Prediction of Cr6+ removal on the biosorbent from pine cone residue with machine learning simulations

Autor(es)

Bento, Joaquim G. G. S. ; Senra, Luidy F. ; Maia, Lana S. ; Almeida, Luana Souza ; Ferreira, Lucas M. ; Faria, Maria Ismenia S. T. ; Rosa, Derval S. ; Mulinari, Daniella R.

• Tipo de documento: Artigo Científico
• Fonte: SURFACES AND INTERFACES; v. 65, p. 14-pg., 2025-04-22.

Resumo

This study investigates the revalorization of pine cone residue as an efficient, low-cost, and eco-friendly biosorbent for the removal of hexavalent chromium (Cry*) from aqueous solutions. The material was characterized using techniques, including Brunauer-Emmett-Teller (BET) analysis, Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy (ATR-FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy (SEM). The adsorption conditions were optimized through experimental design, focusing on the effects of contact time, initial solution concentration, and pH. Furthermore, three machine learning models-multiple linear regression, decision tree regression, and random forest regression-were employed to predict the efficiency of Cry* removal. The optimized conditions resulted in a maximum removal efficiency of 90.84 % within a short contact time. Among the models tested, the decision tree regression achieved the highest predictive accuracy, with a correlation coefficient (R2) of 0.978. These findings underscore the potential of machine learning in modeling adsorption processes and highlight the importance of biosorbents in sustainable water treatment and revalorization of agricultural waste. (AU)

• Processo FAPESP: 23/14598-7 - Desenvolvimento de aerogéis contendo microfibras de celulose e argila para remoção de íons metálicos presentes em águas contaminadas
• Beneficiário: Lana Siqueira Maia
• Modalidade de apoio: Bolsas no Brasil - Doutorado Direto
• Processo FAPESP: 20/13703-3 - Materiais porosos ecológicos para a recuperação e reavaliação de metais recuperados de água contaminada
• Beneficiário: Derval dos Santos Rosa
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 21/14714-1 - EMU concedido no processo 2020/13703-3 (projeto temático): Cromatógrafo de Íons Modular 940 Professional IC Vario
• Beneficiário: Derval dos Santos Rosa
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários