Genetic Algorithms Molecular Effect Model Optimization for High-temperature Superconductors Tin and Thallium Classes

Abstract

Genetic algorithms software was applied in 3D Graphical and Interior Optimization methods for two high-temperature Superconductors (HTSCs) classes. Namely, Tin (Sn) class with (TC>0°), and Thallium (Tl) one subject to (TC˂0°, TC>0°) in Molecular Effect Model (MEM). Results include mathematical Tikhonov Regularization Functionals algorithms for this group of HTSCs without using logarithmic changes. Results also show the contrasts between these two classes for Molecular Effect Model (MEM) hypothesis. Solutions show a series of 2D/3D imaging process charts complemented with a group of numerical results. Applications for MEM in electronics physics are presented, including those for high-temperature superconductors, superconductors, and medical technology.