Machine learning for CO2 conversion driven by dielectric barrier discharge plasma and Cs2TeCl6 photocatalysts

An effective prediction model was established based on the BPANN to reduce the consumption of experimental resources. The effect of each process parameter on conversion efficiency was also quantified, which could facilitate future experimental design.