ULtrahigh TEmperature Refractory Alloys (ULTERA) Database of High Entropy Alloys

<p>ULTERA database, developed under the <a href="https://arpa-e.energy.gov/?q=arpa-e-programs/ultimate">ARPA-E's ULTIMATE program</a>, is aimed at collecting literature data on high entropy alloys (HEAs) to facilitate rapid ML-based discovery of new ones using forward and inverse design.</p> <p>The main scope of this dataset is collecting data on compositionally complex alloys (CCAs), also known as high entropy alloys (HEAs) and multi-principle-element alloys (MPEAs), with extra attention given to (1) high-temperature (refractory) mechanical data, (2) phases present under different processing conditions. Although low-entropy alloys (incl. binaries) are typically not presented to the end-user (or counted in statistics), some are present and used in ML efforts; thus, all high-quality alloy data contributions are welcome! You can set up a contribution in as little as few minutes with <a href="https://contribute.ultera.org">this contribution repository at contribute.ultera.org</a></p> <p>As of September 2024, ULTERA contains over:</p> <ul> <li>7,900+ property-datapoints, corresponding to</li> <li>3,000+ unique HEAs, collected from</li> <li>570+ unique DOIs.</li> </ul> <p>All data is available through a high-performance API, following FAIR principles, while statistics on it can be found at our <a href="https://ultera.org">ultera.org&nbsp;project web page.</a> The database architecture is designed to automatically integrate starting literature data in real time with methods such as experiments, generative modeling, predictive modeling, and validations.</p> <p>Beyond large size, ULTERA has further advantage of being highly curated with&nbsp;many steps of data validation and then processed through <a href="https://pyqalloy.ultera.org">our abnormal data detection tools (pyqalloy.ultera.org).</a></p>