Modeling and experimental optimization in the evaluation of chemical interactions of chitosan/polyvinylpyrrolidone mixtures

• Autor(a) principal: Wanderley, Keilly Grangeiro
• Data de Publicação: 2022
• Outros Autores: Santos, Bruna Giovanna Barbosa dos, Santos, Kleilton Oliveira, Sousa, Wladymyr Jefferson Bacalhau de, Assis Júnior, Pedro Carlos de, Cardoso, Márcio José Batista, Fook, Marcus Vinícius Lia
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• DOI: 10.33448/rsd-v11i5.28063
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/28063
• topic: Quitosano; Polivinilpirrolidona; Interacciones químicas; Mejoramiento; Mezclas.; Chitosan; Polyvinylpyrrolidone; Chemical interactions; Optimization; Mixtures.; Quitosana; Polivinilpirrolidona; Interações químicas; Otimização; Misturas.

Polymeric biomaterials stand out due to their great flexibility in adapting their physical, chemical, mechanical, biological properties, processability and the possibility of using them in different situations. Among the various polymers, chitosan and polyvinylpyrrolidone are promising for the development of dressings, however, they have limitations of properties individually that can be optimized when combined. Therefore, this research seeks to evaluate the chemical interactions of PVP/Chitosan mixtures at different concentrations and mass proportions, through modeling and experimental optimization applying the response surface methodology (MSR) from spectroscopy in the Fourier Transform Infrared Spectroscopy (FTIR) of pure polymers. From the FTIR spectra of the pure polymers, the characteristic functional groups of both polymers were observed, which are consistent with the literature. Through the applied linear model, the chemical interactions between chitosan and PVP K — 90 in the different proportions and concentrations of the polymers were determined, and using the MSR with a central composite model, the behavior of the interaction in the mixture was verified for the different conditions and how the proportion of mass in the mixture and the concentration influences. In view of the study, it is observed that the simulation of chemical interaction of the polymeric mixture considering the linear model and using the central composite model of response surface methodology was satisfactory. Experimental optimization from modeling is promising for understanding the behavior of the mixture, helping to develop combinations and predictions of interactions, as well as enabling an improvement in practical experiments.