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
• 负责人: Eva Zurek
• 金额: $ 37.5万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1827815&HistoricalAwards=false
• 关键词: Metallization; Hydrogen; Rich; Materials; Predicting

NONTECHNICAL SUMMARYThis award supports theoretical and computational research and education whose ultimate goal is the rational design via computational modeling of new superconductors, materials through which electric currents can flow without losing energy. Replacing copper wires with superconducting power lines would have a tremendously beneficial impact on the electrical power infrastructure of the USA, but unfortunately all of the superconductors that are technologically useful must be cooled to very low temperatures. Research suggests that hydrogen-rich solids could potentially behave as superconductors at high temperatures and are the focus of this project.Just like diamonds can be synthesized at high pressures deep within the Earth, researchers can use pressure as a variable to create new materials with unusual properties. A number of superconductors have been synthesized in this way. Recent exciting experiments in certain hydrogen- and lanthanum-containing compounds under pressure bring tantalizing promise of room-temperature superconductivity, exhibiting superconductivity onset temperatures of as high as 44 degrees Fahrenheit. These types of experiments are very difficult to carry out, and accurate computational predictions can accelerate new materials discovery. The PI will carry out calculations based upon quantum mechanics to predict promising new targets for synthesis, and will collaborate with leading experimental groups in high-pressure research that will attempt to create these materials. To advance this goal the PI will further develop relevant software that can be used to computationally predict the structure of a solid without any experimental information. The software is freely available to the materials science, physics, and chemistry communities, facilitating the advance of rational materials design as well as of current and future discoveries in science and engineering.Graduate and undergraduate students will be trained in computational materials discovery as part of this project. Aiming to broaden their participation, undergraduate students from underrepresented groups will be trained in computational modelling and materials prediction via personnel exchange, paving the way for future career opportunities in STEM fields.TECHNICAL SUMMARYThis award supports theoretical and computational research and education that will lead towards rational design of novel superconductors. The PI will computationally predict the crystal structures of materials with unique stoichiometries and structures that can be synthesized under pressure, and study their electronic structure and properties via first-principles calculations. The phase diagrams under pressure of most binary hydrides have already been explored computationally, and a number of phases with very high superconducting critical temperatures have been predicted, in particular for alkaline and rare-earth polyhydrides. The focus of this project will be on ternary hydrides, whose structures and properties are still unknown. The PI will also study novel hydrides containing expanded metal compounds, which are known to exhibit fascinating quantum behavior. New, perhaps completely unexpected, chemistry and totally new types of materials will be discovered theoretically, and the predictions will be confirmed by leading experimental groups in high-pressure research.The XtalOpt evolutionary algorithm that can be used to predict the structure of an extended system given only its stoichiometry, will be further developed. Key developments will increase the size and complexity of the unit cells that can be predicted without any experimental information, and accelerate the progress of a priori structure prediction for extended systems. The crystallography suite within the highly popular chemical builder, editor, and visualizer Avogadro, will be further advanced. XtalOpt and Avogadro are open-source software, which contributes to the creation of cyberinfrastructure as well as to facilitating current and future discoveries in science and engineering.Graduate and undergraduate students will be trained in rational computational materials design and programming, thereby preparing them for future careers where synergy between theory, computation, and experiment leads to innovation. Collaboration with primarily undergraduate, minority-serving institutions that involves student and faculty exchange will expose students from underrepresented groups to research and future career opportunities in STEM fields and train them in first-principles modelling techniques.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.

非技术总结该奖项支持理论和计算研究和教育，其最终目标是通过计算模型对新型超导体进行合理设计，新型超导体是一种电流可以流经而不损失能量的材料。用超导输电线取代铜线将对美国的电力基础设施产生巨大的有利影响，但不幸的是，所有技术上有用的超导体都必须冷却到非常低的温度。研究表明，富含氢的固体可能在高温下表现为超导体，这是该项目的重点。就像钻石可以在地球深处的高压下合成一样，研究人员可以利用压力作为变量来创造具有特殊性质的新材料。用这种方法已经合成了许多超导体。最近对某些含氢和含镧化合物在加压下进行的激动人心的实验带来了诱人的室温超导前景，展示了高达44华氏度的超导起始温度。这些类型的实验很难进行，准确的计算预测可以加速新材料的发现。PI将进行基于量子力学的计算，以预测有前景的新合成目标，并将与领先的实验小组合作，进行高压研究，试图创造这些材料。为了推进这一目标，PI将进一步开发相关软件，这些软件可以在没有任何实验信息的情况下通过计算预测固体的结构。该软件可免费提供给材料科学、物理和化学社区，促进合理材料设计的发展以及科学和工程领域当前和未来的发现。作为该项目的一部分，研究生和本科生将接受计算材料发现方面的培训。为了扩大他们的参与，来自代表性不足群体的本科生将通过人员交流接受计算建模和材料预测方面的培训，为未来在STEM领域的职业机会铺平道路。技术总结该奖项支持理论和计算研究和教育，从而导致新型超导体的合理设计。PI将通过计算预测具有独特化学计量比的材料的晶体结构和在压力下可以合成的结构，并通过第一性原理计算来研究它们的电子结构和性质。对大多数二元氢化物在压力下的相图已经进行了计算，并预测了一些具有很高超导临界温度的相，特别是对于碱性和稀土多氢化物。该项目的重点将是三元氢化物，其结构和性质尚不清楚。PI还将研究含有扩展金属化合物的新型氢化物，这些化合物具有迷人的量子行为。理论上将发现新的、也许是完全意想不到的化学和全新类型的材料，这些预测将得到高压研究中领先的实验小组的证实。XtalOpt进化算法将进一步发展，该算法只需给定化学计量比即可用于预测扩展系统的结构。关键的发展将增加在没有任何实验信息的情况下可以预测的单胞的大小和复杂性，并加速扩展系统的先验结构预测的进展。非常受欢迎的化学建造器、编辑者和可视化工具Avogadro内的结晶学套件将进一步推进。XtalOpt和Avogadro是开源软件，有助于创建网络基础设施，促进当前和未来的科学和工程发现。研究生和本科生将接受合理的计算材料设计和编程方面的培训，从而为未来的职业生涯做好准备，理论、计算和实验之间的协同导致创新。与主要为本科生和少数族裔服务的机构合作，包括学生和教师交流，将使学生从代表不足的群体获得STEM领域的研究和未来职业机会，并培训他们第一原理建模技术。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

The XtalOpt Evolutionary Algorithm for Crystal Structure Prediction

• DOI: 10.1021/acs.jpcc.0c09531
• 发表时间: 2021-01-28
• 期刊: JOURNAL OF PHYSICAL CHEMISTRY C
• 影响因子: 3.7
• 作者: Falls, Zackary;Avery, Patrick;Zurek, Eva
• 通讯作者: Zurek, Eva

Materials under high pressure: a chemical perspective

• DOI: 10.1007/s00339-022-05576-z
• 发表时间: 2022-05-01
• 期刊: APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING
• 影响因子: 2.7
• 作者: Hilleke, Katerina P.;Bi, Tiange;Zurek, Eva
• 通讯作者: Zurek, Eva

Pressure-induced yttrium oxides with unconventional stoichiometries and novel properties

• DOI: 10.1103/physrevmaterials.5.044802
• 发表时间: 2021-04
• 期刊: Physical Review Materials
• 影响因子: 3.4
• 作者: Qiuping Yang;Jianyan Lin;Fei Li;Jing Zhang;E. Zurek;Guochun Yang

The Computational Design of Two-Dimensional Materials

二维材料的计算设计

• DOI: 10.1021/acs.jchemed.9b00485
• 发表时间: 2019
• 期刊: Journal of Chemical Education
• 影响因子: 3
• 作者: Miller, Daniel P.;Phillips, Adam;Ludowieg, Herbert;Swihart, Sarah;Autschbach, Jochen;Zurek, Eva
• 通讯作者: Zurek, Eva

Electronic Structure and Superconductivity of Compressed Metal Tetrahydrides

• DOI: 10.1002/chem.202102679
• 发表时间: 2021-09-24
• 期刊: CHEMISTRY-A EUROPEAN JOURNAL
• 影响因子: 4.3
• 作者: Bi, Tiange;Zurek, Eva
• 通讯作者: Zurek, Eva