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.

非技术总结职业项目支持研究和教育，以研究含有带电分子的液体的特性。该项目的重点是推进对带电分子（也称为离子）如何通过液体分子围绕的理解。该解决方案过程是为新兴技术制造新型材料的关键步骤。锂离子聚合物电池就是一个例子。现有的计算机模拟无法访问对离子解决方案足够理解的长度和时间的尺度。在本项目中，PI将开发简化的计算模型，称为粗粒模型，该模型代表单位包含多个原子作为有效相互作用的有效粒子。该过程降低了模拟的计算强度，使其可进行处理，但以某种精度为代价。该方法将使聚合物中的关键参数和一般机制更直接地识别，这些参数是长长的链样分子。该项目旨在推进分子模拟的当前最新技术。这项研究中获得的知识还将有助于在原子和相关的仿真方法的水平上完善现有理论。使用开发的方法，PI还将研究各种纳米颗粒在离子求解中的作用。教育部分涉及为大学和高中生构建教学法，其中学生可以使用计算机模拟和可视化来发展科学的解决问题的技能，并培养跨学科方法来解决问题。通过利用编程语言和开源软件的组合，将实现教育对象，以帮助学生可视化数学表达式并弥合实践和理论之间的差距，同时丰富他们的编程技能。 PI还旨在利用该职业项目中开发的教育创新，以弥合软体和硬化物理物理学之间的教育差距。为了扩展项目的影响力，PI及其小组将与K-12教育家合作，开发和举办与这项研究相关的主题的简短计划。这些程序旨在使用开源软件（例如PHET和Physlets以及仿真技术）以及介绍编程为当地的中学学生提供软性物理的味道。最终，目的是开发，评估和传播这些外展计划资源。技术摘要这项职业项目支持研究和教育，以研究含离子液体的热力学和电化学特性。当液体混合物，聚合物，不同的时间和长度尺度以及饮食反应的显着空间不均匀性出现在一起时，静电相互作用变得令人惊讶地使人们非常复杂，从而使理解含离子的液体挑战。这项研究旨在更深入地了解分子和原子量表的离子解决方案，以启用新型的电化材料，以启用新型的电化学技术。 PI将主要集中在离子和离子液体中的离子和溶液机理上。还将研究纳米尺寸固体的溶液机理，例如金属氧化物纳米颗粒和量子点，以评估Lifshitz力的影响。 PI将研究以下假设：确定含离子液体的物理特性的关键因素是：（1）静电电位的强烈波动，（2）自由基反应的空间不均匀性，（3）在特定相互作用（3）诸如氢键和芳族粘合和芳族相互作用以及（4）van der waals of silities bods of silities selitials of silities selitials of silities selities selities of silborties的特定相互作用的协同作用。聚合物的复杂性，例如链结构和链连接性，通常会使这些因素挑战所产生的物理特性。为了解决这个问题，PI将通过连接偶极和四极单体单元来形成粗粒的分子模拟。 PI还将在未充电的纳米颗粒之间发展有效的力场，该纳米粒子解释了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构建物理学软性科学的教学法。该计划将使用可以在标准计算机上执行的开源软件，例如PHET，Physlet和LAMMPS，以确保广泛的可访问性。 PI的主要目的是最大程度地减少物理教育中的逐渐令人担忧的关注点，特别是“硬化物理和软性物理学之间的教育差距。”为了进一步进一步的职业项目的影响，PI和他的小组将基于PI的夏季计划，以PI的专业知识为当地的中学提供软性物理学的品味。这些外展课程与K-12教育专家进行了协调和协调，将使用开源软件，例如PHET和Physlets，以及相关的仿真技术以及介绍编程。外展部分的目的是开发，评估和传播在全国类似计划中使用的资源。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的审查标准，通过评估诚实地认为通过评估。

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