3 papers
cond-mat.mtrl-sci2025
Efficient training of machine learning potentials for metallic glasses: CuZrAl validation
Antoni Wadowski, Anshul D. S. Parmar, Filip Kaśkosz +4
Interatomic potentials are key to uncovering microscopic structure-property relationships, essential for multiscale simulations and high-throughput experiments. For metallic glasse…
cond-mat.soft2024
The breakdown of the direct relation between the density scaling exponent and the intermolecular interaction potential for molecular systems with purely repulsive intermolecular forces
Filip Kaśkosz, Kajetan Koperwas, Andrzej Grzybowski +1
In this work, we question the generally accepted statement that the character of intermolecular interactions can be directly determined from the scaling exponent. Based on detailed…
cond-mat.dis-nn2023
Transmutation-accelerated sampling method for multi-component ZrCu(Al) metallic glasses
Filip Kaskosz, Rene Alvarez-Donado, Mikko Alava +2
We investigate multi-component metallic glass systems using a hybrid Molecular Dynamics (MD) and Variance-Constrained Semi-Grand Canonical approach. This method enables us to gener…