Active photocatalysts for CO2 conversion by severe plastic deformation (SPD)
Saeid Akrami, Tatsumi Ishihara, Masayoshi Fuji, and Kaveh Edalati

TL;DR
This paper reviews recent advances in using severe plastic deformation (SPD) techniques to develop novel photocatalysts with enhanced efficiency for converting CO2 into useful chemicals, addressing global warming concerns.
Contribution
It introduces four main SPD-based strategies for designing active photocatalysts and discusses their impact on improving CO2 photoreduction performance.
Findings
SPD enhances photocatalytic efficiency through defect engineering and phase stabilization.
New high-entropy oxides and oxynitrides show promising activity for CO2 conversion.
SPD-processed catalysts outperform conventional materials in CO2 photoreduction.
Abstract
Excessive CO2 emission from fossil fuel usage has resulted in global warming and environmental crises. To solve this problem, the photocatalytic conversion of CO2 to CO or useful components is a new strategy that has received significant attention. The main challenge in this regard is exploring photocatalysts with high efficiency for CO2 photoreduction. Severe plastic deformation (SPD) through the high-pressure torsion (HPT) process has been effectively used in recent years to develop novel active catalysts for CO2 conversion. These active photocatalysts have been designed based on four main strategies: (i) oxygen vacancy and strain engineering, (ii) stabilization of high-pressure phases, (iii) synthesis of defective high-entropy oxides, and (iv) synthesis of low-bandgap high-entropy oxynitrides. These strategies can enhance the photocatalytic efficiency compared with conventional and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCO2 Reduction Techniques and Catalysts · Carbon dioxide utilization in catalysis · Machine Learning in Materials Science
