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Powder‐based heterojunction photocatalysts suffer from aggregation, difficult recovery, and secondary pollution, limiting their practical applications in water remediation. Here, we develop a photothermal‐modulated electrohydrodynamic jet printing (PME‐Jet) strategy assisted by an artificial lemming algorithm‐optimized neural network (ALA‐ANN) for fabricating flexible and recyclable g‑C 3 N 4 /BiOI heterojunction photocatalytic devices on silanized quartz fiber fabrics. The coupled laser‐electric fields generate a transient thermal environment that accelerates droplet evaporation, suppresses nanoparticle aggregation, and enables uniform catalyst assembly without damaging the heterointerface. The ALA‐ANN model achieves 95% prediction accuracy for printed linewidth and reduces optimization time by ∼35%. The fabricated devices exhibit enhanced visible‐light photocatalytic degradation of Rhodamine B, Acid Fuchsin, Methylene Blue, and Congo Red, with reaction rates up to 20‐fold higher than pristine g‑C 3 N 4 and BiOI. Strong interfacial adhesion, flexibility, and recyclability effectively minimize catalyst loss and secondary pollution. Combined catalyst‐retention, residual‐solid, Inductively Coupled Plasma Mass Spectrometry, ecotoxicity, and Total Organic Carbon analyses indicate reduced catalyst‐release risk and favorable environmental compatibility under the investigated conditions. This work provides an intelligent manufacturing strategy for sustainable, flexible photocatalytic systems in water purification.
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Li et al. (2026) studied this question.
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