EAGER: SUPER: Non-Hexagonal 2D Boride and Borocarbide Superconductors

Iowa State University, Ames IA

Investigators

Abstract

NON-TECHNICAL SUMMARY With this project, supported by Division of Materials Research, Profs. Kirill Kovnir, Kai Ming Ho, and Vladimir Antropov and their research groups at Iowa State University will be focused on the discovery of novel high-temperature superconductors which will greatly benefit society. High-temperature superconductors which are stable at ambient pressure have the potential to revolutionize modern technology in many energy-related fields: generation, transmittance, transformation, and transportation. Such superconducting materials are currently unavailable. Extensive previous studies on conventional superconductors pointed to promise of the systems based on light elements, such as hydrogen, carbon, and boron. In the current project, computational and experimental efforts are joined to find novel superconductors among layered borides and borocarbides of two or more transition metals. These particular target systems are severely understudied, and hold promise for tuning of the materials properties by means of metal or boron/carbon substitutions. The proposed research integrates computational and experimental studies to provide diverse training for graduate student researchers. The fundamental issues considered in the project are applicable to emergent energy technology. The acquired knowledge and established methodology may be applicable for functional materials development in other areas. TECHNICAL SUMMARY This project, supported by the Division of Materials Research, is focused on the discovery of high-temperature superconductors in non-hexagonal borides and borocarbides of two or more transition metals. A combination of different transition metals allowed for realization of layers based on 5- and 7-membered B rings providing a lever to tune electron-phonon interactions in the boron network. The search for new superconductors starts with the wide computational screening of ternary and multinary metal borides and borocarbides containing at least two different transition metals with non-hexagonal B or B-C layers. A combination of Adaptive Genetic Algorithm and fast advanced machine learning algorithms is used to screen a large number of boride and borocarbides. The promising candidates are evaluated by higher-level theory and the properties relevant for the electron-phonon superconductivity (density of states, phonon frequencies, electron-phonon coupling) are estimated using DFT. Using the DFT result, selected candidates are experimentally synthesized and characterized. The experimental feedback is provided both to structural optimization and superconductivity groups to further estimate potential ways of optimizing electron-phonon interaction by aliovalent substitutions, in both, transition metal sublattice (to tune electronic properties), and boron sublattice (boron/carbon substitutions to tune phonon interactions). 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.