NIST Materials Data Repository
The National Institute of Standards and Technology has created a materials science data repository as part of an effort in coordination with the Materials Genome Initiative (MGI) to establish data exchange protocols and mechanisms that will foster data sharing and reuse across a wide community of researchers, with the goal of enhancing the quality of materials data and models. Data present on this system are varied and may originate from within NIST or from the worldwide materials community. Data present on this system may or may not be critically reviewed.
All data in this repository are intended to be public; some data may be a part of invitation-only collections while researchers continue to analyze the data prior to publication, with the goal of making the public data presentable in a meaningful way. Publishable data derived from working data will be made public at the appropriate time (this may coincide with end of a grant or when the data has been accepted for publication).
The NIST Materials Data Repository is open to the research community interested in developing best practices in the management of materials data. We are currently looking into use cases for expansion of the site including, but not limited to, partnerships with other projects focusing on discoverability.
Anyone having an interest in an invitation-only collection should contact the site administrator for more information.
This is the dataset of materials obtained from the Jarvis-DFT dataset and used for the study "Machine learning approaches for feature engineering of the crystal structure: Application to the prediction of the formation ...
X-ray computed tomography of large HMX crystals, and scanning electron microscopy of focused ion beam milled/polished small HMX crystals of varying solid phases.
Spherical nanoindentation stress-strain curves of primary-α grains in Ti5-2.5, Ti811, Ti64, Ti6242 and Ti6246 alloys Recently established spherical indentation stress-strain protocols have demonstrated the feasibility of measuring reliably the mechanical responses at different material structure length scales in a broad range of structural ...
(2019)A new algorithm was developed to segment three-dimensional fibers in multi-directional fiber-reinforced composites (FRCs) imaged using X-ray microtomography (µCT). Validation of the algorithm was performed using synthetic ...
File contains characterization data related to carbon fiber composite coupons and constituents.