供对分子和原子尺度上的离子溶剂化的更深层次的理解，以便为下一代技术设计新型的电化学材料。PI将主要集中在离子的溶剂化能和聚合物和离子液体中的溶剂化机理。还将研究金属氧化物纳米粒子和量子点等纳米固体的溶剂化机理，以评估Lifshitz力的影响。PI将研究这样一个假设，即决定含离子液体物理性质的关键因素是：(1)静电势的强烈波动，(2)介电响应的空间不均匀，(3)特定相互作用之间的协同，如氢键和芳香族相互作用，以及(4)来自固体的范德华力。聚合物的复杂性，如链结构和链连接性，往往使理解这些因素产生的物理性质具有挑战性。为了解决这个问题，PI将通过连接偶极和四极单体单元来开发粗粒度分子模拟。PI还将在未带电的纳米粒子之间开发有效力场，以解释聚电解质和离子液体的分子相互作用。拟议的教育计划旨在为物理学中的软物质科学构建一种教学方法。该计划将使用开放源码软件，如Phet、Physlets和LAMMPS，这些软件可以在标准计算机上执行，以确保广泛的可及性。PI的主要目标是将物理教育中逐渐加剧的担忧降至最低，具体地说，就是“硬凝聚态物理和软凝聚态物理学之间的教育差距”。为了进一步扩大职业项目的影响，PI和他的团队将根据PI的专业知识举办短期暑期项目，为当地中学提供软物质物理的滋味。这些外联课程是与一名K-12教育专家协调开发和提供的，将使用开放源码软件，如Phet和Physlets，以及相关的模拟技术和介绍性编程。推广部分的目的是开发、评估和传播在全国范围内类似项目中使用的资源。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Inhibition of Lithium Dendrite Growth with Highly Concentrated Ions: Cellular Automaton Simulation and Surrogate Model with Ensemble Neural Networks

• DOI: 10.1039/d1me00150g
• 发表时间: 2022
• 期刊: Molecular Systems Design & Engineering
• 影响因子: 3.6
• 作者: Tong Gao;Ziwei Qian;Hongbo Chen;R. Shahbazian‐Yassar;I. Nakamura

Polarization of ionic liquid and polymer and its implications for polymerized ionic liquids: An overview towards a new theory and simulation

• DOI: 10.1002/pol.20210330
• 发表时间: 2021-08
• 期刊: Journal of Polymer Science
• 影响因子: 3.4
• 作者: Tongtong Gao;Jester N. Itliong;S. Kumar;Zackerie W Hjorth;I. Nakamura

Surrogate molecular dynamics simulation model for dielectric constants with ensemble neural networks

使用集成神经网络介电常数的替代分子动力学模拟模型

• DOI: 10.1557/s43579-022-00283-5
• 发表时间: 2022
• 期刊: MRS Communications
• 影响因子: 1.9
• 作者: Gao, Tong;Shock, Cameron J.;Stevens, Mark J.;Frischknecht, Amalie L.;Nakamura, Issei
• 通讯作者: Nakamura, Issei