30 citations · 126 across the 15 of their papers we have counts for
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MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance
Bartosz Brzoza, Wiktoria Szopa, Zakaria Elabid +5
Electronic-structure calculations based on Kohn-Sham density functional theory remain indispensable in computational materials science and chemistry. Their computational cost, howe…
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…
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…
Towards Non-van der Waals 2D Topological Insulators
Mani Lokamani, Gustav Bihlmayer, Gregor Michalicek +3
Non-van der Waals two-dimensional (2D) materials derived from strongly bonded non-layered crystals have recently emerged as a novel and rising platform for nanoscale research. Whil…
The CP-PAW code package for first-principles calculations from a user's perspective
Peter E. Blöchl, Robert Schade, Lukas Allen-Rump +5
CP-PAW is a combined electronic structure and ab-initio molecular dynamics code to perform mixed quantum and classical simulations of atomistic condensed phase systems, such as sol…
Prediction of atomic H adsorption energies in metalloid doped MSSe (M = Mo/W) Janus layers: A combined DFT and machine learning study
G. Tejaswini, Anjana E Sudheer, Amrendra Kumar +9
Janus derivatives of 2H MX2 (M = Mo/W; X = S/Se), namely MSSe, have already been experimentally realized and explored for applications in photocatalysis, photovoltaics, and optoele…
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…
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…
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…
Transferable Interatomic Potentials for Aluminum from Ambient Conditions to Warm Dense Matter
Sandeep Kumar, Hossein Tahmasbi, Kushal Ramakrishna +5
We present a study on the transport and materials properties of aluminum spanning from ambient to warm dense matter conditions using a machine-learned interatomic potential (ML-IAP…
Impact of Electronic Correlations on High-Pressure Iron: Insights from Time-Dependent Density Functional Theory
Kushal Ramakrishna, Mani Lokamani, Andrew Baczewski +2
We present a comprehensive investigation of the electrical and thermal conductivity of iron under high pressures at ambient temperature, employing the real-time formulation of time…
Electrical Conductivity of Iron in Earth's Core from Microscopic Ohm's Law
Kushal Ramakrishna, Mani Lokamani, Andrew Baczewski +2
Understanding the electronic transport properties of iron under high temperatures and pressures is essential for constraining geophysical processes. The difficulty of reliably meas…