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.

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建模合理设计新的超导体，电流可以在不损失能量的情况下流过的材料。用超导电线取代铜线将对美国的电力基础设施产生巨大的有益影响，但不幸的是，所有在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，富氢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一个变量来创造具有不同寻常特性的新材料。许多超导体已经用这种方法合成出来了。最近对某些含氢和含镧化合物在压力下进行的令人兴奋的实验，带来了室温超导性的诱人希望，显示出超导性的起始温度高达华氏44度。这些类型的实验很难进行，而准确的计算预测可以加速新材料的发现。PI将基于量子力学进行计算，以预测有希望的合成新目标，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。为了实现这一目标，PI将进一步开发相关软件，可用于在没有任何实验信息的情况下计算预测固体的结构。该软件免费提供给材料科学、物理和化学社区，促进了合理材料设计的进步，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领域的就业机会铺平道路。该奖项支持理论和计算研究和教育，这些研究和教育将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和结构的材料的晶体结构，这些材料可以在压力下合成，并通过第一性原理计算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进行了计算探索，并预测了一些具有非常高超导临界温度的相，特别是碱性和稀土多氢化物。这个项目的重点将是三元氢化物，其结构和性质仍然未知。PI还将研究含有膨胀金属化合物的新型氢化物，这种化合物被认为具有迷人的量子行为。理论上，新的、也许完全出乎意料的化学物质和全新类型的材料将被发现，而这些预测将得到高压研究领域领先实验小组的证实。XtalOpt进化算法可用于预测仅给定其化学计量的扩展系统的结构，将进一步开发。关键的发展将增加可以在没有任何实验信息的情况下预测的单元格的大小和复杂性，并加速扩展系统的先验结构预测的进展。高度流行的化学构建器、编辑器和可视化器Avogadro中的晶体学套件将进一步发展。XtalOpt和Avogadro是开源软件，有助于创建网络基础设施，并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训练，从而为他们未来的职业生涯做好准备，在理论，计算和实验之间的协同作用导致创新。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，将使来自代表性不足群体的学生接触到STEM领域的研究和未来的职业机会，并训练他们掌握第一性原理建模技术。该奖项反映了美国国家科学基金会的法定使命，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

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