activity
20162025
most citedStratified construction of neural network based interatomic models for multicomponent materials

86 citations · 243 across the 10 of their papers we have counts for

collaborators

10 papers

physics.comp-ph2025★ 3 cited

XtalOpt Version 14: Variable-Composition Crystal Structure Search for Functional Materials Through Pareto Optimization

Samad Hajinazar, Eva Zurek

Version 14 of XtalOpt, an evolutionary multi-objective global optimization algorithm for crystal structure prediction, is now available for download from its official website https…

cond-mat.mtrl-sci2024★ 2 cited

Powder X-Ray Diffraction Assisted Evolutionary Algorithm for Crystal Structure Prediction

Stefano Racioppi, Alberto Otero De la Roza, Samad Hajinazar +1

Experimentally obtained X-ray diffraction (XRD) patterns can be difficult to solve, precluding the full characterization of materials, pharmaceuticals, and geological compounds. He…

cond-mat.mtrl-sci2024★ 14 cited

Impact of Data Bias on Machine Learning for Crystal Compound Synthesizability Predictions

Ali Davariashtiyani, Busheng Wang, Samad Hajinazar +2

Machine learning models are susceptible to being misled by biases in training data that emphasize incidental correlations over the intended learning task. In this study, we demonst…

physics.comp-ph2024★ 15 cited

XtalOpt Version 13: Multi-Objective Evolutionary Search for Novel Functional Materials

Samad Hajinazar, Eva Zurek

Version 13 of XtalOpt, an evolutionary algorithm for crystal structure prediction, is now available for download from the CPC program library or the XtalOpt website, https://xtalop…

cond-mat.supr-con2023★ 38 cited

Full-bandwidth anisotropic Migdal-Eliashberg theory and its application to superhydrides

Roman Lucrezi, Pedro P. Ferreira, Samad Hajinazar +4

Migdal-Eliashberg theory is one of the state-of-the-art methods for describing conventional superconductors from first principles. However, widely used implementations assume a con…

cond-mat.mtrl-sci2023★ 8 cited

Structurally Constrained Evolutionary Algorithm for the Discovery and Design of Metastable Phases

Busheng Wang, Katerina P. Hilleke, Samad Hajinazar +2

Metastable materials are abundant in nature and technology, showcasing remarkable properties that inspire innovative materials design. However, traditional crystal structure predic…

cond-mat.mtrl-sci2023★ 7 cited

Electron-phonon physics from first principles using the EPW code

Hyungjun Lee, Samuel Poncé, Kyle Bushick +13

EPW is an open-source software for calculations of electron-phonon interactions and related materials properties. The code combines density functional perturba…

cond-mat.str-el2020★ 16 cited

Inhomogeneous Kondo-lattice in geometrically frustrated PrIrO

Mariam Kavai, Joel Friedman, Kyle Sherman +12

Magnetic fluctuations induced by geometric frustration of local Ir-spins disturb the formation of long range magnetic order in the family of pyrochlore iridates, RIrO$_…

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…

cond-mat.mtrl-sci2016★ 86 cited

Stratified construction of neural network based interatomic models for multicomponent materials

Samad Hajinazar, Junping Shao, Aleksey N. Kolmogorov

Recent application of neural networks (NNs) to modeling interatomic interactions has shown the learning machines' encouragingly accurate performance for select elemental and multic…