FEATURED RESEARCH

Machine-learning guided prediction of new stable Li-Sn alloys (Kolmogorov group, NPJ Comput. Mater. 2022)

Quantum mechanical modelling boosting a material's understanding for neuromorphic computing (Lee group, Adv. Quantum Tech. 2022)

Inhomogeneous Kondo-lattice in geometrically frustrated Pr2Ir2O7 (Kolmogorov, Lawler, Aynajian Groups, Nature Comm. 2021)
Research Grants & Awards
- Margine receives NSF award to create an advanced electronic structure modeling infrastructure
- Margine receives NSF award to develop methods for superconductivity modeling
- Margine and Kolmogorov receive NSF EAGER award to design high-Tc superconductors
- Liu, Piper, and Smeu receive NSF award to study Li-ion Batteries
- Lee receives NSF EAGER grant to study quantum criticality with machine learning
- Shim's group receive NSF grant for studying laser plasma interactions
- Shim's group receive AFOSR grant for table-top ultrashort UV and soft x-ray light
- Piper receives NSF-MRI for a 1st in the US HAXPES spectrometer
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Kolmogorov receives NSF award to design tin alloys with machine learning