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Advancing toward aSustainable metal extraction sustainableSustainable society relies on intensive use of critical metalsCritical metals such as indiumIndium, germaniumGermanium, and antimonyAntimony. This requires improving their recoveryCritical metal recovery rates in metalMetal production, finding value in waste materials and creating new recyclingRecycling methods. However, there are gaps in our understanding of critical metal behavior in metallurgical processes. A promising approach to understanding the distribution behavior of these target metalsMetal is integrating systematic thermodynamic modelingThermodynamic modeling with key experiments. This work aims to develop a comprehensive thermodynamic database for oxideOxide systems, via adding critical element oxides like GeO2, In2O3, and Sb2O3 to major slag components such as PbO, ZnO, CaO, SiO₂, and FeO. Our methodology involves creating physics-based machine learningMachine learning models to estimate the thermodynamic properties ( \(\Delta H_{298.15K}^{0} , S_{298.15K}^{0} , C_{P}\) ) of critical metal-containing oxidesOxide, which are often scarce in current literature. This model will support thermodynamic modelingThermodynamic modeling of phase equilibria and diagrams based on the CALPHAD method, validated through experiments. The resulting oxide database can be linked with existing metalMetal and gas databases, allowing for predictive modelingModeling of current processes and exploration of new recovery methods forCritical metal recovery critical metalsCritical metals from waste streams, including by-products from copperCopper, lead, and zinc production, as well as electronic wasteElectronic waste. This integration enables reasonable calculations of how critical metalsMetal distribute across different phases (metal, slag, and gas), helping to identify optimal conditions, like composition, temperature, and oxygen levels, within the complex parameter space of multi-component systems. This work summarizes the challenges, advancements, and findings achieved so far.

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Enhancing Recovery of Critical Metals Indium, Germanium, and Antimony from Metallurgical Processes Through Thermodynamic Modeling

  • 会议论文

  • 发表日期：

    2025年

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  • Elmira Moosavi-Khoonsari,
  • Saleh Rasouli-Jouryabi,
  • Abbas Ahmadi Siahboumi,
  • Jesus Alejandro Arias-Hernandez,
  • Manel Houria

摘要

Advancing toward aSustainable metal extraction sustainableSustainable society relies on intensive use of critical metalsCritical metals such as indiumIndium, germaniumGermanium, and antimonyAntimony. This requires improving their recoveryCritical metal recovery rates in metalMetal production, finding value in waste materials and creating new recyclingRecycling methods. However, there are gaps in our understanding of critical metal behavior in metallurgical processes. A promising approach to understanding the distribution behavior of these target metalsMetal is integrating systematic thermodynamic modelingThermodynamic modeling with key experiments. This work aims to develop a comprehensive thermodynamic database for oxideOxide systems, via adding critical element oxides like GeO2, In2O3, and Sb2O3 to major slag components such as PbO, ZnO, CaO, SiO₂, and FeO. Our methodology involves creating physics-based machine learningMachine learning models to estimate the thermodynamic properties ( \(\Delta H_{298.15K}^{0} , S_{298.15K}^{0} , C_{P}\) ) of critical metal-containing oxidesOxide, which are often scarce in current literature. This model will support thermodynamic modelingThermodynamic modeling of phase equilibria and diagrams based on the CALPHAD method, validated through experiments. The resulting oxide database can be linked with existing metalMetal and gas databases, allowing for predictive modelingModeling of current processes and exploration of new recovery methods forCritical metal recovery critical metalsCritical metals from waste streams, including by-products from copperCopper, lead, and zinc production, as well as electronic wasteElectronic waste. This integration enables reasonable calculations of how critical metalsMetal distribute across different phases (metal, slag, and gas), helping to identify optimal conditions, like composition, temperature, and oxygen levels, within the complex parameter space of multi-component systems. This work summarizes the challenges, advancements, and findings achieved so far.