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

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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.