JARVIS-publications

JARVIS-FF

Evaluation and comparison of classical interatomic potentials through a user-friendly interactive web-interface, Scientific Data 4, 160125 (2017)

High-throughput assessment of vacancy formation and surface energies of materials using classical force-fields, J. Phys. Cond. Matt. 30, 395901(2018).

JARVIS-DFT

High-throughput Identification and Characterization of Two-dimensional Materials using Density functional theory, Scientific Reports 7, 5179 (2017)

Computational Screening of High-performance Optoelectronic Materials using OptB88vdW and TBmBJ Formalisms, Scientific Data 5, 180082 (2018)

Elastic properties of bulk and low-dimensional materials using Van der Waals density functional, Phys. Rev. B, 98, 014107 (2018).

Convergence and machine learning predictions of Monkhorst-Pack k-points and plane-wave cut-off in high-throughput DFT calculations, Comp. Mat. Sci. 161, 300 (2019)

High-throughput discovery of topological materials using spin-orbit spillage, submitted

Accelerated Discovery of Efficient Solar-cell Materials using Quantum and Machine-learning Methods, submitted

JARVIS-ML

Machine learning with force-field inspired descriptors for materials: fast screening and mapping energy landscape, Phys. Rev. Mat., 2, 083801 (2018).

Materials Science in the AI age: high-throughput library generation, machine learning and a pathway from correlations to the underpinning physics, submitted


More details coming soon !

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