High-throughput screening of high-activity oxygen carriers for chemical looping argon purification via a machine learning – density functional theory method†

IF 5 3区 材料科学 Q2 CHEMISTRY, PHYSICAL Sustainable Energy & Fuels Pub Date : 2025-02-18 DOI:10.1039/D4SE01575D
Shenglong Teng, Yiwen Song, Yu Qiu, Xinyu Li, Yixia Hong, Jian Zuo, Dewang Zeng and Kai Xu
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Abstract

Argon, a protective gas, is susceptible to contamination by impurity gases in the production of monocrystalline silicon for solar cells. Chemical looping combustion (CLC) technology offers a solution for argon recycling by leveraging the cyclic conversion of oxygen carriers. However, the desorption of low-concentration impurity gases requires high-activity oxygen carriers, and current screening methods primarily rely on experimental trial and error, which is time-consuming and labor-intensive. Herein, we propose machine learning-assisted Density Functional Theory (DFT) for high-throughput screening of oxygen carriers. Quaternary iron-based spinel oxygen carriers A1xA21−xByFe2−y were used as the object of study. DFT calculations were conducted on 756 oxygen carriers, while the remaining 3619 were predicted through machine learning, achieving a prediction accuracy R2 of 0.87. Based on these predictions and a three-step screening criterion of synthesizability, thermodynamic stability, and reactivity, Cu0.875Ni0.125Al0.5Fe1.5O4 exhibited the highest reactivity and its desorption of impurity gases is 6 times higher than that of fresh Fe2O3. In the stability test, Cu0.875Ni0.125Al0.5Fe1.5O4 maintained 96% CO removal efficiency after 10 cycles, facilitating the cyclic purification of crude argon. This study provides new guidance for the design and discovery of high-activity materials through high-throughput screening.

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Sustainable Energy & Fuels
Sustainable Energy & Fuels Energy-Energy Engineering and Power Technology
CiteScore
10.00
自引率
3.60%
发文量
394
期刊介绍: Sustainable Energy & Fuels will publish research that contributes to the development of sustainable energy technologies with a particular emphasis on new and next-generation technologies.
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Back cover Back cover High-throughput screening of high-activity oxygen carriers for chemical looping argon purification via a machine learning – density functional theory method† Correction: Photocatalytic CO2 reduction to methanol integrated with the oxidative coupling of thiols for S–X (X = S, C) bond formation over an Fe3O4/BiVO4 composite Amorphous cobalt–copper oxide for upgrading anodic electro-oxidation of glycerol to formate in a basic medium†
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