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SUMMARY:Physical Chemistry Seminar - Prof. Venkat Kapil
DTSTART:20251106T171500
DTEND:20251106T181500
DTSTAMP:20261005T011635Z
UID:9d50b648fc3c709fe34cf0a8c957b7694d4e0b919cdc7f8e3587e8e6
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Venkat Kapil\, University College London\, UK\nAn apéro
  will be served after the seminar! \n\n\nMachine learning electronic and 
 quantum nuclear effects in condensed phases: Applications to understanding
  the phase diagram of nanoconfined water\n\nUnderstanding the microscopic 
 structure and dynamics of condensed phase systems is essential for fields 
 ranging from drug design to catalysis and battery science. While quantum s
 imulations offer predictive accuracy\, incorporating quantum effects in co
 ndensed phases remains computationally prohibitive. I will present recent 
 progress in developing machine learning (ML) approaches that overcome thes
 e challenges. To capture electronic quantum effects\, we train foundation 
 models that predict first-principles-quality energies and electronic prope
 rties across diverse systems and can be efficiently fine-tuned for specifi
 c problems with small volumes of training data—extending the scope of fi
 nite-temperature simulations to beyond DFT accuracy. To capture quantum nu
 clear effects\, we develop ML frameworks that learn quantum-effective corr
 ections to Born–Oppenheimer potentials\, enabling quantum statistics and
  approximate dynamics at classical cost. As an application\, I will show a
  fully quantum prediction of the phase diagram of nanoconfined water—a m
 odel system relevant to water treatment\, catalysis\, and battery science\
 , which exhibits several poorly understood anomalous properties. Our appro
 ach reveals rich phase behaviour sensitive to the pressure within nanoconf
 ined channels\, including a superionic phase of water with ionic conductiv
 ity rivalling that of battery materials. Our work demonstrates that ML app
 roaches are maturing toward full quantum accuracy in condensed phases acro
 ss many classes of systems.
LOCATION:CH G1 495 https://plan.epfl.ch/?room==CH%20G1%20495
STATUS:CONFIRMED
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