Publications (28)
Quantum effects on dislocation motion from Ring-Polymer Molecular Dynamics
Rodrigo Freitas, Mark Asta, Vasily V. Bulatov
Quantum motion of atoms known as zero-point vibrations is recognized to be important at low temperatures in condensed matter systems comprised of light atoms or ions, affecting suc…
Stable Machine Learning Potentials for Liquid Metals via Dataset Engineering
Alex Tai, Jason Ogbebor, Rodrigo Freitas
Liquid metals are central to energy-storage and nuclear technologies, yet quantitative knowledge of their thermophysical properties remains limited. While atomistic simulations off…
Capturing short-range order in high-entropy alloys with machine learning potentials
Yifan Cao, Killian Sheriff, Rodrigo Freitas
Chemical short-range order (SRO) affects the distribution of elements throughout the solid-solution phase of metallic alloys, thereby modifying the background against which microst…
The Uhlenbeck-Ford model: Exact virial coefficients and application as a reference system in fluid-phase free-energy calculations
Rodolfo Paula Leite, Rodrigo Freitas, Rodolfo Azevedo +1
The Uhlenbeck-Ford (UF) model was originally proposed for the theoretical study of imperfect gases, given that all its virial coefficients can be evaluated exactly, in principle. H…
Atomistic Simulations of Short-range Ordering with Light Interstitials in Inconel Superalloys
Tyler D. Dolžal, Emre Tekoglu, Jong-Soo Bae +3
This study employed hybrid Monte Carlo Molecular Dynamics simulations to investigate the short-range ordering behavior of Ni-based superalloys doped with boron or carbon. The simul…
A data-centric framework for crystal structure identification in atomistic simulations using machine learning
Heejung Chung, Rodrigo Freitas, Gowoon Cheon +1
Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale…