  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
formula, number of elements (En) and with Tc. We study some superconductor
families and use the discovered correlations to predict similar and novel
superconductors and also estimate their Tcs. Thus the material specific
equations derived in this paper, the material specific characterization dataset
(MSCD) system developed here and the discovered correlation between Tc and
Fw/Z, En and An, provide the building blocks for the analysis, design and
search of potential novel high temperature superconductors with specific
estimated Tcs.
