Theoretical Prediction of Hydrogen Rich High-Temperature Superconductors

非技术总结该奖项支持旨在推进超导体计算设计的理论研究和教育。超导材料在技术上很重要，因为电流可以流过它们而不会造成能量损失，而且因为它们的内部会排出磁场。这些特性使超导体能够用作SmartGrid项目中的电缆、悬浮列车中的电缆，以及磁共振成像(MRI)机器和风力涡轮机中使用的电磁铁。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，低于液氮沸腾的寒冷温度。发现在室温下表现为超导体的材料将彻底改变电力基础设施、医疗保健，并以不可想象的方式影响我们的生活。富含氢的固体是这个项目的重点，因为研究表明，它们在高温下可以表现为超导体。就像钻石可以在地球深处的高压下合成一样，研究人员可以通过改变压力来创造具有特殊性质的新材料。最近已经用这种方法合成了几个超导体，表现出接近室温的超导电性。其中许多都是通过计算预测的，可能是设计成功的故事所提供的材料。PI将进行量子力学计算，以预测有希望合成的新超导目标，并将与试图创造这些材料的领先实验小组合作进行高压研究。这项工作的重点是寻找在比目前最高温度的超导材料更低的压力下，具有与室温一样高的温度的超导体材料。为了推进这一目标，PI将进一步开发软件，在没有任何实验信息的情况下预测固体的结构。机器学习方法将与晶体结构预测软件对接，以加快计算速度。由此产生的计划将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，从而导致新型富氢超导体的合理设计。PI将通过计算预测具有独特化学计量的氢化物的晶体结构，以及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。重点将是通过计算绘制出三元氢化物的相图作为压力的函数。这些系统目前正在进行深入的研究，因为研究表明，与最近深入研究的二元氢化物相比，它们可能在更高的温度或更低的压力下表现为超导体。计算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。机器学习方法将加快晶体结构搜索的进度，并将重点放在可能具有最高超导临界温度的材料上，这些方法将与XtalOpt对接。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，它们的开发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。

NONTECHNICAL SUMMARYThis award supports theoretical research and education aimed to advance computational design of superconductors. Superconducting materials are technologically important because electrical current can flow through them without energy loss, and because their interiors expel magnetic fields. These properties enable superconductors to be employed as cables in SmartGrid projects, in levitating trains, and as electromagnets used in Magnetic Resonance Imaging (MRI) machines and wind-turbines. Unfortunately, all the superconductors that are technologically useful must be cooled to very low temperatures, below the frigid temperature where liquid nitrogen boils. Finding materials that behave as superconductors at room temperature would revolutionize electrical infrastructure, health care, and impact our lives in unimaginable ways. Hydrogen-rich solids are the focus of this project because research suggests that they could behave as superconductors at high temperatures.Just as diamonds can be synthesized at high pressures deep within the Earth, researchers can vary pressure to create new materials with unusual properties. Several superconductors have recently been synthesized in this way, exhibiting superconductivity onset approaching room temperature. Many of these have been computationally predicted and could be materials by design success stories. The PI will carry out quantum mechanical calculations to predict promising new superconducting targets for synthesis and will collaborate with leading experimental groups in high-pressure research that will attempt to create these materials. A focus of the work is finding materials that are superconductors at temperatures as high as room temperature at lower pressures than current highest temperature superconducting materials. To advance this goal the PI will further develop software that can predict the structure of a solid without any experimental information. Machine learning methods will be interfaced with the crystal structure prediction software to accelerate the calculations. The resulting programs will be made freely available to the materials science, physics, and chemistry communities, facilitating the advance of rational materials design as well as 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 the rational design of novel hydrogen-rich superconductors. The PI will computationally predict the crystal structures of hydrides with unique stoichiometries and structures that can be synthesized under pressure and study their electronic structure and properties via first-principles calculations. The focus will be on computationally mapping out the phase diagrams of ternary hydrides as a function of pressure. These systems are currently under intense investigation, since research suggests they may behave as superconductors at higher temperatures or lower pressures than the binary hydrides that have been recently studied intensively. The computational 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. Machine learning methods that will accelerate the progress of the crystal structure searches and focus them on materials that are likely to have the highest superconducting critical temperatures, will be interfaced with XtalOpt. The crystallography suite within the highly popular chemical builder, editor, and visualizer Avogadro, will be further advanced. XtalOpt and Avogadro are open-source software, and their development contributes to the creation of cyberinfrastructure, 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.