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

Abstract

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.