Low-Temperature Hydrothermal Modification with Fe/C Catalysts for Enhancing Corn Stover Anaerobic Digestion Performance and Modeling Development for Predicting Biomethane Yield DOI Open Access
Xitong Wang, Hairong Yuan, Xiujin Li

et al.

Catalysts, Journal Year: 2025, Volume and Issue: 15(4), P. 362 - 362

Published: April 8, 2025

This study investigated the enhancement of corn stover (CS) anaerobic digestion (AD) performance through low-temperature hydrothermal modification (HM) with Fe/C catalysts and developed two predictive models for biomethane yield (BY). CS was modified at 50 °C then anaerobically digested. The results indicated that significantly improved hydrolysis efficiency, by increasing concentrations glucose, mannose, xylose, volatile fatty acids (VFAs), which were 1.9, 1.7, 3.0, 1.8 times higher than those HM alone, respectively. enhanced effectively AD performance, leading to a BY increase 25.5% as compared control group. time reach 90% maximum (T90) also reduced 7 days. Furthermore, GM(1,N) gray system model simulated multi-parameter coupling effects in processes under small-sample conditions (n < 20), demonstrating high accuracy (average percentage deviation [APD] = 4.50%) enabling correlation analysis between parameters BY. ANN-GA exhibited superior prediction. demonstrated effectiveness HM-Fe/C enhancing predicting

Language: Английский

Low-Temperature Hydrothermal Modification with Fe/C Catalysts for Enhancing Corn Stover Anaerobic Digestion Performance and Modeling Development for Predicting Biomethane Yield DOI Open Access
Xitong Wang, Hairong Yuan, Xiujin Li

et al.

Catalysts, Journal Year: 2025, Volume and Issue: 15(4), P. 362 - 362

Published: April 8, 2025

This study investigated the enhancement of corn stover (CS) anaerobic digestion (AD) performance through low-temperature hydrothermal modification (HM) with Fe/C catalysts and developed two predictive models for biomethane yield (BY). CS was modified at 50 °C then anaerobically digested. The results indicated that significantly improved hydrolysis efficiency, by increasing concentrations glucose, mannose, xylose, volatile fatty acids (VFAs), which were 1.9, 1.7, 3.0, 1.8 times higher than those HM alone, respectively. enhanced effectively AD performance, leading to a BY increase 25.5% as compared control group. time reach 90% maximum (T90) also reduced 7 days. Furthermore, GM(1,N) gray system model simulated multi-parameter coupling effects in processes under small-sample conditions (n < 20), demonstrating high accuracy (average percentage deviation [APD] = 4.50%) enabling correlation analysis between parameters BY. ANN-GA exhibited superior prediction. demonstrated effectiveness HM-Fe/C enhancing predicting

Language: Английский

Citations

0