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ULTERA database, developed under the ARPA-E's ULTIMATE program, 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. 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 this contribution repository at contribute.ultera.org As of September 2024, ULTERA contains over: 7,900+ property-datapoints, corresponding to 3,000+ unique HEAs, collected from 570+ unique DOIs. All data is available through a high-performance API, following FAIR principles, while statistics on it can be found at our ultera.org project web page. 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. Beyond large size, ULTERA has further advantage of being highly curated with many steps of data validation and then processed through our abnormal data detection tools (pyqalloy.ultera.org).
CCM, refractory alloys, metals, PyQAlloy, high entropy alloys, compositionally complex materials, alloys, data, ULTIMATE, ULTERA, entropy, CCA, MPEA, database, HEA
CCM, refractory alloys, metals, PyQAlloy, high entropy alloys, compositionally complex materials, alloys, data, ULTIMATE, ULTERA, entropy, CCA, MPEA, database, HEA
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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