Materials fingerprints identified for informatics
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semiconductor materials. The researchers further used a graph-drawing algorithm to create a map of materials connected by their fingerprint similarities. In their arespite the vast amounts of data ticle, which was published in the February piling up in established materials 10 issue of Chemistry of Materials (DOI: databases, there has not been much suc10.1021/cm503507h; p. 735), researchers cess in forming quantitative relations demonstrate a B-fingerprint network that between the properties and the overall shows a clear separation between metals function of a material. The ability to preand non-metals. There is also high clusdict future materials and their propertering among subgroups, such as semities from the information contained in conductors and bimetals. these repositories is a much sought afThe researchers refer to this approach ter goal in materials research. It is then as visualizing and analyzing materials not surprising that this is also a mighty and their properties as materials cartogchallenge, with few explorers groping raphy. This might aid in the prediction in the dark due to a lack of better tools of new materials with a given property and techniques. by being able to identify similar materiA team of researchers, led by Stefano als. The researchers illustrate this with a Curtarolo of Duke University and superconductor data map that shows high Alexander Tropsha of The University of clustering among high-temperature superNorth Carolina at Chapel Hill, has now conductors, as marked in the figure. Using employed a set of novel materials fingera custom quantitative materials structure– prints to quantify a material’s physical, property relationship (QMSPR), they electronic, and geometrical properties were able to predict—with over 94% accuracy—whether the critical temperature of a given material would fall above or below a threshold temperature. This is interesting, as the fingerprints by themselves do not contain any information other than the material’s electronic structure. “The challenge that we face today is to translate data into knowledge by establishing relationships between inherent material structural properties and their function,” Curtarolo and Tropsha said in a communication. “Our studies help bridge this gap, enhancing our ability to explore and exploit these data for rational design of novel materials with the desired function.” Databases such as AFLOWLIB and ICSD provided the data used to create the fingerprints. The data for superconductors were taken from the Handbook of Superconductivity, CRC Handbook of Chemistry and Physics, and the Supercon Materials cartography: Mapping the superconductivity critical temperature with relevant regions outlined. database. Reproduced with permission from Chem. Mater. 27 (3) (2015), DOI: 10.1021/cm503507h; p. 735. © 2014 Vineet Venugopal American Chemical Society. Materials fingerprints identified for informatics
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MRS BULLETIN
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VOLUME 40 • APRIL 2015
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