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cond-mat.mtrl-sci2026

Can MACE Potentials Accurately Describe Magnetism and Phase Stability in Fe-Ni Alloys? A Systematic Benchmark

Kushal Ramakrishna, Mani Lokamani, Attila Cangi

We present a systematic benchmark of MACE potentials for iron-nickel alloys, focusing on structural, elastic, magnetic, and finite-temperature properties relevant to phase stabilit…

cond-mat.mtrl-sci2026

Thermal PBE in warm dense matter: Does it matter and is it accurate?

Kushal Ramakrishna, Mani Lokamani, Zhandos A. Moldabekov +3

Conditional probability density functional theory has recently been used to derive the temperature dependence of the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation…

cond-mat.mtrl-sci2024

Electrical Conductivity of Warm Dense Hydrogen from Ohm's Law and Time-Dependent Density Functional Theory

Kushal Ramakrishna, Mani Lokamani, Attila Cangi

Understanding the electrical conductivity of warm dense hydrogen is critical for both fundamental physics and applications in planetary science and inertial confinement fusion. We…

cond-mat.mtrl-sci20231 cited

Probing Iron in Earth's Core With Molecular-Spin Dynamics

Svetoslav Nikolov, Kushal Ramakrishna, Andrew Rohskopf +5

Dynamic compression of iron to Earth-core conditions is one of the few ways to gather important elastic and transport properties needed to uncover key mechanisms surrounding the ge…

cond-mat.mtrl-sci2023

Machine Learning-Driven Structure Prediction for Iron Hydrides

Hossein Tahmasbi, Kushal Ramakrishna, Mani Lokamani +1

We created a computational workflow to analyze the potential energy surface (PES) of materials using machine-learned interatomic potentials in conjunction with the minima hopping a…