Principal component analysis and response surface methodology: optimization for H2 evolution from water catalyzed adopting V–Bi under visible light. (September 2022)

• Record Type: Journal Article
• Authors: Zhao, X.; Zhang, Y.; Zhao, H.; Akanyange, S.N.; Liu, Q.; Zhang, Y.; Lyu, X.; Crittenden, J.; Jing, X.; Qiu, R.; Yang, W.; Xie, H.; Wang, X.
• Is Part Of: Materials today chemistry. Volume 25(2022)
• Publication Date: 2022-09
• Subjects: Photocatalysis -- Water splitting -- Hydrogen production -- Optimization; Chemistry -- Periodicals; Materials -- Research -- Periodicals; Materials science -- Periodicals; Chemistry; Materials -- Research; Electronic journals; Periodicals; 660.282
• DOI: 10.1016/j.mtchem.2022.100920
• Languages: English
• ISSNs: 2468-5194

Abstract

Abstract: Energy generation by photocatalytic water splitting with semiconductors under visible light is an effective method for generating pollution-free energy. In this work, a highly efficient vanadium pentoxide (V2 O5 )-based composite photocatalyst was prepared by hydrothermal calcination. The preparation conditions were optimized using single factor experiments, factor analysis (FA), principal component analysis (PCA), and response surface method (Design Expert). The results showed that the optimal preparation conditions were 6% Bi2 S3 loading, 10 h hydrothermal time, 175.0°C hydrothermal temperature, 4.0 h calcination time, and a calcination temperature of 400.0°C. The results of FA and PCA analysis showed that the hydrothermal temperature, calcination time, and calcination temperature were the three main influencing factors. According to the optimization analysis using the response surface method, the highest hydrogen production rate (590.151 μmol/(g۰h)) was obtained at a hydrothermal temperature of 168.74°C, a calcination time of 3.97 h, and a calcination temperature of 390.15°C. The quantum yield of the catalyst was 27.71%. Highlights: (Bi2 S3 ) promotes the hydrogen production rate of vanadium pentoxide (V2 O5 ). Main influencing factors were screened out by factor analysis (FA) and principal component analysis (PCA). Optimal conditions were obtained through Design Expert optimization.