Collaborative Research: DMREF: Design of Superionic Conductors by Tuning Lattice Dynamics
合作研究:DMREF:通过调整晶格动力学设计超离子导体
基本信息
- 批准号:2119351
- 负责人:
- 金额:$ 45.72万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-10-01 至 2025-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
NON-TECHNICAL SUMMARYSuperionic conductors are solid materials in which a subset of the atoms can flow as though they were in a liquid. These materials could be used in energy technologies such as next-generation rechargeable batteries, fuel-cells, and thermoelectric devices. However, a fundamental understanding of the atomistic mechanisms underlying the outstanding liquid-like behavior of superionic conductors remains elusive. In the spirit of the Materials Genome Initiative (MGI), this project will develop an integrated computational and experimental framework to provide insights into the atomic-scale mechanisms controlling superionic behavior. The project will provide new quantitative understanding of the role of atomic-level disorder and crystal flexibility in the liquid-like behavior of atoms in superionic materials. Advanced computational techniques, validated by state-of-the-art experiments, will further enable predictive modeling, accelerating the current search for new superionic materials. This research project will open new avenues for the design and discovery of efficient materials for novel energy storage and conversion technologies, and in turn, has the potential to help drive the growth of the US economy.TECHNICAL SUMMARYSuperionic conductors are rare materials with part crystalline-part liquid character in which ions can diffuse with high mobilities. This project will rationalize atomistic processes of thermal and mass transport in superionic conductors. This will provide the critical understanding needed to accelerate the discovery and design of superionic materials for improved energy conversion technologies. The research will investigate three design hypotheses. These are that: (1) superionic conductivity is controlled by the thermodynamic state of the mobile sublattice; (2) there is an optimal lattice softness for fast ion conductivity; and (3) superionic conductivity and low thermal conductivity are related by strong anharmonic effects and dynamic sublattice disorder. In the spirit of the Materials Genome Initiative, these hypotheses will be tested by combining state-of-the-art computational modeling and experimental techniques to shed light on how the unusual atomic dynamics of superionic conductors enable fast ionic diffusion and control their thermal transport and thermodynamic properties. A targeted set of superionic compounds will be studied in an investigative loop between theory and experiment, combining neutron and x-ray scattering experiments, thermodynamic and transport measurements, and computer simulations of atomic dynamics using first-principles and machine-learning methods. Additionally, this project will advance the interdisciplinary training of the early-career researchers associated with the project to afford for MGI-based workforce development. Moreover, the project will develop summer workshops, a summer exchange program between the research groups at different universities, and educational online short courses.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.
非技术概述电子导体是固体材料,其中原子的子集可以像在液体中一样流动。这些材料可用于能源技术,如下一代可充电电池,燃料电池和热电设备。然而,对超离子导体突出的类液体行为背后的原子机制的基本理解仍然难以捉摸。本着材料基因组计划(MGI)的精神,该项目将开发一个集成的计算和实验框架,以深入了解控制超离子行为的原子尺度机制。该项目将提供对超离子材料中原子的类液体行为中原子级无序和晶体柔性的作用的新的定量理解。先进的计算技术,经过最先进的实验验证,将进一步实现预测建模,加速目前对新超离子材料的研究。该研究项目将为新型能量存储和转换技术的高效材料的设计和发现开辟新的途径,进而有可能帮助推动美国经济的增长。技术概述离子导体是具有部分结晶-部分液体特性的稀有材料,其中离子可以以高迁移率扩散。这个计画将使超离子导体中的热与质量传输的原子过程合理化。这将提供加速发现和设计用于改进能量转换技术的超离子材料所需的关键理解。本研究将探讨三个设计假设。这就是:(1)超离子电导率由移动的亚晶格的热力学状态控制;(2)对于快离子电导率存在最佳晶格软度;以及(3)超离子电导率和低热导率与强非谐效应和动态亚晶格无序有关。本着材料基因组计划的精神,这些假设将通过结合最先进的计算建模和实验技术进行测试,以揭示超离子导体的不寻常原子动力学如何实现快速离子扩散并控制其热传输和热力学性质。一组有针对性的超离子化合物将在理论和实验之间的研究循环中进行研究,结合中子和X射线散射实验,热力学和传输测量,以及使用第一原理和机器学习方法的原子动力学计算机模拟。 此外,该项目将推进与该项目相关的早期职业研究人员的跨学科培训,以提供基于MGI的劳动力发展。此外,该项目还将开发夏季研讨会、不同大学研究小组之间的夏季交流计划以及教育在线短期课程。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值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
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Boris Kozinsky其他文献
Addressing the Band Gap Problem with a Machine-Learned Exchange Functional
使用机器学习交换函数解决带隙问题
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Kyle Bystrom;Stefano Falletta;Boris Kozinsky - 通讯作者:
Boris Kozinsky
The design space of E(3)-equivariant atom-centred interatomic potentials
E(3) 等变原子中心原子间势的设计空间
- DOI:
10.1038/s42256-024-00956-x - 发表时间:
2025-01-15 - 期刊:
- 影响因子:23.900
- 作者:
Ilyes Batatia;Simon Batzner;Dávid Péter Kovács;Albert Musaelian;Gregor N. C. Simm;Ralf Drautz;Christoph Ortner;Boris Kozinsky;Gábor Csányi - 通讯作者:
Gábor Csányi
Cellule de lithium-soufre et procédé de préparation correspondant
锂电池及制备程序通讯员
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Timm Lohmann;Paul Albertus;John F. Christensen;Boris Kozinsky;A. Kojic - 通讯作者:
A. Kojic
Atomistic simulations of out-of-equilibrium quantum nuclear dynamics
非平衡量子核动力学的原子模拟
- DOI:
10.1038/s41524-025-01588-4 - 发表时间:
2025-04-16 - 期刊:
- 影响因子:11.900
- 作者:
Francesco Libbi;Anders Johansson;Lorenzo Monacelli;Boris Kozinsky - 通讯作者:
Boris Kozinsky
Nanoscale wetting controls reactive Pd ensembles in synthesis of dilute PdAu alloy catalysts
纳米尺度润湿控制稀钯金合金催化剂合成中的活性钯团簇
- DOI:
10.1038/s41467-025-61540-4 - 发表时间:
2025-07-08 - 期刊:
- 影响因子:15.700
- 作者:
Kang Rui Garrick Lim;Cameron J. Owen;Selina K. Kaiser;Prahlad K. Routh;Montserrat Mendoza;Kyoo-Chul K. Park;Taek-Seung Kim;Sadhya Garg;Jules A. Gardener;Lorenzo Russotto;Christopher R. O’Connor;Marianne Bijl;Michael Aizenberg;Christian Reece;Jennifer D. Lee;Anatoly I. Frenkel;Boris Kozinsky;Joanna Aizenberg - 通讯作者:
Joanna Aizenberg
Boris Kozinsky的其他文献
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{{ truncateString('Boris Kozinsky', 18)}}的其他基金
Elements: FLARE infrastructure for reproducible active learning of Bayesian force fields for ex-machina exascale molecular dynamics
元素:FLARE 基础设施,用于可重现的贝叶斯力场主动学习,用于前机械百亿亿次分子动力学
- 批准号:
2003725 - 财政年份:2020
- 资助金额:
$ 45.72万 - 项目类别:
Standard Grant
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