Machine Learning New Superconductors

A collaboration of CNAM members including Ichiro Takeuchi (MSE), Efrain Rodriguez (Chemistry) and Johnpierre Paglione (Physics), together with researchers from NIST and Duke University,have been exploring methods of using artificial intelligence techniques to explore new compounds and search for new, practical superconducting materials by developing machine learning schemes to model the critical temperature (T_c) of over 12,000 known superconductors. Led by postdoctoral research Valentin Stanev, this project involved training a classification model based only on chemical compositions to categorize the known superconductors using a random forest model, and developing regression models to predict the values of T_c for compounds from the database of known materials. Including calculated first principles data from the AFLOW Online Repositories, classification and regression models were combined into a single-integrated pipeline to search the entire Inorganic Crystallographic Structure Database and predict more than 30 new candidate superconductors. This work is now published in NPJ Computational Materials.

CNAM Undergrad Named Goldwater Scholar

Four University of Maryland undergraduates have been awarded scholarships by the Barry Goldwater Scholarship and Excellence in Education Foundation, which encourages students to pursue advanced study and careers in the sciences, engineering and mathematics. Congratulations to Paul Neves—a junior physics major working on magnetic materials using neutron scattering and other experimental techniques in collaboration with the NIST Center for Neutron Research —who designed and built a new device to improve neutron scattering measurements by simultaneously measuring the bulk magnetic properties of a material under high pressure and at low temperature. Read more here.

Discovery of First High-Spin Superconductor

A collaboration between CNAM, CMTC and Ames National Lab researchers led by Prof. J. Paglione has reported experimental evidence of exotic high-spin superconductivity that arises from the unusual electronic structure of the topological semimetal YPtBi. While predicted to occur in other non-material systems, higher than spin-1/2 pairing has remained elusive until now. The team’s research, published in the April 6 issue of Science Advances, reveals effects that are profoundly different from anything that has been seen before with superconductivity.

See news story here.

2018 FQM Winter School - Great Success!

The Fundamentals of Quantum Materials Winter School is a unique school in North America dedicated specifically to the synthesis, characterization and electronic modeling of quantum materials. The focus is on techniques for material synthesis, taught by leaders in the field, through a mix of tutorials and practical demonstrations at the University of Maryland. Thanks to all of those that contributed to help make the 2018 School and Workshop a grand success! More information and media can be found at the School's web site