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The Journal of Physical Chemistry Letters|January 4, 2018
Structure and Stability of Molecular Crystals with Many-Body Dispersion-Inclusive Density Functional Tight BindingMajid Mortazavi, Jan Gerit Brandenburg, Reinhard J Maurer, et al.The Journal of Chemical Physics|June 10, 2018
Binding energies of benzene on coinage metal surfaces: Equal stability on different metalsFriedrich Maaß, Yingda Jiang, Wei Liu, et al.Physical Review Letters|March 25, 2022
Colossal Enhancement of Atomic Force Response in van der Waals Materials Arising from Many-Body Electronic CorrelationsPaul Hauseux, Alberto Ambrosetti, Stéphane P A Bordas, et al.Journal of Chemical Information and Modeling|April 8, 2026
aims-PAX: Parallel Active Exploration Enables Expedited Construction of Machine Learning Force Fields for Molecules and MaterialsTobias Henkes, Shubham Sharma, Alexandre Tkatchenko, et al.The Journal of Physical Chemistry Letters|August 18, 2015
Size Effects in the Interface Level Alignment of Dye-Sensitized TiO2 ClustersNoa Marom, Thomas Körzdörfer, Xinguo Ren, et al.Journal of Chemical Theory and Computation|April 20, 2026
Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy CalculationsMathias Hilfiker, Leonardo Medrano Sandonas, Alexandre Tkatchenko, et al.Physical Review Letters|May 16, 2015
Electronic properties of molecules and surfaces with a self-consistent interatomic van der Waals density functionalNicola Ferri, Robert A DiStasio, Alberto Ambrosetti, et al.Journal of Chemical Theory and Computation|January 9, 2020
Accurate Description of Nuclear Quantum Effects with High-Order Perturbed Path Integrals (HOPPI)Igor Poltavsky, Venkat Kapil, Michele Ceriotti, et al.Physical Review Letters|May 1, 2012
Density-functional theory with screened van der Waals interactions for the modeling of hybrid inorganic-organic systemsVictor G Ruiz, Wei Liu, Egbert Zojer, et al.The Journal of Chemical Physics|July 2, 2018
Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learningTristan Bereau, Robert A DiStasio, Alexandre Tkatchenko, et al.Pageof 22