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SUMMARY:Towards modeling molecular crystals with the accuracy of diffusion
  Quantum Monte Carlo - Flaviano Della Pia\, University of Cambridge
DTSTART:20250521T140000Z
DTEND:20250521T143000Z
UID:TALK228607@talks.cam.ac.uk
CONTACT:Lisa Masters
DESCRIPTION:Computational modelling plays a central role in molecular crys
 tal discovery\, fundamental to a wide range of applications\, including ph
 armaceuticals and renewable energy. However\, a reliable description of th
 ese systems requires both a high-accuracy description of the potential ene
 rgy surface and a fully anharmonic quantum description of the nuclear moti
 on. [1\,2] In this talk\, I will first show that reliable lattice energies
  can be obtained with quantum diffusion Monte Carlo. [3\,4] Then\, I will 
 demonstrate the generation of machine learning interatomic potentials capa
 ble of describing molecular crystals at finite temperature and pressure wi
 th sub-chemical accuracy\, using as few as ∼ 200 data structures\, an or
 der of magnitude improvement over the current state-of-the-art. [5] Our\nm
 odels successfully reproduce experiments for a diverse range of molecular 
 crystals and open up the prospects of reliable modeling for drug discovery
  and beyond.\n\n[1] G. J. O. Beran\, Chem. Rev. 2016\, 116\, 9\, 5567–56
 13 (2016)\n[2] V. Kapil and E. A. Engel\,  Proc. Natl. Acad. Sci. U.S.A. 1
 19 (6) e2111769119 (2022)\n[3] F. Della Pia\, A. Zen\, D. Alfè\, A. Micha
 elides\, J. Chem. Phys. 157\, 134701 (2022)\n[4] F. Della Pia\, A. Zen\, D
 . Alfè\, A. Michaelides\, Phys. Rev. Lett. 133\, 046401 (2024)\n[5] F. De
 lla Pia\, B. X. Shi\, V. Kapil\, A. Zen\, D. Alfè\, A. Michaelides\, arXi
 v:2502.15530 (2025)
LOCATION:Unilever Lecture Theatre\, Yusuf Hamied Department of Chemistry
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