Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method

Джураев, Д.Р., Тураев, А.А., Тураев, О.Г.

O‘zbekiston fizika jurnali · 2026-yil

Annotatsiya

This paper presents the results of a study on modeling and predicting the critical superconductingtemperature (Tc) of YBa2Cu3O7δ (YBCO) samples synthesized via the solid-state reactionmethod, using a multiparameter machine approach. The influence of synthesis parameters suchas calcination temperature and duration (Tcal, τ1, τ2), sintering temperature (Tsin), pressing pressure(P), and cooling time (τ3) was investigated. To model the complex, uncertain, and multifactorrelationships between synthesis conditions and Tc values, a Random Forest regressionmodel was employed. The Random Forest model achieved high accuracy: R2 = 0.993, MAE =0.0106 K, and RMSE = 0.0125 K, indicating excellent agreement between predicted and experimentalTc values. Feature importance analysis revealed that τ2 (sintering time) and Tsin (sinteringtemperature), τ3 (cooling time), and τ1 (calcination time) have the greatest impact on Tc.This hierarchy of importance was further confirmed using SHAP analysis (Shapley values).This study demonstrates the potential for effective development of high-performance superconductingmaterials through the integration of regression modeling and experimental design.

Maqola ma’lumotlari
MualliflarДжураев, Д.Р., Тураев, А.А., Тураев, О.Г.
JurnalO‘zbekiston fizika jurnali
NashriyotЎзбекистон Республикаси Фанлар академияси
ISSN1025-8817, 2181-077X
Nashr sanasi2026-02-18
Jild27
Son4
TilIngliz
Ilmiy sohaFizika-matematika
DOI10.52304/.v27i4.611
Indeksga qo‘shilgan2026-08-26

DOI: 10.52304/.v27i4.611 · Maqolaning asl sahifasi

Kalit so‘zlar

YBCO, критическая температура, метод Тагучи, случайный лес, регрессионная модель, YBCO, critical temperature, Taguchi method, Random Forest regression model

Ilmiy soha

Fizika-matematika

Iqtibos keltirish

APAДжураев, Д.Р., Тураев, А.А., & Тураев, О.Г. (2026). Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method. O‘zbekiston fizika jurnali, 27(4). https://doi.org/10.52304/.v27i4.611
GOST (OAK)Джураев, Д.Р., Тураев, А.А., Тураев, О.Г. Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method // O‘zbekiston fizika jurnali. – 2026. – T. 27, № 4. – DOI: 10.52304/.v27i4.611.
MLAДжураев, Д.Р., Тураев, А.А., and Тураев, О.Г. “Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method.” O‘zbekiston fizika jurnali, 27(4), 2026. https://doi.org/10.52304/.v27i4.611
ChicagoДжураев, Д.Р., Тураев, А.А., and Тураев, О.Г. “Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method.” O‘zbekiston fizika jurnali, 27(4) (2026). https://doi.org/10.52304/.v27i4.611
HarvardДжураев, Д.Р., Тураев, А.А., and Тураев, О.Г (2026) ‘Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method’, O‘zbekiston fizika jurnali, 27(4). https://doi.org/10.52304/.v27i4.611
BibTeX
@article{article2026,
  title = {Optimization of the Synthesis of Superconducting YBCO Samples Using the Random Forest Algorithm and the Taguchi Method},
  author = {Джураев, Д.Р. and Тураев, А.А. and Тураев, О.Г.},
  journal = {O‘zbekiston fizika jurnali},
  year = {2026},
  volume = {27},
  number = {4},
  doi = {10.52304/.v27i4.611},
  url = {https://doi.org/10.52304/.v27i4.611}
}

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