Empirical modeling, experimental optimization, and artificial intelligence (ANN-GA) as a tool for the efficient dye remediation by the biosilica extracted from sugarcane bagasse ash
Author:
Publisher
Springer Science and Business Media LLC
Subject
Renewable Energy, Sustainability and the Environment
Link
https://link.springer.com/content/pdf/10.1007/s13399-023-04825-2.pdf
Reference57 articles.
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2. Siqueira MU, Contin B, Fernandes PRB et al (2022) Brazilian agro-industrial wastes as potential textile and other raw materials: a sustainable approach. Mater Circ Econ 4:9. https://doi.org/10.1007/s42824-021-00050-2
3. Costa JAS, Paranhos CM (2020) Mitigation of silica-rich wastes: an alternative to the synthesis eco-friendly silica-based mesoporous materials. Microporous Mesoporous Mater 309:110570. https://doi.org/10.1016/j.micromeso.2020.110570
4. Rovani S, Santos JJ, Corio P, Fungaro DA (2018) Highly pure silica nanoparticles with high adsorption capacity obtained from sugarcane waste ash. ACS Omega 3:2618–2627. https://doi.org/10.1021/acsomega.8b00092
5. Santana Costa JA, Paranhos CM (2018) Systematic evaluation of amorphous silica production from rice husk ashes. J Clean Prod 192:688–697. https://doi.org/10.1016/j.jclepro.2018.05.028
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