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Learned free-energy functionals from pair-correlation matching for dynamical density functional theory

Karnik Ram1,2,*, Jacobus Dijkman3,4, René van Roij5, Jan-Willem van de Meent4, Bernd Ensing3, Max Welling4, and Daniel Cremers1,2

  • 1School of Computation, Information and Technology, TU Munich, Munich, Germany
  • 2Munich Center for Machine Learning, Munich, Germany
  • 3Van't Hoff Institute for Molecular Sciences, University of Amsterdam, Amsterdam, the Netherlands
  • 4Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands
  • 5Institute for Theoretical Physics, Utrecht University, Utrecht, the Netherlands

  • *Contact author: karnik.ram@tum.de

Nonequilibrium scaling of drag forces in counterdriven fluid mixtures

Jonas Köglmayr, Florian Sammüller, and Matthias Schmidt

Phys. Rev. E 114 L033401 (2026)

Spherical Metadensity Functional Learning for Inhomogeneous Classical Fluids

Stefanie M. Kampa, Matthias Schmidt, and Florian Sammüller

Journal of Chemical Theory and Computation 22 9371 (2026)

Metadensity Functional Learning for Classical Fluids: Regularizing with Pair Correlations

Stefanie M. Kampa, Florian Sammüller, and Matthias Schmidt

J. Phys. Chem. B 130 6231 (2026)

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Dario Coscia and Gianluigi Rozza

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