Extraction of Phenolic Compounds from the Pulp of Myrciaria dubia Using Eco-Friendly Solvents: Extraction Kinetics and Determination of Mass Transfer and Thermodynamic Parameters
Abstract Sustainable extraction of bioactive compounds from Amazonian fruits is essential for green chemistry, but integrated kinetic, thermodynamic, economic, and sustainability assessments for Myrciaria dubia (camu–camu) phenolics remain limited. This study investigated phenolic extraction from camu–camu pulp using natural deep eutectic solvents (NADES) composed of choline chloride and acetic acid, either pure or in binary mixtures with water or ethanol (EtOH), combined with conventional (CE), shear (SE), and ultrasound-assisted extraction (UAE; 420, 490, 560 W). Extraction kinetics, mass transfer parameters, thermodynamics, environmental performance (EcoScale and AGREE metrics), and preliminary economics were evaluated. UAE using NADES + EtOH at 560 W yielded the highest phenolic content (17.11 mg GAE/g). Fick’s diffusion model best described the kinetics (R2 > 0.9523), indicating a diffusion-controlled process, while thermodynamic analysis confirmed an endothermic and spontaneous process. All DES-based systems showed superior environmental performance over CE using 70% (v/v) EtOH, with EcoScale scores of 87.97–92.97 (vs 83.43) and AGREE values of 0.61 (vs 0.52). Preliminary economic assessment indicated extract production costs of US$ 1.83–2.26/kg; NADES-based systems maintained competitive costs while providing higher phenolic content than conventional extraction. Combining NADES + EtOH and UAE represents a promising strategy for enhancing phenolic recovery while maintaining favorable sustainability and economic performance, supporting greener extraction of Amazonian resources.
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Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.