Electrochemical Engineering for Commodity Metals Extraction

Allanore, Antoine

doi:10.1149/2.f05172if

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…Reaction (5) minimum decomposition voltage is 0.41 V, with actual measurement at 50 A scale of about 5 V (though this has not yet been optimized) [47]. With a cautious estimated faradaic efficiency at 50%, the energy consumption per tonne of Cu is estimated at 4220 kWh, which is comparable with the overall energy consumption in existing smelting [48].…”

Section: Discussion: Towards a Fully Electrified Stepmentioning

confidence: 98%

“…While a full economic evaluation is outside the scope of this paper, the conversion costs of copper in the incumbent smelting-converting-electrorefining route can be used as a benchmark to derive key engineering metrics a new process based on direct electrochemical decomposition must achieve. This method and the corresponding targets are found in a prior work by Allanore [48]. For the conversion costs of an electrolytic process for copper extraction to be on par with the incumbent processes, electricity consumption use must be around 3900 kWh/t.…”

Section: Economic Feasibilitymentioning

confidence: 99%

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Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Daehn

Stinn

Rush

et al. 2022

Metals

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Clean energy infrastructure depends on chalcopyrite: the mineral that contains 70% of the world’s copper reserves, as well as a range of precious and critical metals. Smelting is the only commercially viable route to process chalcopyrite, where the oxygen-rich environment dictates the distribution of impurities and numerous upstream and downstream unit operations to manage noxious gases and by-products. However, unique opportunities to address urgent challenges faced by the copper industry arise by excluding oxygen and processing chalcopyrite in the native sulfide regime. Through electrochemical experiments and thermodynamic analysis, gaseous sulfur and electrochemical reduction in a molten sulfide electrolyte are shown to be effective levers to selectively extract the elements in chalcopyrite for the first time. We present a new process flow to supply the increasing demand for copper and byproduct metals using electricity and an inert anode, while decoupling metal production from fugitive gas emissions and oxidized by-products.

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Section: Discussion: Towards a Fully Electrified Stepmentioning

confidence: 98%

Section: Economic Feasibilitymentioning

confidence: 99%

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Daehn

Stinn

Rush

et al. 2022

Metals

Self Cite

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“…Alternatively, chlorides have high electrical conductivity and are often used as electrolytes in electrowinning and electrorefining. They are disadvantageous insofar as the solubility of oxygen ions is low for oxide electrolysis [13]. On the other hand, the oxide feedstock is highly soluble in the molten oxide, and current density is high due to the high concentration of ions in the electrolyte [14].…”

Section: Introductionmentioning

confidence: 99%

Electrolysis of iron with oxygen gas evolution from molten sodium borate electrolytes

Choi

Kim

et al. 2021

Ironmaking & Steelmaking

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Molten oxide electrolysis can be used to reduce the carbon dioxide emissions from ironmaking. In this paper, we electrochemically decompose iron oxide (Fe 2 O 3 ) into iron (Fe) and oxygen (O 2 ) using boron trioxide and sodium oxide (B 2 O 3 -Na 2 O) as the molten oxide electrolyte at 1000°C that is less than the temperature of other molten oxide electrolysis. The formation of Fe at the cathode and O 2 at the anode is identified by analysing products from both electrodes. The results suggest that the cathodic current efficiency of electrolysis at 2 V is about 54.7%, energy consumption is about 5.27 kW h kg -1 of Fe at 2 V electrolysis, and purity of the reduced Fe was more than 97 mol.%. With respect to the process temperature and product yield, B 2 O 3 -Na 2 O molten oxide has potential as a supporting electrolyte to reduce Fe 2 O 3 to Fe without consuming any carbon.

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“…The T red ML model thus does not capture the underlying thermodynamics correctly and would not predict useful free energies at temperatures other than the oxide reduction temperature. Hence, the T red ML model does not provide reliable predictions of the temperature-dependent reduction free energy and would therefore not be useful for, e.g., the prediction of reduction potentials for high-temperature electrolysis 31 .…”

Section: Introductionmentioning

confidence: 99%

Augmenting zero-Kelvin quantum mechanics with machine learning for the prediction of chemical reactions at high temperatures

et al. 2021

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The prediction of temperature effects from first principles is computationally demanding and typically too approximate for the engineering of high-temperature processes. Here, we introduce a hybrid approach combining zero-Kelvin first-principles calculations with a Gaussian process regression model trained on temperature-dependent reaction free energies. We apply this physics-based machine-learning model to the prediction of metal oxide reduction temperatures in high-temperature smelting processes that are commonly used for the extraction of metals from their ores and from electronics waste and have a significant impact on the global energy economy and greenhouse gas emissions. The hybrid model predicts accurate reduction temperatures of unseen oxides, is computationally efficient, and surpasses in accuracy computationally much more demanding first-principles simulations that explicitly include temperature effects. The approach provides a general paradigm for capturing the temperature dependence of reaction free energies and derived thermodynamic properties when limited experimental reference data is available.

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Electrochemical Engineering for Commodity Metals Extraction

Cited by 14 publications

References 15 publications

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Liquid Copper and Iron Production from Chalcopyrite, in the Absence of Oxygen

Electrolysis of iron with oxygen gas evolution from molten sodium borate electrolytes

Augmenting zero-Kelvin quantum mechanics with machine learning for the prediction of chemical reactions at high temperatures

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