Congratulations to Yash Anand for winning a 2024 Goldwater Scholarship! Yash is an undergraduate student in the Gemstone program in the Honors College and is actively involved in quantum materials research at QMC. Yash joins a successful lineup of QMC undergraduates who have been awarded the Goldwater Scholarship -- congrats! (read more) .
This year's W. J. Carr Lecture Series on Superconductivity and Advanced Materials will be presented by Prof. Jochen Mannhart from the Max Planck Institute of Solid State Research in Stuttgart, Germany. Prof Mannhart's research interests are focused on the properties of interfaces in complex electronic materials, and have included work on the discovery and development of bicrystal Josephson junctions and SQUIDs, the enhancement of critical currents of high-Tc superconductors by grain alignment, which is the basis for the modern high-Tc superconducting cables, the first imaging of individual atoms with subatomic resolution, and the fabrication of the first all-oxide FETs. Mannhart has received numerous awards for his research, including the Gottfried Wilhelm Leibniz-Preis of the German Science Foundation and the Europhysics Prize in 2014. A Technical Seminar will be given on Monday, January 29 at 4pm in Toll 1201 (more info here), followed by a special Department Colloquium on Tuesday, January 30 at 4pm in 1410 Toll (more info here).
QMC member and NIST Researcher Nick Butch has been elected to the APS 2023 Fellowship. This program recognizes members who have made exceptional contributions in physics research, important applications of physics, leadership in or service to physics, or significant contributions to physics education. Each year, no more than one half of one percent of the Society membership is recognized by their peers for election to Fellow of the American Physical Society. Nick was nomiated to the DCMP Unit and is one of 14 elected fellows -- congrats Nick!!
A team of UMD researchers led by Carlos Ocampo (MSE and IREAP) and including Ichiro Takeuchi (MSE) have been awarded a $2 million grant to support the discovery of new materials for high-performance, energy-efficient and sustainable semiconductors for electronic and optical computational devices, using machine learning to predict unexplored “phase change materials” (PCM) that the researchers can combine, synthesize, test and later integrate into electronic and photonic computational devices. More information can be found here.