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Topology and the nonreciprocal Hall response in p-type Tellurium.
LQMEC Synergy com Dyon van Dinter (Okinawa Institute of Science and Technology – OIST)
28/02, 4ª feira, 15h. Ed. Principal, Auditório César Lattes ou via Zoom: sala 824 15 11, senha 011616
Incorporating AI (big data algorithms, machine learning, large language models) and future Quantum Simulations in the Material Science (MS) process is leading to a substantial increase in efficiency, accuracy, and potential material candidates. For example, DeepMind (a subsidiary of Google) announced late last year that their designed AI model for materials discovery recently completed the discovery of close to 400.000 thermodynamically stable crystalline materials. As they claim, this is equivalent to “800 years” of progress. However, the experimental field of MS is by no means prepared to keep up with the pace of these developments in material discovery. There is too much work to be done by too few experimentalists. A streamlined and standardized infrastructure and workflow are crucial to maximizing the potential these new technologies offer. With this in mind, I will introduce the capabilities of the Quantum Materials Sciences Unit at the Okinawa Institute of Science and Technology (OIST). As a relatively young research unit, we are trying to design and implement a laboratory environment compatible with the in-silico technologies of this new era of big data and quantum information. Functioning as the current ongoing proof of concept study, I will focus on my work on monolayer FeSe on STO and SVO.
► Mais informações em lqmec.com/lqmec-synergy
