Collaborative Research: Ab Initio Engineering of Doped-Covalent-Bond Superconductors

合作研究：掺杂共价键超导体从头开始工程

• 批准号: 2320074
• 负责人: Igor Mazin
• 金额: $ 20万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320074&HistoricalAwards=false
• 关键词: Collaborative; Research; Ab; Initio; Engineering

NONTECHNICAL SUMMARYThis award supports computational research aimed at designing superconducting materials with advanced modeling methods. Superconductors display a unique property of conducting electrical current without any resistance when cooled below a certain critical temperature. Discovery of new materials synthesizable with ambient-pressure techniques and superconducting at high temperatures can impact a wealth of emerging technologies in the areas of energy storage and distribution, medicine, electronics, and transportation.The project will involve a systematic screening of a vast compositional and structural space. The chemical set will include light-weight elements that can form strongly bonded layered frameworks and different metals that can make the covalent frameworks stable and superconducting. In order to study and tune the key properties of candidate materials, the team will add new capabilities to software packages developed in the PIs’ groups. The new features will enable investigation of large-scale phenomena using artificial intelligence approaches and evaluation of the complex materials’ superconducting properties with cutting-edge electronic structure methods.The educational activities will focus on training graduate and undergraduate students in computational materials science and high-performance computing. The team will also participate in outreach activities for K-12 students to help attract a new generation of scientists from underrepresented groups into the Science, Technology, Engineering, and Mathematics disciplines. All new computational features will be made freely available to reach a wider community of physicists, chemists, and materials scientists.TECHNICAL SUMMARYThis award supports a collaborative project on the prediction of high-temperature superconductors that can be synthesized at ambient pressure. The team’s exploratory work has identified layered metal borocarbides as a promising materials class to host new synthesizable compounds with targeted electronic and vibrational properties. In contrast to searches for ground state crystal structures that can be performed with a variety of existing algorithms, identification of temperature- and composition-dependent synthesis routes yielding metastable materials is a far more difficult task. The team will employ a combination of ab initio methods and machine learning interatomic potentials to explore complex kinetics-protected pathways that may lead to the desired metastable configurations. The large size and possible disorder of the resulting structures will make the accurate description of their superconducting properties a considerable challenge. The PIs will introduce new descriptors of the electron-phonon coupling and new capabilities within the anisotropic Migdal-Eliashberg framework to enable a high-throughput evaluation of the candidate materials’ superconducting critical temperatures.The new features in the PIs’ electronic structure software packages (MAISE and EPW) will be disseminated under the open-source GNU General Public License via well-established platforms and presented at workshops to ensure that the scientific community will benefit from these developments in a timely fashion. The PIs will also train (under)graduate students in computational materials physics and high-performance computing as well as introduce K-12 students to present-day materials research through interactive demonstrations organized with the help of the Physics Outreach Program at Binghamton University. Aimed at fostering the young generation’s interest in STEM disciplines, these efforts will contribute to the development of a skilled workforce for advancing cyberinfrastructure and computational materials research.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.

非技术摘要这一奖项支持旨在使用先进建模方法设计超导材料的计算研究。超导体在冷却一定的临界温度以下时显示出无电流的独特属性。在高温下发现可通过环境压力技术合成的新材料和超导会影响在储能和分配，医学，电子设备和运输领域的大量新兴技术。该化学套件将包括可以形成强键的分层框架和不同金属的轻量重量元素，这些元素可以使共价框架稳定且超导。为了研究和调整候选材料的关键特性，团队将为PIS组中开发的软件包添加新功能。新功能将使用人工智能方法进行大规模现象的投资，并通过尖端的电子结构方法评估复杂材料的超导性能。教育活动将集中于计算材料科学和高表现计算的培训毕业生和本科生。该团队还将参加K-12学生的外展活动，以帮助吸引来自代表性不足的群体的新一代科学家进入科学，技术，工程和数学学科。所有新的计算功能都将免费获得，以吸引更广泛的物理学家，化学家和材料科学家社区。技术摘要奖支持可以在环境压力下合成的高温超导体预测的协作项目。该团队的探索性工作已将分层的金属硼砂确定为承诺的材料类，可容纳具有靶向电子和振动特性的新合成化合物。与搜索可以使用多种现有算法进行的基态晶体​​结构相反，鉴定温度和组成依赖性合成途径产生可稳定材料的途径是一项更加困难的任务。该团队将采用AB Initife方法和机器学习间原子间潜力的组合，以探索可能导致所需的可稳态配置的复杂动力学保护的途径。所得结构的大尺寸和可能的混乱将使对其超导性能的准确描述成为考虑。 PI将在各向异性Migdal-EliAshberg框架中介绍电子偶联的新描述和新功能，以对候选材料的超导性临界温度进行高通量评估。 PIS的电子结构软件包（Maise和EPW）中的新功能将通过良好的平台在开源GNU通用公共许可下进行传播，并在研讨会上介绍，以确保科学界将以及时的方式从这些发展中受益。 PIS还将培训（以下）计算材料物理和高性能计算的研究生，并通过在Binghamton University的物理外展计划的帮助下，将K-12学生介绍为现在的材料研究。旨在促进年轻一代对STEM学科的兴趣，这些努力将有助于发展熟练的劳动力，以推进Cyber​​infrasture和计算材料研究。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来通过评估来支持的。