@article{marquez_ortiz_barrios_vera_patino-agudelo_vivas_salas_zambrano_theiner_2024, title={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}, volume={5}, ISSN={["1558-9293"]}, url={https://doi.org/10.1002/jsde.12766}, DOI={10.1002/jsde.12766}, abstractNote={Abstract 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.}, journal={JOURNAL OF SURFACTANTS AND DETERGENTS}, author={Marquez, Ronald and Ortiz, Maria S. and Barrios, Nelson and Vera, Ramon E. and Patino-Agudelo, alvaro Javier and Vivas, Keren A. and Salas, Mariangeles and Zambrano, Franklin and Theiner, Eric}, year={2024}, month={May} }
 @article{salem_clayson_salas_haque_rao_agate_singh_levis_mittal_yarbrough_et al._2023, title={A critical review of existing and emerging technologies and systems to optimize solid waste management for feedstocks and energy conversion}, volume={6}, ISSN={2590-2385}, url={http://dx.doi.org/10.1016/j.matt.2023.08.003}, DOI={10.1016/j.matt.2023.08.003}, abstractNote={Solid waste generation and its accumulation is increasing at an alarming pace due to population growth and urbanization posing severe risks to health, safety, and natural ecosystems. This review strategically addresses the challenges and solutions to increasing the sustainability footprint of solid waste management (SWM) systems by revealing multipronged approaches that reduce solid waste and handling costs while generating revenue and reducing greenhouse gas and related emissions. For example, the United States sends ∼150 million tons of waste to landfills, which is composed of over 75% organic and recyclable materials having a potential to be diverted to alternative scenarios. The emergence of an automated upstream and downstream sorting process for solid waste to increase material diversion from landfills is a promising approach for creating sustainable SWM. The utilization of artificial-intelligence-enabled smart and automated systems at the home and industrial scales, comprehensive public re-education including awareness of the adverse effects of landfilled waste on the ecosystem, and more eco-friendly product development are required to significantly reduce landfills and their negative footprint.}, number={10}, journal={Matter}, publisher={Elsevier BV}, author={Salem, Khandoker Samaher and Clayson, Kathryn and Salas, Mariangeles and Haque, Naimul and Rao, Raman and Agate, Sachin and Singh, Anand and Levis, James W. and Mittal, Ashutosh and Yarbrough, John M. and et al.}, year={2023}, month={Oct}, pages={3348–3377} }