dc.contributor.author | Bakari, Ramadhani | |
dc.contributor.author | Kivevele, Thomas | |
dc.contributor.author | Huang, Xiao | |
dc.contributor.author | Jande, Yusufu | |
dc.date.accessioned | 2021-06-14T10:09:55Z | |
dc.date.available | 2021-06-14T10:09:55Z | |
dc.date.issued | 2021-05-18 | |
dc.identifier.uri | https://doi.org/10.1021/acsomega.0c06318 | |
dc.identifier.uri | https://dspace.nm-aist.ac.tz/handle/20.500.12479/1242 | |
dc.description | This research article published by ACS Publications, 2021 | en_US |
dc.description.abstract | In this study, rice husk biomass was gasified under sub- and supercritical water conditions in an autoclave reactor. The effect of temperature (350-500 °C), residence time (30-120 min), and feed concentration (3-10 wt %) was experimentally studied using the response surface methodology in relation to the yield of gasification products. The quadratic models have been suggested for both responses. Based on the models, the quantitative relationship between various operational conditions and the responses will reliably forecast the experimental outcomes. The findings revealed that higher temperatures, longer residence times, and lower feed concentrations favored high gas yields. The lowest tar yield obtained was 2.98 wt %, while the highest gasification efficiency and gas volume attained were 64.27% and 423 mL/g, respectively. The ANOVA test showed that the order of the effects of the factors on all responses except gravimetric tar yield follows temperature > feed concentration > residence time. The gravimetric tar yield followed a different trend: temperature > residence time > feed concentration. The results revealed that SCW gasification could provide an effective mechanism for transforming the energy content of RH into a substantial fuel product. | en_US |
dc.language.iso | en | en_US |
dc.publisher | ACS Publications | en_US |
dc.subject | Research Subject Categories::SOCIAL SCIENCES | en_US |
dc.title | Sub- and Supercritical Water Gasification of Rice Husk: Parametric Optimization Using the I-Optimality Criterion. | en_US |
dc.type | Article | en_US |