Materials Informatics Reveals Unexplored Structure Space in Cuprate Superconductors. (24th September 2021)

• Record Type: Journal Article
• Authors: Goodall, Rhys E. A.; Zhu, Bonan; MacManus‐Driscoll, Judith L.; Lee, Alpha A.
• Is Part Of: Advanced functional materials. Volume 31:Number 52(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-24
• Subjects: cuprates -- materials informatics -- superconductivity; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adfm.202104696
• Languages: English
• ISSNs: 1616-301X

Abstract

Abstract: High‐temperature superconducting cuprates have the potential to be transformative in a wide range of energy applications. In this work, the corpus of historical data about cuprates is analyzed using materials informatics, re‐examining how their structures are related to their critical temperatures (Tc). The available data is highly clustered and no single database contains all the features of interest to properly examine trends. To work around these issues a linear calibration approach that allows the utilization of multiple data sources is employed, combining fine resolution data for which the Tc is unknown with coarse resolution data where it is known. The hybrid data set constructed enables the exploration of the trends in Tc with the apical and in‐plane copper–oxygen distances. It is shown that large regions of the materials space have yet to be explored. Novel experiments relying on the nano‐engineering of the crystal structure may enable the exploration of such new regions. Based on the trends identified it is proposed that single layer Bi‐based cuprates are good candidate systems for such experiments. Abstract : The apical and in‐plane copper–oxygen distances play an important role in controlling superconductivity in cuprates. Combining high and low resolution data about the structures of cuprates using materials informatics shows that large regions of materials space are yet to be explored. Emerging nano‐engineering techniques show promise for exploring this space and improving Tc.