376 citations · 948 across the 14 of their papers we have counts for
14 papers
Accelerating High-Throughput Phonon Calculations via Machine Learning Universal Potentials
Huiju Lee, Vinay I. Hegde, Chris Wolverton +1
Phonons play a critical role in determining various material properties, but conventional methods for phonon calculations are computationally intensive, limiting their broad applic…
Towards Informatics-Driven Design of Nuclear Waste Forms
Vinay I. Hegde, Miroslava Peterson, Sarah I. Allec +11
Informatics-driven approaches, such as machine learning and sequential experimental design, have shown the potential to drastically impact next-generation materials discovery and d…
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability
Sarah I. Allec, Xiaonan Lu, Daniel R. Cassar +8
Glasses form the basis of many modern applications and also hold great potential for future medical and environmental applications. However, their structural complexity and large c…
By how much can closed-loop frameworks accelerate computational materials discovery?
Lance Kavalsky, Vinay I. Hegde, Eric Muckley +3
The implementation of automation and machine learning surrogatization within closed-loop computational workflows is an increasingly popular approach to accelerate materials discove…
OPTIMADE, an API for exchanging materials data
Casper W. Andersen, Rickard Armiento, Evgeny Blokhin +53
The Open Databases Integration for Materials Design (OPTIMADE) consortium has designed a universal application programming interface (API) to make materials databases accessible an…
AutoMat: Accelerated Computational Electrochemical systems Discovery
Emil Annevelink, Rachel Kurchin, Eric Muckley +17
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and…
Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Vinay I. Hegde, Christopher K. H. Borg, Zachary del Rosario +7
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be use…
Ternary mixed-anion semiconductors with tunable band gaps from machine-learning and crystal structure prediction
Maximilian Amsler, Logan Ward, Vinay I. Hegde +3
We report the computational investigation of a series of ternary XYZ and XYZ compounds with X={Mg, Ca, Sr, Ba}, Y={P, As, Sb, Bi}, and Z={S, Se, Te}. The compos…
The Phase Stability Network of all Inorganic Materials
Vinay I. Hegde, Muratahan Aykol, Scott Kirklin +1
One of the holy grails of materials science, unlocking structure-property relationships, has largely been pursued via bottom-up investigations of how the arrangement of atoms and i…
Network analysis of synthesizable materials discovery
Muratahan Aykol, Vinay I. Hegde, Linda Hung +4
Assessing the synthesizability of inorganic materials is a grand challenge for accelerating their discovery using computations. Synthesis of a material is a complex process that de…
Exploring the high-pressure materials genome
Maximilian Amsler, Vinay I. Hegde, Steven D. Jacobsen +1
A thorough in situ characterization of materials at extreme conditions is challenging, and computational tools such as crystal structural search methods in combination with ab init…
Designing and discovering a new family of semiconducting quaternary Heusler compounds based on the 18-electron rule
Jiangang He, S. Shahab Naghavi, Vinay I. Hegde +2
Intermetallic compounds with sizable band gaps are attractive for their unusual properties but rare. Here, we present a new family of stable semiconducting quaternary Heusler compo…
Computational Investigation of Half-Heusler Compounds for Spintronics Applications
Jianhua Ma, Vinay I. Hegde, Kamaram Munira +6
We present first-principles density functional calculations of the electronic structure, magnetism, and structural stability of 378 half-Heusler compounds (with …
Ultralow Thermal Conductivity in Full-Heusler Semiconductors
Jiangang He, Maximilian Amsler, Yi Xia +6
Semiconducting half- and, to a lesser extent, full-Heusler compounds are promising thermoelectric materials due to their compelling electronic properties with large power factors.…