Transition Temperatures of Superconductors estimated from Periodic Table Properties
O. Paul Isikaku-Ironkwe

TL;DR
This paper presents an empirical method to estimate superconductor transition temperatures using Periodic Table properties, enabling the prediction and design of new high-temperature superconductors.
Contribution
It introduces a novel empirical formula and a material-specific characterization dataset (MSCD) model based on Periodic Table properties for estimating Tc.
Findings
Ko correlates with Fw/Z, Ne, Z, An, En, and Tc.
The model can predict Tcs of known and novel superconductors.
Correlations facilitate the search for high-temperature superconductors.
Abstract
Predicting the transition temperature, Tc, of a superconductor from Periodic Table normal state properties is regarded as one of the grand challenges of superconductivity. By studying the correlations of Periodic Table properties with known superconductors, it is possible to estimate their transition temperatures. Starting from the isotope effect and correlations of superconductivity with electronegativity (\Chi), valence electron count per atom (Ne), atomic number(Z) and formula weight (Fw), we derive an empirical formula for estimating Tc that includes an unknown parameter,(Ko). With average values of \Chi, Ne and Z, we develop a material specific characterization dataset (MSCD) model of a superconductor that is quantitatively useful for characterizing and comparing superconductors. We show that for most superconductors, Ko correlates with Fw/Z, Ne, Z, number of atoms (An) in the…
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Taxonomy
TopicsMachine Learning in Materials Science · Superconductivity in MgB2 and Alloys · Surface and Thin Film Phenomena
