2009/03/06 by J. C. Phillips, Phillips, J. C.
Chemistry · Engineering · Materials Science · Physics and Astronomy · #Advanced ceramic materials synthesis #FOS: Physical sciences #Inorganic Fluorides and Related Compounds #Superconducting Materials and Applications #Superconductivity (cond-mat.supr-con) #cond-mat.supr-con
paper · pdf · doi:10.48550/arxiv.0903.1306
arxiv created 2009/03/06 · openalex publication_date 2009/03/06 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The prediction of transition temperatures can be regarded in several ways, either as an exacting test of theory, or as a tool for identifying theoretical rules for defining new homology models. Popular "first principle" methods for predicting transition temperatures in conventional crystalline superconductors have failed for cuprate HTSC, as have parameterized models based on CuO2 planes (with or without apical oxygen). Following a path suggested by Bayesian probability, we find that the glassy, self-organized dopant network percolative model is so successful that it defines a new homology class appropriate to ceramic superconductors. The reasons for this success are discussed, and a critical comparison is made with previous theories. The predictions are successful for all ceramics, including new non-cuprates based on FeAs in place of CuO2.