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: 2320073
• 负责人: Alexey Kolmogorov
• 金额: $ 37.8万
• 依托单位: SUNY at Binghamton
• 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=2320073&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.

非技术总结该奖项支持旨在用先进的建模方法设计超导材料的计算研究。超导体在冷却到某一临界温度以下时，表现出一种独特的性质，即在没有任何电阻的情况下传导电流。可用常压技术和高温超导合成的新材料的发现，将对能源储存和分配、医药、电子和运输等领域的大量新兴技术产生影响。该项目将涉及对广阔的成分和结构空间进行系统筛选。化学组将包括可以形成强键合层状框架的轻质元素，以及可以使共价框架稳定和超导的不同金属。为了研究和调整候选材料的关键属性，该小组将在PI小组开发的软件包中添加新的功能。这些新功能将使人们能够使用人工智能方法研究大规模现象，并使用尖端电子结构方法评估复合材料的超导性能。教育活动将侧重于培养计算材料科学和高性能计算方面的研究生和本科生。该团队还将参与面向K-12学生的外联活动，以帮助吸引来自代表性不足群体的新一代科学家进入科学、技术、工程和数学学科。所有新的计算功能将免费提供给更广泛的物理学家、化学家和材料科学家社区。技术总结该奖项支持一个关于可以在常压下合成的高温超导体预测的合作项目。该团队的探索性工作确定了层状金属碳化物是一种很有前途的材料类别，可以容纳具有目标电子和振动性能的新的可合成化合物。与可以用各种现有算法进行的基态晶体结构搜索相比，识别产生亚稳态材料的温度和成分相关的合成路线是一项困难得多的任务。该团队将使用从头算方法和机器学习原子间势相结合的方法来探索复杂的动力学保护路径，这些路径可能会导致所需的亚稳态配置。由此产生的结构的巨大尺寸和可能的无序将使对其超导性质的准确描述成为一个相当大的挑战。PIS将在各向异性Migdal-Eliashberg框架内引入关于电子-声子耦合的新描述符和新能力，以实现对候选材料的超导临界温度的高通量评估。PIS的电子结构软件包(MAISE和EPW)中的新功能将在开源GNU通用公共许可证下通过成熟的平台传播，并在研讨会上介绍，以确保科学界及时从这些发展中受益。PIS还将培训(本科)计算材料物理和高性能计算的研究生，并通过在宾厄姆顿大学物理推广计划的帮助下组织的互动演示，向K-12学生介绍当今的材料研究。旨在培养年轻一代对STEM学科的兴趣，这些努力将有助于发展一支技能娴熟的劳动力队伍，以推进网络基础设施和计算材料研究。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。