The National Institute of Standards and Technology (NIST) has developed a comprehensive database called JARVIS-DFT as part of their larger NIST-JARVIS project. This database focuses on providing density functional theory (DFT) predictions of material properties for approximately 40,000 bulk and 1,000 low-dimensional crystalline materials. The database contains a wide range of properties, including formation energies, bandgaps, elastic constants, piezoelectric constants, and magnetic moments, as well as more specialized data like exfoliation energies for van der Waals bonded materials and Wannier tight-binding Hamiltonians.
The JARVIS-DFT project has been featured in recent publications, highlighting its potential for accelerating the discovery of efficient solar-cell materials using quantum and machine-learning methods. This project serves as a valuable resource for researchers and scientists working in the field of materials science and quantum computing, providing access to a vast amount of data and research on crystalline materials.
Source: https://www.nist.gov/programs-projects/jarvis-dft
Keywords: density functional theory, quantum computing, materials science, machine learning, crystalline materials
