6 papers
Capturing Nuclear Quantum Effects in Hydrogen Diffusion through MoS2 via Machine-Learning-Enhanced Path-Integral Simulations
Ismail Eren, Ege Yigit Erbil, Maria-Judith Caisachana-Lozada +4
Hydrogen transport through layered two-dimensional (2D) materials is central to technologies such as hydrogen storage, fuel cells, and isotope separation. Among these materials, Mo…
The UZH protocol: Separating errors and constructing improved CP2K basis sets and pseudopotentials
Hossein Mirhosseini, Tiziano M. A. Müller, Matthias Krack +2
Reliable density-functional simulations require numerical settings whose residual errors are smaller than the chemical and materials trends being interpreted. In CP2K/Quickstep, th…
Benchmarking Universal Machine Learning Interatomic Potentials on Elemental Systems
Hossein Tahmasbi, Andreas Knüpfer, Thomas D. Kühne +1
The rapid emergence of universal Machine Learning Interatomic Potentials (uMLIPs) has transformed materials modeling. However, a comprehensive understanding of their generalization…
In silico investigation of Ba-based ternary chalcogenides for photovoltaic applications
Ramya Kormath Madam Raghupathy, Hossein Mirhosseini, Thomas D. Kühne
In solar cells, the absorbers are the key components for capturing solar energy and converting photons into electron-hole pairs. The search for high-performance absorbers with adva…
The CP2K Program Package Made Simple
Marcella Iannuzzi, Jan Wilhelm, Frederick Stein +24
CP2K is a versatile open-source software package for simulations across a wide range of atomistic systems, from isolated molecules in the gas phase to low-dimensional functional ma…
Revisiting the Abundance of Topological Materials
Hossein Mirhosseini, Luis Elcoro, Andreas Knüpfer +1
The classification of topological materials is revisited using advanced computational workflows that integrate hybrid density functional theory calculations with exact Hartree-Fock…