Abstract: In this talk, I will begin by addressing what correlated electron quantum materials are, why they are gaining interest, and their current and future applications, from quantum computing and microelectronics, to smart window coatings. Then I will focus on 3 inter-related topics of key importance in their discovery, study and application: 1) How the roles of the crystal structure and the valence electrons in symmetry-breaking (Jahn-Teller and pseudo Jahn-Teller) phase transitions in correlated electron materials can be disentangled, solving a longstanding issue in their study[1] 2) How layered structures of two different materials can inform the study of electronic phase transitions at the nanoscale for realistic models of thin-film devices[2] and 3) How machine learning can be used as a tool to assist at all steps of discovery of quantum materials, from their identification to their synthesis[3]. I will then briefly discuss new directions since I began my career at IU, particularly looking at correlated electron materials with molecular orbitals (dimers,trimers) as the quantum building blocks, rather than the traditional d-orbitals, and materials with lone pairs.
[1] Alexandru B. Georgescu, Andrew J. Millis, ’Quantifying the role of the Lattice in Metal- Insulator Phase Transitions’, Communications Physics, 5, 135 (2022)↩
[2] Claribel Domınguez Ordonez, Alexandru B. Georgescu, Bernat Mundet, Yajun Zhang, Jennifer Fowlie, Alain Mercy, Sara Catalano, Duncan Alexander, Philippe Ghosez, Antoine Georges, Andrew J. Millis, Marta Gibert, and Jean-Marc Triscone ’Length-scales of interfacial coupling between metal-insulator phases in oxides’, Nature Materials, 19, 1182-1187, August 2020↩
[3] Alexandru B. Georgescu, Peiwen Ren, Aubrey Toland, Nicholas Wagner, Shengtong Zhang, Kyle D. Miller, Daniel W. Apley, Elsa Olivetti, James M. Rondinelli, ’Database, Features, and Machine Learning Model to Identify Thermally Driven Metal–Insulator Transition Compounds’, Chemistry of Materials, 33, 5591, 2021↩
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