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2026 AziziKasin Sulphate Chloride Chalcopyrite Leaching Model

Mohammadreza AziziKasin, Hiva Samadian

2026enchalcopyritecopper recoveryleachingoxidizing agentsGaussian process regressionhydrometallurgy

Abstract

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Chalcopyrite leaching in sulfuric acid with chloride-based oxidizing agents (NaCl, NaClO, NaClO3) was investigated to optimize copper recovery. The influence of sulfuric acid concentration, chloride concentration, and temperature on copper dissolution was systematically evaluated through experimental tests. A Gaussian Process Regression (GPR) model was developed to predict copper recovery, integrating experimental data with Partial Rank Correlation Coefficient (PRCC) analysis to assess the impact of key variables. The results showed that NaClO and NaClO3 significantly improved copper recovery, with NaClO3 achieving nearly 100% copper recovery in under 30 min at higher temperatures. Maximum recovery of 45.5% was achieved with NaCl at 1 M concentration, 3 M H2SO4, and 80 ◦C. The GPR model demonstrated superior predictive accuracy, achieving RMSE = 4.0028 and R2 = 0.99, outperforming Support Vector Machine Regression (SVMR) and Ensemble Regression (ER) models. The GPR model accurately predicted recovery under conditions not tested experimentally, providing a robust tool for process optimization. The results confirm the effectiveness of chloride-based oxidizers in enhancing copper dissolution and demonstrate the practical application of GPR for optimizing leaching conditions, ensuring maximum copper recovery in hydrometallurgical processes.

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Cite This Work

@article{295b7771-12ce-46dd-99a3-59385ba57fb2,
  title={2026   AziziKasin   Sulphate Chloride Chalcopyrite Leaching Model},
  author={Mohammadreza AziziKasin and Hiva Samadian},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - 2026   AziziKasin   Sulphate Chloride Chalcopyrite Leaching Model
AU  - Mohammadreza AziziKasin
AU  - Hiva Samadian
PY  - 2026
LA  - en
ER  -

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