Cross-field-enhanced photocatalysis couples light, electric polarization, magnetic bias, and mechanical perturbation to amplify charge separation and interfacial redox for environmental remediation and energy conversion. However, the discovery of multi-field-responsive, high-efficiency photocatalysts is hampered by s...
This review provides a molecular-level perspective on AI-MD-enabled water treatment, linking interfacial structure, transport behavior, and reactive mechanisms to predictive and automated material design and can support the development of more efficient and environmentally sustainable water-treatment technologies.
Jia Yan, Di Wu, Yixuan Cai et al.· Environmental Research· 0 citations
It is shown that explainable artificial intelligence (XAI) provides a transformative approach by connecting model predictions to interpreting chemical descriptors, structural motifs, and reaction features, and it is reshaping data-driven catalysis from opaque prediction toward mechanism-informed catalyst design.
Zixuan Geng, Di Wu, Xu Zhao et al.· Academia Catalysis· 0 citations
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