2022
DOI: 10.1021/acsmaterialslett.2c00734
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Tuning OER Electrocatalysts toward LOM Pathway through the Lens of Multi-Descriptor Feature Selection by Artificial Intelligence-Based Approach

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Cited by 17 publications
(8 citation statements)
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“…First, theoretical approaches based on the volcano-scaling relation can help prioritize highly active atoms, structural phases, and compositions. It is noteworthy that recent advancements have introduced artificial-intelligence-based theoretical prediction for catalyst design. As mentioned above, the predicted OER activity can be further improved by departing from the constraints of the volcano-scaling relationship through the implementation of various design strategies. Furthermore, to provide informative insights into the effectiveness of the design strategy, we have compiled a list of the most active Ir- and Ru-based acidic OER catalysts and their corresponding electrocatalytic parameters, as shown in Table .…”
Section: Summary and Perspectivesmentioning
confidence: 99%
“…First, theoretical approaches based on the volcano-scaling relation can help prioritize highly active atoms, structural phases, and compositions. It is noteworthy that recent advancements have introduced artificial-intelligence-based theoretical prediction for catalyst design. As mentioned above, the predicted OER activity can be further improved by departing from the constraints of the volcano-scaling relationship through the implementation of various design strategies. Furthermore, to provide informative insights into the effectiveness of the design strategy, we have compiled a list of the most active Ir- and Ru-based acidic OER catalysts and their corresponding electrocatalytic parameters, as shown in Table .…”
Section: Summary and Perspectivesmentioning
confidence: 99%
“…be screened out accurately, which is expected to increase the efficiency of material design. [172][173][174] Unfortunately, there is still a lack of application of AI or ML in screening doped spinel oxides for acidic OER.…”
Section: Elemental Dopingmentioning
confidence: 99%
“…With the development of artificial intelligence (AI) and machine learning (ML) techniques, the possible efficient spinel oxides–based acidic OER performance with different dopants can be screened out accurately, which is expected to increase the efficiency of material design. [ 172–174 ] Unfortunately, there is still a lack of application of AI or ML in screening doped spinel oxides for acidic OER.…”
Section: Optimization Strategies For Spinel Oxidesmentioning
confidence: 99%
“…This way and with the aid of artificial intelligence systems, through screening and theoretical studies of different kinds of electrocatalysts as well as with fine‐tuning the redox electrochemistry and surface properties of nanomaterials, engineering of LOM‐based electrocatalysts can be achieved. [ 32 ] Regarding the surface properties and according to a recent review, the role of defects was highlighted, aiding in the adsorption or even formation of intermediates of a mechanism, and since it plays significant part in overall efficiency, strategies that introduce defects should be followed. [ 33 ] Moreover, it has been proved that neutral or semi‐neutral conditions could be to some avail, as there is a chance to diminish both corrosion and instability issues due to harsh acidic or alkaline environment as well as, in the context of practical applications, eliminate the use of membrane separators, eventually lowering the overall operational cost.…”
Section: Overviewmentioning
confidence: 99%