activity
20182020
most citedThe Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design

538 citations · 697 across the 6 of their papers we have counts for

collaborators

7 papers

cond-mat.mtrl-sci2020★ 2 cited

Dataset of Random Relaxations for Crystal Structure Search of Li-Si System

Gowoon Cheon, Lusann Yang, Kevin McCloskey +2

Crystal structure search is a long-standing challenge in materials design. We present a dataset of more than 100,000 structural relaxations of potential battery anode materials fro…

cond-mat.mtrl-sci2020★ 27 cited

Discovery of stable surfaces with extreme work functions by high-throughput density functional theory and machine learning

Peter Schindler, Evan R. Antoniuk, Gowoon Cheon +2

The work function is the key surface property that determines how much energy is required for an electron to escape the surface of a material. This property is crucial for thermion…

cond-mat.mtrl-sci2020

A data-centric framework for crystal structure identification in atomistic simulations using machine learning

Heejung Chung, Rodrigo Freitas, Gowoon Cheon +1

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale…

cond-mat.mtrl-sci2020★ 538 cited

The Joint Automated Repository for Various Integrated Simulations (JARVIS) for data-driven materials design

Kamal Choudhary, Kevin F. Garrity, Andrew C. E. Reid +25

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional the…

cond-mat.mtrl-sci2019

Quantifying the search for solid Li-ion electrolyte materials by anion: a data-driven perspective

Austin D. Sendek, Gowoon Cheon, Mauro Pasta +1

We compile data and machine learned models of solid Li-ion electrolyte performance to assess the state of materials discovery efforts and build new insights for future efforts. Can…

cond-mat.mtrl-sci2018★ 5 cited

Machine learning-assisted discovery of many new solid Li-ion conducting materials

Austin D. Sendek, Ekin D. Cubuk, Evan R. Antoniuk +3

We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided b…

cond-mat.mtrl-sci2018★ 125 cited

Elastic properties of bulk and low-dimensional materials using Van der Waals density functional

Kamal Choudhary, Gowoon Cheon, Evan Reed +1

In this work, we present a high-throughput first-principles study of elastic properties of bulk and monolayer materials mainly using the vdW-DF-optB88 functional. We discuss the tr…