Alexandre Tkatchenko

University of Luxembourg — LU

Materials Science · Physical Sciences

82h-index39.3kcitations509works7.12yr avg
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Research Topics

Machine Learning in Materials Science(151), Advanced Chemical Physics Studies(114), Computational Drug Discovery Methods(69), Quantum, superfluid, helium dynamics(63), Spectroscopy and Quantum Chemical Studies(59)

Publications502 total

Machine-Learned Electrostatic Potentials for Accurate Hydration Free Energy Calculations
arXiv (Cornell University)·2025Open Access
Accurate Density Functional Theory for Non-Covalent Interactions in Charged Systems
2025
AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions
arXiv (Cornell University)·2025Open Access
Multipartite Gaussian entanglement measure with applications to graph states and bosonic field theory
Journal of Physics A Mathematical and Theoretical·2025
Many-Body Description of van der Waals Torque in Two-Dimensional Materials
ACS Nano·2025
Repulsive Inverse-Distance Interatomic Interaction from Many-Body Quantum Electrodynamics
arXiv (Cornell University)·2025Open Access
Accurate Density Functional Theory for Non-Covalent Interactions in Charged Systems
2025
aims-PAX: Parallel Active eXploration Enables Expedited Construction of Machine Learning Force Fields for Molecules and Materials
2025· 1 citedOpen Access
Noncovalent Interactions in Density Functional Theory: All the Charge Density We Do Not See
Journal of the American Chemical Society·2025· 1 citedOpen Access
Accurate noncovalent interactions in atomistic systems via quantum Drude oscillators
The Journal of Chemical Physics·2025Open Access
Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions
Nature Communications·2025· 4 citedOpen Access
Assessing the performance of quantum-mechanical descriptors in physicochemical and biological property prediction
2025Open Access
Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer
The Journal of Chemical Physics·2025· 4 citedOpen Access
Author response for "Unraveling chemical bonding mechanisms through dipole moment variations under external electric fields"
2025
Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields
Journal of the American Chemical Society·2025· 28 citedOpen Access
aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
2025Open Access
aims-PAX: Parallel Active eXploration for the automated construction of Machine Learning Force Fields
arXiv (Cornell University)·2025Open Access
A Computational Community Blind Challenge on Pan-Coronavirus Drug Discovery Data
2025· 2 citedOpen Access
Power of the Many‐Body Force: Magnitudes and Angles of Atomic Van der Waals Dispersion Forces in Extended Molecular Systems
Small Structures·2025· 2 citedOpen Access
Atomic orbits in molecules and materials for improving machine learning force fields
Machine Learning Science and Technology·2025· 1 citedOpen Access
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Frequent Co-authors

Matthias Scheffler(17), Klaus‐Robert Müller(9), Robert A. DiStasio(9), Kristof T. Schütt(8), O. Anatole von Lilienfeld(6), Stefan Chmiela(6), Anthony M. Reilly(6), Wei Liu(6), Huziel E. Sauceda(5), K. Müller(4), Michael Gastegger(4), Noa Marom(4), Vivekanand V. Gobre(4), Biswajit Santra(4), Angelos Michaelides(4), Matthias Rupp(3), Claudia Draxl(3), Guoxu Zhang(3), Roberto Car(3), Igor Poltavsky(3)