HIGH-TEMPERATURE SUPERCONDUCTING THIN-FILMS - A MULTIVARIATE STATISTICAL APPROACH

Recent investigations have indicated that high-temperature superconduc ting thin films produced by chemical vapour deposition possess interes ting properties. The present study reveals a new aspect of this trend, i.e. detection of similarities or dissimilarities of these materials with respect to their technological and superconducting properties, us ing some multivariate statistical approaches like cluster, principle c omponents and multiple regression analysis. This approach adds to the conventional knowledge of fabrication parameters and superconducting p roperties by establishing the number and type of conditional factors r esponsible for these properties or technologies, correlation of variab les (properties) within a certain conditional factor, similarities bet ween film-producing teams even with the use of different technological parameters etc. Multivariate statistics make it possible to detect so me quantitative links between superconducting and fabrication paramete rs and to suggest certain patterns of high-temperature superconducting thin films possessing common features.