2.3k citations · 16.8k across the 81 of their papers we have counts for
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Optimized Quantum Drude Oscillators for Atomic and Molecular Response Properties
Szabolcs Góger, Almaz Khabibrakhmanov, Ornella Vaccarelli +2
The quantum Drude oscillator (QDO) is an efficient yet accurate coarse-grained approach that has been widely used to model electronic and optical response properties of atoms and m…
Accurate global machine learning force fields for molecules with hundreds of atoms
Stefan Chmiela, Valentin Vassilev-Galindo, Oliver T. Unke +4
Global machine learning force fields (MLFFs), that have the capacity to capture collective many-atom interactions in molecular systems, currently only scale up to a few dozen atoms…
Towards Linearly Scaling and Chemically Accurate Global Machine Learning Force Fields for Large Molecules
Adil Kabylda, Valentin Vassilev-Galindo, Stefan Chmiela +2
Machine learning force fields (MLFFs) are gradually evolving towards enabling molecular dynamics simulations of molecules and materials with ab initio accuracy but at a small fract…
The three-center two-positron bond
Jorge Charry, Félix Moncada, Matteo Barborini +4
Computational studies have shown that one or more positrons can stabilize two repelling atomic anions through the formation of two-center positronic bonds. In the present work, we…
Accurate Machine Learned Quantum-Mechanical Force Fields for Biomolecular Simulations
Oliver T. Unke, Martin Stöhr, Stefan Ganscha +8
Molecular dynamics (MD) simulations allow atomistic insights into chemical and biological processes. Accurate MD simulations require computationally demanding quantum-mechanical ca…
Second Quantization Approach to Many-Body Dispersion Interactions
Matteo Gori, Philip Kurian, Alexandre Tkatchenko
The many-body dispersion (MBD) framework is a successful approach for modeling the long-range electronic correlation energy and optical response of systems with thousands of atoms.…
Quantum Machine Learning Corrects Classical Force Fields: Stretching DNA Base Pairs in Explicit Solvent
Joshua T. Berryman, Amirhossein Taghavi, Florian Mazur +1
In order to improve the accuracy of molecular dynamics simulations, classical force fields are supplemented with a kernel-based machine learning method trained on quantum-mechanica…