4.6 Article

Graphitic mesoporous carbon-silica composites from low-value sugarcane by-products for the removal of toxic dyes from wastewaters

期刊

ROYAL SOCIETY OPEN SCIENCE
卷 7, 期 9, 页码 -

出版社

ROYAL SOC
DOI: 10.1098/rsos.200438

关键词

waste; adsorption; bio-based; molasses; congo red; remediation

资金

  1. Thailand Research Fund grant for New scholars, Office of the Higher Education Commission
  2. Khon Kaen University [MRG6280199]
  3. Center of Excellence for Innovation in Chemistry (Perch-CIC)
  4. Newton Mobility Grant (Royal Society)
  5. OHEC, Thailand [NI150336]

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Highly porous carbon-silica composites (CSC) were prepared for the first time through a simple wet impregnation process and subsequent pyrolysis of low-value sugarcane by-products, namely molasses. These CSC materials demonstrate a distinct range of functionalities, which significantly differ from similar materials published in the literature. Importantly, the carbon-silica composites prepared at 800 degrees C exhibited exceptional adsorption capacities for the azo-dye congo red (445 mg g(-1)), due to the graphitic carbon coating and unique functionality including C-O-C within the porous structure. Congo red adsorption capacity of the highly mesoporous graphitic carbon-silica composites significantly exceeds that of commercial activated carbon and silica, these carbon-silica composites therefore represent an effective step towards the development of porous bio-derived adsorbent for remediation of dye wastewaters. Both the porous properties (surface area and pore size distribution) and the functionality of the carbon coating were dependent on the temperature of preparation. The sustainable synthetic methods employed led to a versatile material that inherited the mesoporosity characteristics from the parent silica, demonstrating mesoporous volumes greater than 90% (as calculated from the total pore volume). Adsorption on the 800 degrees C prepared carbon-silica composites demonstrated an excellent fit with the Langmuir isotherm and the pseudo-first-order kinetic model.

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