Genetic algorithms molecular effect model optimization computational method for high temperature superconductors

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 comprise Tikhonov Regularization Functional mathematical algorithms for these HTSCs group 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. Electronics Physics applications for Superconductors and High Temperature Superconductors and Medical Technology are specified for MEM and presented.