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DTSTART:20260101T000000
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DTSTART;TZID=UTC:20260325T101500
DTEND;TZID=UTC:20260325T110000
DTSTAMP:20260421T101509
CREATED:20260213T125711Z
LAST-MODIFIED:20260225T063525Z
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SUMMARY:Seminar by Volker Deringer
DESCRIPTION:Prof. Volker Deringer from the University of Oxford will deliver an invited seminar on Wednesday 25 March 2025 at 10:15-11:00 in hall A304 (Ke2) of the Aalto University School of Chemical Engineering main building\, Kemistintie 1\, Espoo. \nMachine-learned interatomic potentials for materials chemistry \nVolker Deringer \nDepartment of Chemistry\, University of Oxford \nMachine-learned interatomic potentials (MLIPs) are now widely used in atomistic simulations\, giving access to length and time scales that are otherwise inaccessible to first-principles methods. Their reliability in practice\, however\, depends crucially on the quality and coverage of the training data. In this talk\, I will discuss data-efficient approaches to constructing MLIPs\, including ML-accelerated first-principles molecular dynamics for generating reference configurations\, and automated de novo exploration of relevant configurational spaces using the autoplex software. I will also highlight model-distillation strategies (specifically\, a teacher–student approach) using accurate but computationally costly models to train fast\, task-specific MLIPs for downstream applications. I will illustrate these ideas using examples of structurally complex materials: amorphous silicon\, graphene oxide\, and phase-change materials that are used in data storage and neuromorphic computing.
URL:https://ocamm.fi/event/seminar-by-volker-deringer/
LOCATION:Aalto University\, School of Chemical Engineering\, Kemistintie 1\, Kemistintie 1\, Espoo\, 02150\, Finland
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/jpeg:https://ocamm.fi/wp-content/uploads/2023/09/volker-deringer.jpg
ORGANIZER;CN="Miguel Caro":MAILTO:miguel.caro@aalto.fi
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