Issue 32, 2026, Issue in Progress

Study on the gasification characteristics of wool in supercritical water for hydrogen production

Abstract

Waste wool, a protein-based waste from textile and livestock industries, represents a promising yet underexplored feedstock for clean hydrogen production. In supercritical water, its keratin structure undergoes rapid hydrolysis and depolymerization, enabling efficient conversion into hydrogen-rich gas with minimal char formation. In this study, a systematic investigation of wool SCWG was conducted by evaluating the effects of temperature, feedstock concentration, residence time, and catalyst addition. Compared with conventional biomass feedstocks, the unique protein structure of wool leads to distinct gasification behavior and high hydrogen production potential. Higher temperature, lower feedstock concentration, and moderately long residence time significantly enhance carbon conversion and gas yield. Under optimal conditions (600 °C, 2 wt% feedstock concentration, and 5 min residence time), carbon conversion efficiency reached 95.71%, hydrogen efficiency reached 119.26%, and gas yield reached 42.72 mol kg−1. Furthermore, the addition of Cu-3% Al2O3 catalyst significantly improves hydrogen production and gasification efficiency, highlighting the synergistic role of catalytic effects and feedstock characteristics. These findings provide new insights into the gasification behavior of protein-rich biomass and demonstrate that supercritical water gasification is a promising and efficient pathway for converting waste wool into clean hydrogen energy.

Graphical abstract: Study on the gasification characteristics of wool in supercritical water for hydrogen production

Article information

Article type
Paper
Submitted
12 Apr 2026
Accepted
26 May 2026
First published
01 Jun 2026
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2026,16, 29515-29528

Study on the gasification characteristics of wool in supercritical water for hydrogen production

W. Deng, Y. Chao, Q. Li, B. Chen, Z. Liu, H. Chen, L. Yi and C. Liu, RSC Adv., 2026, 16, 29515 DOI: 10.1039/D6RA03076A

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