3 citations · 3 across the 2 of their papers we have counts for
3 papers
physics.chem-ph2025
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…
physics.chem-ph2025
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…
physics.chem-ph2024★ 3 cited
Machine Learning Potentials for Heterogeneous Catalysis
Amir Omranpour, Jan Elsner, K. Nikolas Lausch +1
The sustainable production of many bulk chemicals relies on heterogeneous catalysis. The rational design or improvement of the required catalysts critically depends on insights int…