Magnetic biobased rigid foam as a potential adsorbent to remove herbicides from contaminated waters

Autor(es)

Moreira, Wardleison M. ; Moreira, Paula V. Viotti ; da Costa, Talles B. ; Gimenes, Marcelino L. ; Vieira, Melissa G. A.

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF WATER PROCESS ENGINEERING; v. 54, p. 19-pg., 2023-07-01.

Resumo

The present work addresses the development of iron-functionalized rigid carbon foam as an alternative adsorbent for removing herbicides from water bodies. Rigid foams were developed from tannin and starch as monomers and carbon sources for the subsequent carbonization process. In the polymerization reaction, the usual crosslinkers were replaced by glycerol and citric acid to reduce the cost of the process and the level of toxicity of the material. Functionalization of rigid carbon foam with iron improved herbicide adsorption, with an optimum impregnation content of 8 % (Fe3+/rigid carbon foam). The experimental results on the uptake capacity of the different herbicides followed the order of affinity: Atrazine > Diuron >2,4-D. The uptake capacity presented by the Langmuir model was 87.686, 36.166, and 5.107 mg g-1 for Atrazine, Diuron, and 2,4-D, respectively. Additionally, Density Functional Theory (DFT) was used to optimize the herbicides bond lengths and perform vibrational analyzes and stability calculations to verify stability and structure with minimum local energy. Thus, the DFT explains the potential effects of steric hindrance on the adsorption of herbicides on Fe@CF, based on the molecular dimensions and shapes of the herbicides. The DFT showed that the higher uptake capacity of Atrazine can be assigned to the higher molecular chemical reactivity and lower steric hindrance effects. Overall, this study provides important insights into the potential application of iron-functionalized rigid carbon foam as an adsorbent to remove emerging pollutants from wastewater. (AU)

• Processo FAPESP: 20/16004-9 - Desenvolvimento de bioadsorventes avançados e modelos baseados em inteligência artificial para aplicação na remoção e monitoramento de poluentes emergentes em meios aquosos
• Beneficiário: Meuris Gurgel Carlos da Silva
• Modalidade de apoio: Auxílio à Pesquisa - Regular