Phase Diagrams Construction Using Mean-Field Renormalization and Neural Network Fitting

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Rodriguez, Esteban Bedoya, Diaz, Leon Escobar, Hernandez, Sebastian Trujillo
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866916652255281152
author Rodriguez, Esteban Bedoya
Diaz, Leon Escobar
Hernandez, Sebastian Trujillo
author_facet Rodriguez, Esteban Bedoya
Diaz, Leon Escobar
Hernandez, Sebastian Trujillo
contents Employing the mean-field renormalization group (MFRG) method, we analyzed the $Fe_p Mn_{0.6-p}Al_{0.4}$ and $Fe_{p}Al_{1-p}$ alloys, incorporating second-neighbor interactions in the latter for the first time within this framework. Our analysis utilized neural network fitting, yielding promising results in both the phase diagram adjustments and the estimation of bond energies.
format Preprint
id arxiv_https___arxiv_org_abs_2503_10646
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Phase Diagrams Construction Using Mean-Field Renormalization and Neural Network Fitting
Rodriguez, Esteban Bedoya
Diaz, Leon Escobar
Hernandez, Sebastian Trujillo
Materials Science
Strongly Correlated Electrons
Employing the mean-field renormalization group (MFRG) method, we analyzed the $Fe_p Mn_{0.6-p}Al_{0.4}$ and $Fe_{p}Al_{1-p}$ alloys, incorporating second-neighbor interactions in the latter for the first time within this framework. Our analysis utilized neural network fitting, yielding promising results in both the phase diagram adjustments and the estimation of bond energies.
title Phase Diagrams Construction Using Mean-Field Renormalization and Neural Network Fitting
topic Materials Science
Strongly Correlated Electrons
url https://arxiv.org/abs/2503.10646