27 citations · 63 across the 11 of their papers we have counts for
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Atomistic Simulations of Oxide-Water Interfaces using Machine Learning Potentials
Jan Elsner, K Nikolas Lausch, Jörg Behler
Oxide-water interfaces govern a wide range of physical and chemical processes fundamental to many fields like catalysis, geochemistry, corrosion, electrochemistry, and sensor techn…
Computation of the heat capacity of water from first principles
Motoyuki Shiga, Jan Elsner, Jörg Behler +1
Water is a unique solvent with many remarkable properties. An example is its exceptionally high heat capacity, which plays an important role in storing and transporting thermal ene…
Insights into the Structure and Dynamics of Water at CoO(001) Using a High-Dimensional Neural Network Potential
Amir Omranpour, Jörg Behler
CoO is an important catalyst for the oxidation of organic molecules in the liquid phase. Still, understanding the atomistic details of CoO-water interfaces under op…
Impact of the damping function in dispersion-corrected density functional theory on the properties of liquid water
K. Nikolas Lausch, Redouan El Haouari, Daniel Trzewik +1
Accounting for dispersion interactions is essential in approximate density functional theory (DFT). Often, a correction potential based on the London formula is added, which is dam…
Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis
Alea Miako Tokita, Timothée Devergne, A. Marco Saitta +1
Machine learning potentials (MLPs) have become a popular tool in chemistry and materials science as they combine the accuracy of electronic structure calculations with the high com…
Nuclear Quantum Effects in Liquid Water Are Negligible for Structure but Significant for Dynamics
Nore Stolte, János Daru, Harald Forbert +2
Isotopic substitution, which can be realized both in experiment and computer simulations, is a direct approach to assess the role of nuclear quantum effects on the structure and dy…