Multi-objective optimization (MOO) techniques are crucial in addressing complex engineering problems with conflicting objectives, particularly in pharmaceutical applications. This study focuses on optimizing a biodegradable micro-polymeric carrier system for drug delivery, specifically maximizing the encapsulation efficiency and drug release of Candesartan Cilexetil antihypertensive drug. Achieving a balance between these two goals is essential, as higher encapsulation efficiency ensures adequate drug loading. In contrast, optimal drug release rates are critical for maintaining bioavailability and achieving therapeutic efficacy. Using response surface models to formulate the problem definition, five prominent MOO algorithms were employed: NSGA-III, MOEAD, RVEA, C-TAEA, and AGE-MOEA. The optimization process aimed to generate Pareto fronts representing compromise solutions between encapsulation efficiency and drug release. The results revealed inherent conflicts between objectives: increasing encapsulation efficiency often came at the cost of reducing the drug release rate. Evaluation of MOO algorithms using performance metrics such as hypervolume, generational distance, inverted generational distance, spacing, maximum spread, and spread metric provided insights into their strengths and weaknesses. Among the evaluated algorithms, NSGA-III emerged as the top performer, achieving a Weighted Sum Method (WSM) score of 82.0776, followed closely by MOEAD with a WSM score of 80.8869. RVEA, C-TAEA, and AGE-MOEA also demonstrated competitive formulation quality, albeit with slightly lower WSM scores. In conclusion, the study underscores the importance of MOO techniques in optimizing pharmaceutical formulations, providing valuable insights for decision-makers in selecting optimal formulations.
The analysis of rheological properties of suspensions requires the use of models such as Einstein’s formulation for viscosity in dilute conditions, but its effectiveness diminishes in the context of concentrated suspensions. This study investigates the rheology of suspensions containing solid particles in aqueous media thickened with starch nanoparticles (SNP). The goal is to model the viscosity of these mixtures across a range of shear rates and varying amounts of SNP and SG hollow spheres (SGHP). Artificial neural networks (ANN) combined with swarm intelligence algorithms were used for viscosity modeling, utilizing 1104 data points. Key features include SNP proportion, SGHP content, log-transformed shear rate (LogSR), and log-transformed viscosity (LogViscosity) as an output. Three swarm algorithms—AntLion Optimizer (ALO), Particle Swarm Optimizer (PSO), and Dragonfly Algorithm (DA)—were evaluated for optimizing ANN hyperparameters. The ALO algorithm proved most effective, demonstrating strong convergence, exploration, and exploitation. Comparative analysis of ANN models revealed the superior performance of ANN-ALO, with an R2 of 0.9861, mean absolute error (MAE) of 0.1013, root mean absolute error (RMSE) of 0.1356, and mean absolute percentage error (MAPE) of 3.198%. While all models showed high predictive accuracy, the ANN-PSO model had more limitations. These findings enhance understanding of starch suspension rheology, offering potential applications in materials science.
The rapid development of 3D printing, also known as additive manufacturing, has opened up new opportunities for applying shape memory polymers (SMPs) in various fields. The use of abundant, inexpensive, and easily accessible biomass materials as printing raw materials not only facilitates the creation of more intricate SMPs but also aligns with the principles of low-carbon, green, and sustainable development. Here, we successfully printed a shape memory cross-linked network (NW-MO-TTMP) in a single step by direct-ink-writing printing and an in-situ thiol-ene click reaction with magnolol and trimethylolpropane tris(3-mercaptopropionate) as raw materials. The resulting NW-MO-TTMP network exhibited high mechanical properties and a tensile strength (σ) of up to 2.7 MPa when the thiol-ene ratio was 1.0:1, and the photo-initiator content was 1.5%. To improve printability, ethyl cellulose (EC) derived from biomass was incorporated to enhance the viscosity of the printing precursor fluid, resulting in a significant increase in the σ of the NW-MO-TTMP/EC network, reaching 20.6 MPa. Moreover, the successful printing of intricate models, such as the ‘whale’ and ‘octopus,’ demonstrated excellent shape memory effects. This approach highlights the potential of combining biomass-derived materials with advanced 3D printing techniques to develop sustainable and high-performance SMPs.
Vitrimers are crosslinked polymers containing dynamic covalent linkages. Because of their crosslinked structure, they are stable as thermosets at their service temperatures. At high enough temperatures, dynamic exchange reactions occur and rearrange the polymer network, thus vitrimers become malleable and reprocessable like thermoplastics. The dynamic covalent bonds can also undergo dissociative cleavage reactions under specific conditions, so vitrimers are inherently degradable. To achieve a sustainable future, various biomass resources have been used as raw materials in vitrimer preparation. This review summarizes recent developments in biobased vitrimers and highlights their preparation methods. The limitations of current biobased vitrimers are also discussed.
This study investigated the type and amount of solid waste generation from textile wet processing industries and analyzed the disposal and recycling strategies implemented for its utilization. The method involved industrial interactions with textile processing mills. Data was gathered based on a field survey of manufacturing units and their compliance management teams. The solid waste generated in textile processing stages against input raw materials and fuel sources was recorded. The challenges in recycling solid waste are identified and further scope for its valorization is suggested. The results indicate that significant solid waste produced during the wet processing of textiles arises from waste fabric cuttings, combustion of fuels used in processing stages, and sludge generated from the post-effluent treatment. Around 80% of solid waste generated during the wet processing of textiles can find applications in the construction industry. Effective management of solid waste and its potential applications in construction are elaborated in detail.
The objective of this study is to investigate and analyze the effect of varying sources of energy inputs and their impact on carbon emissions during wool fiber processing. The method involved industrial visits to the textile wool processing mill and interaction with the manufacturing as well as commercial sourcing teams to gather relevant data. The results and outcome of this analysis indicate that wool wet processing is responsible for a significant carbon emission of about 0.031 tCO2e/unit of production. Coal as a source of energy has the highest carbon emission 0.066 tCO2e/product, while the use of biomass and Pressurized Natural Gas (PNG) had significantly lower CO2 emissions. Further, this study evaluated the scope 1 and scope 2 category emissions produced at the wool processing stage which accounted for 56303.2 tCO2e and 1817.10 tCO2e respectively.
The cultivation of topinambur (Helianthus tuberosus) has aroused the interest of producers since it is a source of inulin and can be used for biofuel production. During tuber processing, the aerial part of the crop remains as a by-product with no practical application. This work aimed to characterize the fibers obtained from the aerial part of topinambur and to evaluate their reinforcing potential in cassava starch-based films. Starch-based films with topinambur fiber (0, 5, and 10%) were prepared by extrusion followed by thermocompression. Topinambur residue contains 88.6% of total fiber, 8.5% ash, and 0.68% lipid. Mechanical film properties evidenced the reinforcement action of topinambur fiber, 10% content was able to increase up to 70% the Young’s modulus. SEM micrographs evidenced the good fiber-matrix interaction. UV-visible capacity, opacity, and chromaticity parameters of TPS films increased with fiber content in the formulation. Fiber incorporation improved the hydrophobicity of the biocomposite materials by increasing the contact angle. Starch-based films biodegraded more than 55% after 110 days, showing a similar trend to that of microcrystalline cellulose. Thus, topinambur residue can be effectively used as a reinforcing agent for TPS materials, being an innovative and non-toxic additive within the circular economy premises.
In view of the gradual depletion of lithium resources, sodium-ion batteries (SIBs) have emerged as a viable alternative to lithium-ion batteries (LIBs). This is primarily attributed to their comparable operational principles and abundant reserves of sodium resources. As an essential component of the secondary battery, the electrolyte is of paramount importance in the functioning of SIBs, and the electrode-electrolyte interface constructed by it affects the battery performance. Adding electrolyte additives in LIBs is a low-cost and efficient method that can enhance the performance of the electrolyte and the interface between the electrode and electrolyte. This method is also applicable to SIBs. Therefore, in this study, we provide a comprehensive overview of various electrolyte additives, including but not limited to carbonate additives, sulfur-containing additives, silicon-containing additives, phosphorus-containing additives and inorganic additives. We extensively analyze the impact of these additives on the electrode-electrolyte interface and the electrochemical performance of SIBs. The purpose of this review is to comprehensively evaluate the current status of electrolyte additives in SIBs, which serves as both a basic overview of the existing situation and a practical guide for selecting suitable additives for practical applications of SIBs.
Unique structural features and wide applications of gold nanoparticles (GNPs) are inspiring researchers to develop biocompatible, reliable and cost-effective methods for their synthesis. Herein, a clean, eco-friendly and non-toxic method to obtain GNPs was developed by reducing and capping the liquid extract of stem of Lilium longiflorum and highlights the catalytic reduction of 4-nitrophenol (4-NP) and methylene blue (MB). The formation of GNPs was confirmed through the absorption peak at 535 nm in the UV-Vis spectra. TEM and HRTEM analyses reveal GNPs spherical morphology with an average size of 4.97 nm. SEM and EDX analyses further elucidate the spherical nature of GNPs and elemental composition. FTIR spectroscopy analysis demonstrates that the GNPs were coated with organic compounds, which prevent the nanoparticle from aggregation. GNPs exhibit remarkable efficiency in reducing 4-NP and MB. The catalytic efficacy of the synthesized GNPs was demonstrated through the enhanced reduction rates of 4-NP and MB, with rate constants of 1.50 min−1 and 1.29 min−1, respectively. This study develops a novel and eco-friendly technique for the synthesis of gold nanoparticles and opens possibilities for the green synthesis of other metal nanoparticles. The confirmed catalytic activity holds promise for a range of industrial applications and environmental sustainability.
The adsorption purification of gasoline fraction with NaX zeolites as a solvent for the production of high-density polyethylene at a large pilot plant with a layer height of the adsorbent layer from 1 to 8 m is considered. Removal of impurities of aromatic and unsaturated hydrocarbons, organosulfur impurities and water ensured the production of high-quality polyethylene. The main characteristics of the adsorption process (the dynamic activity of zeolite NaX, the length of the mass transfer zone) in a wide range of flow rates of the cleaned raw materials are determined, allowing the calculation of the adsorber without applying the principles of large-scale transition.
