Genetic Algorithms (GA) Artificial Intelligence (AI) software was applied in 3D Graphical and Interior Optimization methods for several High Temperature Superconductors (HTSCs) classes. Namely, Hg-Cuprates HTSCs, [ Hg-Ba-Ca-Cu-O ] with [ TC > 0° ], and a extent review for Tin ( Sn ) class with [ TC > 0° ], and Thallium ( Tl ) one subject to [ TC ˂ 0° , TC > 0° ] in Molecular Effect Model (MEM). Results comprise both improvements and evaluation with Tikhonov Regularization Functionals algorithms for these HTSCs groups without using objective function logarithmic changes. Results also prove the differences among these classes for Molecular Effect Model (MEM) previously developed 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.