The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

Abstract

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov.

Computational scanning tunneling microscope image database

“…STM imaging is particularly well-suited to studying two-dimensional (2D) materials, such as graphene 16 , MoS 2 17 , NbSe 2 18 , WSe 2 19 , WTe 2 20 , FeSe 21 , black-phosphrous 22 , 23 and SnSe 24 . 2D materials 25 , 26 has opened diverse areas of application, such as sub-micron level electronics 27 , flexible and tunable electronics 28 , superconductivity 29 , photo-voltaics 30 , water-purification 31 , sensors 32 , thermal-management 33 , energy-storage 34 , medicine 35 , quantum dots 36 , 37 and composites 38 – 40 . The surfaces of 2D materials are unique because they lack dangling bonds, allowing them to be exfoliated.…”

“…We use the recently developed JARVIS-DFT database ( https://jarvis.nist.gov/jarvisdft ) and select 2D materials with exfoliation energy less than 200 meV/atom. The JARVIS-DFT database contains about 40000 bulk and 1000 two-dimensional materials with their DFT-computed structural, energetic 26 , elastic 41 , optoelectronic 42 , thermoelectric 43 , piezoelectric, dielectric, infrared 44 , solar-efficiency 45 , and topological 46 , 47 properties. We note that there are several factors that can influence the appearance of experimental or DFT-based STM image predictions, such as the STM-tip material, bias voltage, and the scanning mode, i.e .…”

Database of Wannier tight-binding Hamiltonians using high-throughput density functional theory

“…Since its launch in 2011, the Materials Genome Initiative (MGI) 33 has spurred the generation of several high-throughput databases and tools such as from AFLOW 34 , Materials Project 35 , Open Quantum Materials Database (OQMD) 36 , Materials Cloud 37 , AiiDA 38 , NOMAD 39 , and NIST-JARVIS 40 . They have played key roles in the generation of electronic-property related databases to reduce the time between materials discovery and application.…”

“…We use our Wannierization workflow on the JARVIS-DFT ( https://jarvis.nist.gov/jarvisdft ) database which is a part of the MGI at NIST. The NIST-JARVIS 40 ( https://jarvis.nist.gov ) has several components such as JARVIS-FF 47 , 48 , JARVIS-DFT 48 – 57 , JARVIS-ML 49 , 51 , 57 – 59 , JARVIS-STM 51 , JARVIS-Heterostructure 53 and hosts material-properties such as lattice parameters 50 , formation energies 60 , 2D exfoliation energies 55 , bandgaps, elastic constants 50 , dielectric constants 59 , infrared intensities 59 , piezoelectric constants 59 , thermoelectric properties 57 , optoelectronic properties, solar-cell efficiencies 47 , 49 , topological materials 17 , 21 , electric field gradient 61 , and computational STM images 51 . The JARVIS-DFT database consists of ≈ 40000 3D and ≈1000 2D materials.…”

Two-dimensional Weyl points and nodal lines in pentagonal materials and their optical response

“…4,5 The upsurge of interest in these materials has motivated many computational high-throughput searches. This has resulted in the generation of several databases, [6][7][8][9][10][11] with a great amount of prospective 2D materials with energetically favorable phases. In some of them, interlayer van der Waals interactions imply that they might be obtained by exfoliation.…”