Deep Eutectic Solvents: Properties and Applications in CO2 Separation

Star anise (Illicium verum Hook. F.) polysaccharides: Potential therapeutic management for obesity, hypertension, and diabetes

This study explores the extraction of polysaccharides from star anise (Illicium verum Hook. f.) with its anti-obesity, antihypertensive, antidiabetic, and antioxidant properties. The aim is to optimize the extraction conditions of star anise polysaccharides (SAP) utilizing propane alcohols-based deep eutectic solvents and microwave-assisted methods. The optimized conditions resulted in an extraction yield of 5.14%. The characteristics of acidic pectin-like SAP, including high viscosity (44.86 mPa s), high oil-holding capacity (14.39%), a high degree of esterification (72.53%), gel-like properties, highly amorphous, a high galacturonic acid concentration, and a highly branching size polysaccharide structure, significantly contribute to their potent inhibition of pancreatic lipase (86.67%), angiotensin-converting enzyme (73.47%), and α-glucosidase (82.33%) activities as well as to their antioxidant properties of azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS, 34.94%) and ferric ion reducing antioxidant power (FRAP, 0.56 mM FeSO4). Therefore, SAP could be used as a potential therapeutic agent for obesity, hypertension, and diabetes mellitus management.

Greenhouse gases capture applying impregnated silica with ionic liquids, deep eutectic solvents, and natural deep eutectic solvents

The development of technologies to capture greenhouse gases (GHGs) like carbon dioxide (CO2) and nitrous oxide (N2O) is vital for climate change mitigation. Ionic liquids (ILs), deep eutectic solvents (DES), and natural deep eutectic solvents (NADES) are promising absorbents to abate GHGs emissions. However, their high viscosity limits the gas-liquid contact, as consequence of the mass transfer. To overcome this, their impregnation onto porous silica gel has been carried out, increasing the gas-liquid contact area. The present study analyzes the effect of size particle of silica gel impregnated with ILs, DES, and NADES over the CO2 and N2O capture at atmospheric conditions. The degree of impregnation of silica particles was determined by thermogravimetric analysis (TGA). The identification of functional groups present on the surface of silica, ILs, DES, and NADES was performed using Fourier-transform infrared spectroscopy (FTIR), and their crystalline structure was determined by X-ray diffraction (XRD). The partition coefficient of CO2 and N2O between gas and ILs, DES, and NADES was determined by a static headspace method. Results show that the degree of solvent impregnation on silica gel ranged from 36.8 to 43.0% w/w, the partition coefficient of CO2 in the impregnated silica varied from 0.005 to 0.067, and for N2O, from 0.005 to 0.032. This suggests that impregnated particles have a greater affinity for N2O compared to CO2. Using impregnated particles requires only 40% of the bulk solvent to achieve a similar GHG capture capacity compared to using bulk solvents.

Natural Deep Eutectic Solvents as Rust Removal Agents from Lithic and Cellulosic Substrates

The peculiar physicochemical features of deep eutectic solvents (DESs), in particular their tunability, make them ideal media for various applications. Despite their ability to solubilize metal oxides, their use as rust removers from valuable substrates has not yet been thoroughly investigated. In this study, we chose three known DESs, consisting of choline chloride and acetic, oxalic or citric acid for evaluating their ability to remove corrosion products from a cellulose-based material as linen fabric and two different lithotypes, as travertine and granite. The artificial staining was achieved by placing a rusty iron grid on their surfaces. The DESs were applied by means of cellulose poultice on the linen fabrics, while on the rusted stone surfaces with a cotton swab. Macro- and microscopic observations, colorimetry and SEM/EDS analysis were employed to ascertain the cleaning effectiveness and the absence of side effects on the samples after treatment. Oxalic acid-based DES was capable of removing rust stains from both stone and cellulose-based samples, while choline chloride/citric acid DES was effective only on stone specimens. The results suggest a new practical application of DESs for the elimination of rust from lithic and cellulosic substrates of precious and artistic value.

Novel hybrid QSPR-GPR approach for modeling of carbon dioxide capture using deep eutectic solvents

In recent years, deep eutectic solvents (DESs) have garnered considerable attention for their potential in carbon capture and utilization processes. Predicting the carbon dioxide (CO2) solubility in DES is crucial for optimizing these solvent systems and advancing their application in sustainable technologies. In this study, we presented an evolving hybrid Quantitative Structure-Property Relationship and Gaussian Process Regression (QSPR-GPR) model that enables accurate predictions of CO2 solubility in various DESs. The QSPR-GPR model combined the strengths of both approaches, leveraging molecular descriptors and structural features of DES components to establish a robust and adaptable predictive framework. Through a systematic evolution process, we iteratively refined the model, enhancing its performance and generalization capacity. By incorporating experimental CO2 solubility data in varied DES compositions and temperatures, we trained the model to capture the intricate solubility behaviour precisely. The analytical capability of the evolving hybrid model was validated against an extensive dataset of experimental CO2 solubility values, demonstrating its superiority over individual QSPR and GPR models. The model achieves high accuracy, capturing the complex interactions between CO2 and DES components under varying thermodynamic conditions. The versatility of the evolving hybrid model was highlighted by its ability to accommodate new experimental data and adapt to different DES compositions and temperatures. The proposed QSPR-GPR model presented a powerful tool for predicting CO2 solubility in DES, providing valuable insights for designing and optimizing solvent systems in carbon capture technologies. The model's remarkable performance enhances our understanding of CO2 solubility mechanisms and contributes to sustainable solutions for mitigating greenhouse gas emissions. As research in DESs progresses, the evolving hybrid QSPR-GPR model offers a versatile and accurate means for predicting CO2 solubility, supporting advancements in carbon capture and utilization processes towards a greener and more sustainable future.