activity
20152026
most citedDynamic Jahn-Teller effect in the strong spin-orbit coupling regime

41 citations · 81 across the 10 of their papers we have counts for

collaborators

11 papers

physics.comp-ph2026

Reconstructing local environments from concise atomistic representations

Jigyasa Nigam, Tuong Phung, Ameya Daigavane +2

Symmetry-based representations of local atomic structure, such as the power spectrum or bispectrum, are routinely used to characterize the structural diversity of datasets and as i…

physics.comp-ph2026

Learning Lattice Parameters from Powder X-Ray Diffraction Data Using Invariants

Elyssa Hofgard, Kyucheol Min, Nofit Segal +8

We present a machine learning (ML) method to determine unit cell parameters from powder X-Ray diffraction (XRD) data using a novel invariant lattice representation. In ML, the data…

cond-mat.str-el2024★ 41 cited

Dynamic Jahn-Teller effect in the strong spin-orbit coupling regime

Ivica Zivkovic, Jian-Rui Soh, Oleg Malanyuk +15

Exotic quantum phases, arising from a complex interplay of charge, spin, lattice and orbital degrees of freedom, are of immense interest to a wide research community. A well-known…

cond-mat.mtrl-sci2024

Depth-resolved profile of the interfacial ferromagnetism in superlattices

J. R. Paudel, A. Mansouri Tehrani, M. Terilli +10

Emergent magnetic phenomena at interfaces represent a frontier in materials science, pivotal for advancing technologies in spintronics and magnetic storage. In this letter, we util…

cond-mat.str-el2023

Probing the Mott-insulating behavior of BaMgReO with DFT+DMFT

Maximilian E. Merkel, Aria Mansouri Tehrani, Claude Ederer

We investigate the interplay of spin-orbit coupling, electronic correlations, and lattice distortions in the double perovskite BaMgReO. Combining density-functional…

cs.LG2023★ 16 cited

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Xuan Zhang, Limei Wang, Jacob Helwig +60

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…

cond-mat.mtrl-sci2023★ 9 cited

Exploring energy landscapes of charge multipoles using constrained density functional theory

Luca Schaufelberger, Maximilian E. Merkel, Aria Mansouri Tehrani +2

We present a method to constrain local charge multipoles within density-functional theory. Such multipoles quantify the anisotropy of the local charge distribution around atomic si…

cond-mat.mtrl-sci2022

Charge multipoles correlations and order in CsTaCl

Aria Mansouri Tehrani, Jian-Rui Soh, Jana Pásztorová +4

We examine the role of charge, structural, and spin degrees of freedom in the previously poorly understood phase transition in the 5 transition-metal double perovskite CsT…

cond-mat.mtrl-sci2022★ 7 cited

Physics-guided descriptors for prediction of structural polymorphs

Bastien F. Grosso, Nicola A. Spaldin, Aria Mansouri Tehrani

We develop a method combining machine learning (ML) and density functional theory (DFT) to predict low-energy polymorphs by introducing physics-guided descriptors based on structur…

cond-mat.mtrl-sci2019★ 8 cited

An unconventional mechanism for simultaneous high hardness and ductility in MoBC

Aria Mansouri Tehrani, Amber Lim, Jakoah Brgoch

Materials either have a high hardness or excellent ductility, but rarely both at the same time. MoBC is one of the only crystalline materials that simultaneously has a high Vic…

cond-mat.mtrl-sci2015

Influencing the Martensitic Phase Transformation in NiTi through Point Defects

Aria Mansouri Tehrani, Hamidreza Shahrokhshahi, Nader Parvin +1

Equiatomic nickle-titanium (NiTi) is investigated to determine the consequences of point defects on the Martensitic phase transformation. Using molecular dynamics (MD) simulations,…