Surfactants produced from carbohydrate derivatives: Part 2. A review on the value chain, synthesis, and the potential role of artificial intelligence within the biorefinery concept

Autor(es)

Marquez, Ronald ; Ortiz, Maria S. ; Barrios, Nelson ; Vera, Ramon E. ; Patino-Agudelo, alvaro Javier ; Vivas, Keren A. ; Salas, Mariangeles ; Zambrano, Franklin ; Theiner, Eric

• Tipo de documento: Artigo Científico
• Fonte: JOURNAL OF SURFACTANTS AND DETERGENTS; v. N/A, p. 52-pg., 2024-05-21.

Resumo

This comprehensive and critical review explores the synthesis and applications of carbohydrate-based surfactants within the biorefinery concept, focusing on biobased sugar-head molecules suitable for use across several manufacturing sectors, including cosmetics, pharmaceuticals, household products, detergents, and foods. The main focus relies on sustainable alternatives to conventional surfactants, which could reduce the final manufacturing carbon footprint of several industrial feedstocks and products. A thorough analysis of raw materials, highlighting the significance of feedstock sources, and the current biobased surfactants and rhamnolipid biosurfactants production trends, is presented. Key organic reactions for the production of sorbitan esters, sucrose esters, alkyl polyglycosides, and fatty acid glucamines, such as glycosidation, acylation, and etherification, as well as the production of rhamnolipids through fermentation are described. Given the scarce literature on the characterization of these surfactant types within the hydrophilic-lipophilic deviation (HLD) framework, the surfactant contribution parameter (SCP) in the HLD equation for sugar-head surfactants is critically assessed. The economic landscape is also discussed, noting the significant growth in the biobased surfactants and biosurfactant market, driven by environmental awareness and regulatory changes, with projections indicating a substantial market increase in the forthcoming years. Finally, the promising potential of generative artificial intelligence (AI) in developing customized surfactant molecules, with optimized properties for targeted applications, is emphasized as a promising avenue for future research. Potential application of AI in surfactants structure prediction. image (AU)

• Processo FAPESP: 23/11091-9 - Modelagem termodinâmica da formação de micelas gigantes
• Beneficiário: Álvaro Javier Patiño Agudelo
• Modalidade de apoio: Bolsas no Brasil - Programa Fixação de Jovens Doutores