activity
20202026
most citedMAISE: Construction of neural network interatomic models and evolutionary structure optimization

54 citations · 98 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2026

Transformer-Based Heartbeat Monitoring with FMCW Radar Under Random Body Motion

Matteo Pardi, Amir Hosein Oveis, Saba Kharabadze +1

Millimeter-wave Frequency Modulated Continuous Wave (FMCW) radar enables contactless cardiac monitoring, but heartbeat estimation becomes challenging when respiration and random bo…

cond-mat.mtrl-sci2023★ 10 cited

Machine learning search for stable binary Sn alloys with Na, Ca, Cu, Pd, and Ag

Aidan Thorn, Daviti Gochitashvili, Saba Kharabadze +1

We present our findings of a large-scale screening for new synthesizable materials in five M-Sn binaries, M = Na, Ca, Cu, Pd, and Ag. The focus on these systems was motivated by th…

cond-mat.mtrl-sci2023★ 12 cited

Thermodynamic stability of Li-B-C compounds from first principles

Saba Kharabadze, Maxwell Meyers, Charlsey R. Tomassetti +3

Prediction of high- superconductivity in hole-doped LiBC two decades ago has brought about an extensive effort to synthesize new materials with honeycomb B-C layers…

cond-mat.mtrl-sci2022★ 22 cited

Prediction of stable Li-Sn compounds: boosting ab initio searches with neural network potentials

Saba Kharabadze, Aidan Thorn, Ekaterina A. Koulakova +1

The Li-Sn binary system has been the focus of extensive research because it features Li-rich alloys with potential applications as battery anodes. Our present re-examination of the…

physics.comp-ph2020★ 54 cited

MAISE: Construction of neural network interatomic models and evolutionary structure optimization

Samad Hajinazar, Aidan Thorn, Ernesto D. Sandoval +2

Module for ab initio structure evolution (MAISE) is an open-source package for materials modeling and prediction. The code's main feature is an automated generation of neural netwo…