Supercritical fluid technology as a sustainable alternative method for textile dyeing: An approach on waste, energy, and CO2 emission reduction

Green dyeing of cellulose diacetate fabric with disperse dyes in a liquid paraffin medium

The conventional method of dyeing cellulose diacetate (CDA) fabric with disperse dyes consumes significant amounts of fresh water and dispersants, contributing to environmental pollution and health hazards. This study explored the use of liquid paraffin as an alternative to aqueous mediums for dyeing CDA fabric with Disperse Blue 56 dyes, eliminating the need for dispersants. An L16 orthogonal array was used to optimize dyeing conditions based on the color strength values. The fabric properties were evaluated through several techniques. These include tensile strength, colorfastness to washing and rubbing, Fourier-transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy, and X-ray diffraction. These findings highlight that the textile industry can adopt a practical and environmentally friendly technique for dyeing CDA fabric, leading to a significant reduction in pollution.

Technological trajectories in circular economy: Bridging patent analytics with sustainable development goals

This study examines key technologies in the circular economy through patent mining and expert evaluations. We identified eleven distinct technology clusters, including Smart Fluid Management Systems, Circular Chemical Processing, and Structural Design for Circularity. Using the S-curve model, we analyzed the maturity stages of these technologies, revealing a mix of mature and emerging technologies. For example, Energy Storage and Electrical Systems have reached maturity, while Circular Chemical Processing and Waste Treatment are still in the growth phase. These findings highlight the varying levels of technological development and the potential for targeted research and investment. To assess sustainability, we used the TOPSIS method, which ranks technologies based on their alignment with the Sustainable Development Goals (SDGs). Our results indicate that Circular Chemical Processing, Thermal Management, and Structural Design for Circularity are key areas for innovation, offering significant potential to contribute to global sustainability goals. The study emphasizes the need for integrated solutions, suggesting that technological progress will be driven by synergies between different technology clusters. It calls for cross-sector collaboration to maximize the impact of these technologies. By combining insights on technological maturity and sustainability alignment, this research provides a strategic roadmap for advancing circular economy practices. It offers guidance for industry stakeholders and policymakers on prioritizing investments in technologies that support long-term sustainability and resource efficiency. In conclusion, this study provides a comprehensive framework for understanding and advancing circular economy technologies, offering valuable insights for accelerating the transition toward a sustainable, circular economy.

Machine Learning-Based Process Optimization in Biopolymer Manufacturing: A Review

The integration of machine learning (ML) into material manufacturing has driven advancements in optimizing biopolymer production processes. ML techniques, applied across various stages of biopolymer production, enable the analysis of complex data generated throughout production, identifying patterns and insights not easily observed through traditional methods. As sustainable alternatives to petrochemical-based plastics, biopolymers present unique challenges due to their reliance on variable bio-based feedstocks and complex processing conditions. This review systematically summarizes the current applications of ML techniques in biopolymer production, aiming to provide a comprehensive reference for future research while highlighting the potential of ML to enhance efficiency, reduce costs, and improve product quality. This review also shows the role of ML algorithms, including supervised, unsupervised, and deep learning algorithms, in optimizing biopolymer manufacturing processes.

Supercritical Technology as an Efficient Alternative to Cold Pressing for Avocado Oil: A Comparative Approach

Avocado oil is rich in nutrients beneficial to human health, such as monounsaturated fatty acids, phenolic compounds, tocopherol, and carotenoids, with numerous possibilities for application in industry. This review explores, through a comparative approach, the effectiveness of the supercritical oil extraction process as an alternative to the conventional cold-pressing method, evaluating the differences in the extraction process steps through the effect of temperature and operating pressure on bioactive quality and oil yield. The results reveal that supercritical avocado oil has a yield like that of mechanical cold pressing and superior functional and bioactive quality, especially in relation to α-tocopherol and carotenoids. For better use and efficiency of the supercritical technology, the maturation stage, moisture content, fruit variety, and collection period stand out as essential factors to be observed during pre-treatment, as they directly impact oil yield and nutrient concentration. In addition, the use of supercritical technology enables the full use of the fruit, significantly reducing waste, and adds value to the agro-industrial residues of the process. It produces an edible oil free of impurities, microorganisms, and organic solvents. It is a green, environmentally friendly technology with long-term environmental and economic advantages and an interesting alternative in the avocado market.

Supercritical Impregnation of PETG with Olea europaea Leaf Extract: Influence of Operational Parameters on Expansion Degree, Antioxidant and Mechanical Properties

PETG (poly(ethylene glycol-co-cyclohexane-1,4-dimethanol terephthalate)) is an amorphous copolymer, biocompatible, recyclable, and versatile. Nowadays, it is being actively researched for biomedical applications. However, proposals of PETG as a platform for the loading of bioactive compounds from natural extract are scarce, as well as the effect of the supercritical impregnation on this polymer. In this work, the supercritical impregnation of PETG filaments with Olea europaea leaf extract was investigated, evaluating the effect of pressure (100-400 bar), temperature (35-55 °C), and depressurization rate (5-50 bar min-1) on the expansion degree, antioxidant activity, and mechanical properties of the resulting filaments. PETG expansion degree ranged from ~3 to 120%, with antioxidant loading ranging from 2.28 to 17.96 g per 100 g of polymer, corresponding to oxidation inhibition values of 7.65 and 66.55%, respectively. The temperature and the binary interaction between pressure and depressurization rate most affected these properties. The mechanical properties of PETG filaments depended greatly on process variables. Tensile strength values were similar or lower than the untreated filaments. Young's modulus and elongation at break values decreased below ~1000 MPa and ~10%, respectively, after the scCO2 treatment and impregnation. The extent of this decrease depended on the supercritical operational parameters. Therefore, filaments with higher antioxidant activity and different expansion degrees and mechanical properties were obtained by adjusting the supercritical processing conditions.

Improving and measuring the solubility of favipiravir and montelukast in SC-CO2 with ethanol projecting their nanonization

Supercritical carbon dioxide (SC-CO2)-based approaches have become more popular in recent years as alternative methods for creating micro- or nanosized medicines. Particularly, high drug solubility is required in those techniques using SC-CO2 as a solvent. During the most recent pandemic years, favipiravir and montelukast were two of the most often prescribed medications for the treatment of COVID-19. In this study, ethanol at 1 and 3 mol% was utilized as a cosolvent to increase the solubility of both medicines in SC-CO2 by a static approach using a range of temperatures (308 to 338 K) and pressure (12 to 30 MPa) values. The experimentally determined solubilities of favipiravir and montelukast in SC-CO2 + 3 mol% ethanol showed solubility values up to 33.3 and 24.5 times higher than that obtained for these drugs with only SC-CO2. The highest values were achieved in the pressure of 12 MPa and temperature of 338 K. Last but not least, six density-based semi-empirical models with various adjustable parameters were used to perform the modeling of the solubility of favipiravir and montelukast.