abstract
Natural products can be the basis for the development of green solvents, relevant for the advancement of new, more sustainable processes and products. In this work, 10 binary mixtures constituted by terpenes are prepared and characterized. Their solid-liquid phase diagrams show that room-temperature solvents can be prepared from solid terpenes in a wide composition range. These diagrams are accurately described by the conductor-like screening model for real solvents, showing it to be a useful predictive tool for the design of novel natural solvents. At the eutectic point, these mixtures possess low viscosities, densities lower than water, and high boiling temperatures. The low water solubility in the eutectic solvents together with its negligible impact on the properties measured is a strong indicator of the hydrophobic character of these mixtures. The tunable character of these mixtures is demonstrated by studying the solvatochromic parameters in the entire concentration region, the properties of the final solvents being tuned by simply varying the mole fraction of the terpenes. The high potential of this tunable character is shown in the selective extraction of dyes from their aqueous solutions. This work is expected to devise new insights concerning these solvents as well as to boost their application in green industrial processes.
keywords
SOLUBILITY; BEHAVIOR; BIOMASS; SYSTEMS; MODEL
subject category
Chemistry; Science & Technology - Other Topics; Engineering
authors
Martins, MAR; Silva, LP; Schaeffer, N; Abranches, DO; Maximo, GJ; Pinho, SP; Coutinho, JAP
our authors
Dinis O. Abranches
Assistant Researcher
Liliana Patrocínio da Silva
Collaborator
Nicolas Schaeffer
Assistant ResearcherGroups
G4 - Renewable Materials and Circular Economy
G6 - Virtual Materials and Artificial Intelligence
acknowledgements
This work was developed in the scope of the project CICECO-Aveiro Institute of Materials POCI-01-0145-FEDER-007679 (UID/CTM/50011/2019) and Associate Laboratory LSRE-LCM (UID/EQU/50020/2019), funded by national funds through FCT/MCTES (PIDDAC). FCT is also acknowledged for funding the project DeepBiorefinery (PTDC/AGRTEC/1191/2014). M.A.RM. acknowledges the financial support from NORTE-01-0145-FEDER-000006-funded by NORTE2020 through PT2020 and ERDF. L.P.S. acknowledges FCT for her Ph.D. grant SFRH/BD/135976/2018. G.J.M. acknowledges the national funding agencies CNPq (305870/2014-9, 309780/2014-4, 140702/2017-2, 406918/2016-3, 406963/2016-9), FAPESP (2014/21252-0, 2016/08566-1), and FAEPEX/UNICAMP (0125/16).