Genetic Algorithms Optimization for High Temperature Superconductors SN Class Molecular Effect Model with Electronics Applications

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2D polynomial fit with Matlab. As it was found in previous contributions, for Sn class the MEM shows get an approximate parabolic shape. Green extrapolated model, red, experimental dataset
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Published: Sep 30, 2022
DOI: https://doi.org/10.17762/ijrmee.v9i3.385
Keywords:
Genetic Algorithms (GA), Molecular Effect Model (MEM), Interior Optimization (IO), Graphical Optimization, Systems of Nonlinear Equations, Tikhonov Regularization (TR), Inverse Least Squares (ILS), Electronics Superconductors, High-Temperature Superconductors (HTSC), BCS Theory, [ Sn-Sb-Te-Ba-Mn-Cu-O ] Molecular HTSC Group, Molecular Mass (MO)

Main Article Content

Francisco Casesnoves
PhD Engineering, MSc Physics-Mathematics, Physician. Independent Research Scientist. International Association of Advanced Materials, Sweden. Uniscience Global Scientific Member, Wyoming, USA

Abstract

This contribution deals with the Molecular Effect Model (MEM) Genetic Algorithms polynomial-dual optimization for High Temperature Superconductors (HTSCs) class of [ Sn-Sb-Te-Ba-Mn-Cu-O ] . Results comprise Tikhonov Regularization Functionals development and mathematical methods for this HTSCs group without using logarithmic changes. Findings for this MEM optimization, based on Genetic Algorithms polynomial-dual-method show acceptable theoretical Numerical and 2D/3D Graphical Optimization solutions and low residuals. Solutions comprise two parts, the modelling for TC Molecular Effect predictions equations, and 2D graphics series of results. Electronics Physics applications for Superconductors and High Temperature Superconductors are specified for Isotope Effect in BCS theory and for  MEM and presented.

Article Details

How to Cite
Casesnoves, F. . (2022). Genetic Algorithms Optimization for High Temperature Superconductors SN Class Molecular Effect Model with Electronics Applications. International Journal on Recent Technologies in Mechanical and Electrical Engineering, 9(3), 153–161. https://doi.org/10.17762/ijrmee.v9i3.385
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Vol. 9 No. 3 (2022): July-September (2022) Issue
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Articles

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