玉米秸秆
合成气
生物量(生态学)
超临界流体
产量(工程)
选择性
二氧化碳
甲烷
制浆造纸工业
碳纤维
化学
过程(计算)
超临界二氧化碳
反应性(心理学)
中心组合设计
工作(物理)
制氢
氢
实验设计
环境科学
材料科学
化学工程
工艺工程
水煤气变换反应
生物能源
分解
响应面法
作者
Xu Zhang,Ying Ma,Xinmin Wang,Renwei Li,Jindong Liu
出处
期刊:ACS omega
[American Chemical Society]
日期:2026-06-29
卷期号:11 (27): 40684-40693
标识
DOI:10.1021/acsomega.6c04166
摘要
Supercritical water gasification (SCWG) of biomass to produce hydrogen-rich syngas is a promising technology. However, the high-temperature and high-pressure conditions required for SCWG render the experimental evaluation of gas production performance both time-consuming and costly. Therefore, accurate predictive modeling is essential for determining the optimal process conditions and parameters. In this study, the effects of three process parameters (temperature, biomass concentration, and reaction time) on six performance indicators (gas yield (GY), carbon gasification efficiency (CGE), hydrogen selectivity (HS), methane selectivity (MS), carbon dioxide selectivity (CDS), and solid yield (SY)) were investigated using orthogonal experiments combined with an analysis of variance (ANOVA). A three-factor, three-level Box-Behnken design (BBD) was employed. The results indicated that temperature had a highly significant effect on all six responses, followed by biomass concentration, whereas the reaction time had a negligible effect, with the reaction nearly reaching completion within 15 min. The activation energy for the SCWG of corn stover in the range of 673-873 K was determined to be 88.73 kJ/mol. Predictive models for each response were established, all exhibiting high accuracy with a maximum deviation of only 3.11% between predicted and experimental values.
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