Metallization of Hydrogen-Rich Materials: Predicting Novel Superconductors
富氢材料的金属化:预测新型超导体
基本信息
- 批准号:1005413
- 负责人:
- 金额:$ 38万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-09-15 至 2014-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
TECHNICAL SUMMARYThe Division of Materials Research and the Office of Cyberinfrastrcture contribute funds to this award. It supports theoretical research and education which will lead towards the rational design of novel superconductors. It is thought that under sufficient compression hydrogen will become metallic due to the pressure-induced broadening of filled and unfilled bands, and their eventual overlap. Theoretical predictions indicate that this phase may be a high temperature superconductor. Unfortunately, hydrogen does not become metallic at the highest static pressures reached so far. There is now tremendous interest in developing chemically inspired strategies which could significantly decrease the pressure necessary for metallization. Two examples are: combination with tetravalent atoms, as in the group 14 hydrides, or by the addition of an electropositive element.The PI will focus on predicting the structures of ionic and covalent polyhydrides with unusual stoichiometries that are stable, and metallic under pressure. An evolutionary algorithm, interfaced with a first-principles electronic structure program will be employed towards this end. Already, theoretical and experimental research has shown that specific lithium and silicon bearing hydrogen materials become stable when squeezed, and it is likely that they are metals at experimentally achievable pressures. This work will lead to a deeper understanding of the chemistry, electronic structure and potential superconductivity of hydrogen-rich materials under pressure. The PI aims to determine which factors are important in facilitating the metallization of these systems under mild compression, determine the most favorable stoichiometries and structures, their properties, and ways to chemically stabilize these phases at commercially accessible pressures. The PI will develop an evolutionary algorithm, XtalOpt, which will be used to predict the structures of the most stable systems. This algorithm will be made freely available to the materials science, physics and chemistry communities as an extension to the free visualization tool "Avogadro." It will be released under the GNU Public License, and interfaced with several electronic structure packages which are widely used to study solids. The code will make use of already existing cyberinfrastructure, and will be highly modular, and clearly documented so as to facilitate further development.NONTECHNICAL SUMMARYThe Division of Materials Research and the Office of Cyberinfrastrcture contribute funds to this award. It supports theoretical research and education whose ultimate goal is to use concepts, and theoretical and computational techniques to design new superconducting materials. In a superconductor electric current can flow without dissipation. Replacing copper wires with high temperature superconducting power lines could have a tremendous impact on the electrical power infrastructure of the USA. Unfortunately, all of the materials which are known to behave as superconductors do so only at very low temperatures. Theoretical work has predicted that under pressure the simplest element hydrogen will become metallic, and superconducting near room temperature. Unfortunately, the pressures necessary to metalize hydrogen are greater than those at the center of the earth. The PI will develop chemically inspired strategies which could significantly decrease the pressure necessary to achieve metallic hydrogen. State-of-the-art computational techniques will be employed to predict the structures and properties of hydrogen rich systems under pressure. The PI's computations will determine if these materials could potentially be superconductors, and will suggest how these phases may be chemically stabilized at normal pressures. An evolutionary algorithm, XtalOpt, will be developed in order to predict the structures of the most stable systems. This algorithm will be made freely available to the materials science, physics and chemistry communities as an extension to the free visualization tool "Avogadro." It will be released under the GNU Public License, and interfaced with several computer programs which are widely used to study solid state materials.
技术摘要材料研究部和网络基础设施办公室为该奖项提供资金。它支持理论研究和教育,从而引导新型超导体的合理设计。人们认为,在足够的压缩下,由于填充和未填充带的压力引起的加宽以及它们最终的重叠,氢将变成金属。理论预测表明该相可能是高温超导体。不幸的是,在迄今为止达到的最高静压下,氢不会变成金属。现在人们对开发化学启发策略产生了极大的兴趣,这种策略可以显着降低金属化所需的压力。两个例子是:与四价原子结合,如第 14 族氢化物,或通过添加正电性元素。PI 将重点预测具有不寻常化学计量且在压力下稳定的金属性离子和共价多元氢化物的结构。为此,将采用与第一原理电子结构程序接口的进化算法。理论和实验研究已经表明,特定的含锂和硅的氢材料在受到挤压时会变得稳定,并且在实验可达到的压力下它们很可能是金属。这项工作将有助于更深入地了解压力下富氢材料的化学、电子结构和潜在超导性。 PI 旨在确定哪些因素对于促进这些系统在轻度压缩下的金属化至关重要,确定最有利的化学计量和结构、它们的性能以及在商业压力下化学稳定这些相的方法。 PI 将开发一种进化算法 XtalOpt,该算法将用于预测最稳定系统的结构。该算法将作为免费可视化工具“Avogadro”的扩展免费提供给材料科学、物理和化学界。它将根据 GNU 公共许可证发布,并与多个广泛用于固体研究的电子结构包接口。 该代码将利用现有的网络基础设施,并且将是高度模块化的,并有清晰的记录,以促进进一步的开发。非技术摘要材料研究部和网络基础设施办公室为该奖项提供资金。它支持理论研究和教育,其最终目标是使用概念、理论和计算技术来设计新的超导材料。在超导体中,电流可以无耗散地流动。用高温超导电力线取代铜线可能会对美国的电力基础设施产生巨大影响。不幸的是,所有已知的超导体材料只能在非常低的温度下发挥作用。理论工作预测,在压力下,最简单的元素氢将变成金属,并在接近室温时超导。不幸的是,氢金属化所需的压力比地心的压力更大。 PI 将开发受化学启发的策略,该策略可以显着降低获得金属氢所需的压力。将采用最先进的计算技术来预测压力下富氢系统的结构和特性。 PI 的计算将确定这些材料是否有可能成为超导体,并将建议如何在常压下对这些相进行化学稳定。将开发一种进化算法 XtalOpt,以预测最稳定系统的结构。该算法将作为免费可视化工具“Avogadro”的扩展免费提供给材料科学、物理和化学界。它将根据 GNU 公共许可证发布,并与多种广泛用于研究固态材料的计算机程序连接。
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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Eva Zurek其他文献
Chemistry under high pressure
高压下的化学
- DOI:
10.1038/s41570-020-0213-0 - 发表时间:
2020-09-14 - 期刊:
- 影响因子:51.700
- 作者:
Maosheng Miao;Yuanhui Sun;Eva Zurek;Haiqing Lin - 通讯作者:
Haiqing Lin
A super‐hard high entropy boride containing Hf, Mo, Ti, V, and W
含有 Hf、Mo、Ti、V 和 W 的超硬高熵硼化物
- DOI:
10.1111/jace.19795 - 发表时间:
2024 - 期刊:
- 影响因子:3.9
- 作者:
S. Filipović;N. Obradović;G. Hilmas;W. Fahrenholtz;Donald W. Brenner;Jon‐Paul Maria;Douglas E. Wolfe;Eva Zurek;Xiomara Campilongo;Stefano Curtarolo - 通讯作者:
Stefano Curtarolo
Efficient Modelling of Anharmonicity and Quantum Effects in PdCuH$_2$ with Machine Learning Potentials
利用机器学习潜力对 PdCuH$_2$ 中的非谐性和量子效应进行有效建模
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Francesco Belli;Eva Zurek - 通讯作者:
Eva Zurek
Powder X-ray diffraction assisted evolutionary algorithm for crystal structure prediction
粉末 X 射线衍射辅助进化算法用于晶体结构预测
- DOI:
10.1039/d4dd00269e - 发表时间:
2024-11-28 - 期刊:
- 影响因子:5.600
- 作者:
Stefano Racioppi;Alberto Otero-de-la-Roza;Samad Hajinazar;Eva Zurek - 通讯作者:
Eva Zurek
span class="small-caps"XtalOpt/span version 13: Multi-objective evolutionary search for novel functional materials
<span class="smallcaps">XtalOpt</span> 版本13:用于新型功能材料的多目标进化搜索
- DOI:
10.1016/j.cpc.2024.109306 - 发表时间:
2024-11-01 - 期刊:
- 影响因子:3.400
- 作者:
Samad Hajinazar;Eva Zurek - 通讯作者:
Eva Zurek
Eva Zurek的其他文献
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{{ truncateString('Eva Zurek', 18)}}的其他基金
Theoretical Prediction of Hydrogen Rich High-Temperature Superconductors
富氢高温超导体的理论预测
- 批准号:
2136038 - 财政年份:2022
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
EAGER: SUPER: Collaborative Research: Stabilization of Warm and Light Superconductors at Low Pressures by Chemical Doping
EAGER:SUPER:合作研究:通过化学掺杂在低压下稳定温光超导体
- 批准号:
2132491 - 财政年份:2021
- 资助金额:
$ 38万 - 项目类别:
Continuing Grant
Collaborative Research: DMREF: Machine Learning Algorithm Prediction and Synthesis of Next Generation Superhard Functional Materials
合作研究:DMREF:下一代超硬功能材料的机器学习算法预测与合成
- 批准号:
2119065 - 财政年份:2021
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
Metallization of Hydrogen-Rich Materials: Predicting Novel Superconductors
富氢材料的金属化:预测新型超导体
- 批准号:
1827815 - 财政年份:2019
- 资助金额:
$ 38万 - 项目类别:
Continuing Grant
Tuning Reactivity, Electronic Structure and Properties via Pressure: Predicting Novel Superconductors
通过压力调节反应性、电子结构和特性:预测新型超导体
- 批准号:
1505817 - 财政年份:2015
- 资助金额:
$ 38万 - 项目类别:
Continuing Grant
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