The study presents the ultrasound-assisted synthesis of tricaprin using a triple frequency hexagonal ultrasonic reactor. The esterification of capric acid and glycerol was catalyzed by para-toluene sulfonic acid (p-TSA) at a 500 g scale. A one-factor-at-a-time approach was used to optimize reaction parameters under both conventional and ultrasonic conditions. Under optimized ultrasonic conditions of a 4:1 molar ratio, 150 W ultrasound power, 70% duty cycle, 1.5% p-TSA loading, and combined frequencies of 22–33–48 kHz, the tricaprin yield reached the maximum of 95.7% as determined by gas chromatography–flame ionization detector (GC–FID) analysis. The pseudo-first-order rate constant significantly increased to 0.0167 min–1 in the ultrasound-assisted approach compared to 0.0035 min–1 in the conventional method, while energy consumption was reduced by 19.2%, requiring only 1554.8 kJ against 1924.5 kJ. Among the catalysts evaluated, p-TSA and Amberlyst-15 showed the best catalytic performance among the homogeneous and heterogeneous categories, respectively. The synthesized tricaprin was formulated into a topical antifungal Bigel. Ex-vivo skin permeation studies demonstrated superior performance compared to a marketed formulation (Lulimac gel), with only 3.57% of the drug remaining unpenetrated in the Bigel, compared to 50% in the marketed product. Additionally, the bigel achieved significantly higher skin retention of 18%, while the marketed formulation showed only 0.45%. Overall, the study demonstrates the advantage of ultrasound technology for efficient tricaprin synthesis and its successful application in enhanced topical drug delivery.

Porous metal membranes have broad applications in separation processes, membrane reactors, electronic catalysis, and membrane supports. These applications require a high membrane surface area and packing density to achieve high efficiency. Hollow fiber membrane configurations offer such high packing densities and thus significantly enhance the membrane module performance. However, regulating the pore size of metal hollow fiber membranes remains challenging. In this study, the pore size of fabricated nickel (Ni) hollow fiber membranes (NHFMs) was tuned under redox conditions. The influence of the oxidation–reduction temperature on pore morphology and separation performance was systematically investigated. Optimized redox conditions yielded NHFMs with a narrow pore size distribution (mean pore size ∼60 nm, maximum ≤70 nm) and high porosity (∼47%), achieving a N2 permeance of 2.7 × 104 GPU. Additionally, the pore size of NHFMs was tuned to a mean pore size of 162–177 nm, which demonstrated excellent bovine serum albumin (BSA) separation, exhibiting a 96.6% rejection rate and a water flux of 71 L/(m2·h). This work presents a simple strategy for tailoring the pore size of Ni hollow fiber membranes for diverse applications.

The interplay between structural, compositional, and morphological features of catalysts and their catalytic performance has become crucial in engineering new generations of highly effective materials. Here, a series of Ag–Cu/CeO2–SnO2–ZrO2 catalysts with different Ag/Cu mass ratios and low total metal loading (only 2% wt) is synthesized using a sequential wet impregnation method and tested in CO oxidation and soot combustion. The resulting bimetallic 0.5Ag–1.5Cu and 1Ag–1Cu catalysts show high activity in both reactions. After aging at 650 °C for 10 h, the catalysts with a higher Cu content show improved activity in CO oxidation and only a slight decrease in the Tmax of soot combustion, confirming their stability. The high activity of catalysts can be associated with the presence of dispersed CuOx clusters, the Cu+/Cu2+ ratio, the defectiveness of samples, and the presence of oxygen species involved in carbonate formation. Contacting Ag and Cu species have higher ability to adsorb gaseous CO, improving the performance. The lower activity of the as-prepared 2Ag sample can be due to the decoration of large silver particles (20 nm) with AgCl, and the effect of chloride decreases upon aging. 0.5Ag–1.5Cu and 1Ag–1Cu catalysts show high water resistance in both reactions. Tentative roles played by the catalyst components are discussed. The results obtained can be used to prepare new effective bimetallic environmental catalysts.

Gas- and liquid-phase kinetic data for heterogeneously catalyzed ethylene hydroformylation to propanal have been assessed using analytical Langmuir–Hinshelwood/Hougen–Watson type of expressions. The more extensive gas-phase dataset was employed to discriminate between three models assuming a different surface reaction as rate-determining step (RDS). The model where CO insertion was considered as RDS exhibited the best agreement with the experimental observations. Composite activation energies amounting to −24 and 14 kJ/mol were obtained. Adsorption enthalpies amounted to −33 kJ/mol for ethylene and −47 kJ/mol for CO. Adequately accounting for the thermodynamics of the presence of a liquid phase in the best-performing model sufficed to reproduce the liquid-phase experimental data, indicating that the developed kinetic model performs well at both gas- and liquid-phase conditions.

Lightweight polymer foams with well-controlled microcellular structures are increasingly important for automotive, packaging, and insulation applications. In this study, we report a synergistic nanocomposite approach to enhance the foaming behavior and mechanical stability of long-chain branched polypropylene (LCB-PP) using multiwalled carbon nanotubes (MWCNTs) and in situ fibrillated polytetrafluoroethylene (PTFE) nanofibers. The nanocomposites were prepared via high-shear melt extrusion, which promoted PTFE nanofibrillation in the LCB-PP matrix. MWCNT islands are contributing to high nucleation of bubbles during batch foaming with supercritical CO2. PTFE nanofibrils and MWCNTs allied together as an internal reinforcement of molten LCB-PP and contributed to its high elongational viscosity. The nanocomposite foams also demonstrated that such alliance of PTFE nanofibrils and MWCNTs favored the formation of high cell-density LCB-PP foams with intriguing morphological features. The strong strain hardening of the LCB-PP nanocomposites enhanced the foam stability by preventing the formation of very large cells. Isothermal crystallization studies revealed that the PTFE nanofibrils constitute nucleation sites for polymer crystallization during the foam setting, significantly reducing the solidification time and promoting consolidation of the foam structure. The nanofillers reinforced the foam cell walls and improved the mechanical integrity. Furthermore, the combined nucleating effect of the fillers led to uniform cellular morphology with a cell density reaching 8.97 × 107 cells/cm3 for the highest PTFE nanofibril contents (5 wt %). This work highlights a robust strategy for developing high-performance polymer nanocomposite foams with reduced material consumption and improved structural properties that can be tailored for industrial applications.

Trial and error remains the most common method to select the right solvent for the extraction or separation of natural products. This can lead to either a lengthy or a suboptimal selection of solvents. Modeling biphasic systems using thermodynamic models such as the conductor-like screening model for realistic solvents (COSMO-RS) was reported recently and has proven to be a valuable tool. The current work explores the capabilities and limitations of COSMO-RS in the context of separation processes. Following the well-known HEMWAT system commonly used in the countercurrent separation process, 16 different solvent compositions were calculated. Proof of concept was given by injecting several standards into a 50 mL column of centrifugal partition chromatography (CPC). Both solvent systems expressed stable hydrodynamic behavior in the column and a good separation potential. Finally, this study reports large-scale screening and design of over 200 sustainable biphasic solvent systems with experimental validation in CPC.

This study introduced an organic polymer (Ph-g-C3N4-Ag) featuring a D-A1-A2 structure created by integrating a benzene ring with a single Ag atom and incorporating reduced graphene oxide (RGO) to form a Ph-g-C3N4-Ag/RGO Schottky junction. This precise construction enhanced the separation efficiency of photogenerated charges while minimizing surface charge complexation. The Ag single-atom optimized photogenerated charge transport through its localized surface plasmon resonance effect, further improving thermal charge transfer at the interface. The RGO as a hole-extraction layer facilitated the effective transfer of photogenerated holes and reduced surface complexation. Additionally, coupling the piezoelectric polarization field with the Schottky junction lessened charge complexation and boosted the charge separation and transport efficiency. The photothermal effect of localized surface plasmon resonance in Ph-g-C3N4-Ag/RGO enhanced carrier migration efficiency and reaction system temperature, which was proved by photothermal experiments and thermal infrared imaging. The catalytic performance of Ph-g-C3N4-Ag/RGO was evaluated by piezo-photothermal catalysis self-Fenton degradation of organic pollutants, and the results showed that the k-value of the tetracycline hydrochloride degradation by Ph-g-C3N4-Ag/RGO-15 was 0.02121 min–1 when 5 mg of Fe2+ was added. Ph-g-C3N4-Ag/RGO-15 showed superior properties compared to those of the other five different g-C3N4 composites. Changes in degradation intermediates were detected and analyzed, thus revealing the synergistic degradation mechanism of the piezoelectric photothermal-catalyzed self-Fenton-catalyzed mineralization system, and it was shown that hydroxyl radical, hole, and superoxide anion radical were the primary active species and played a more important role in the system. This presented a novel approach for the degradation of organic pollutants.

Along with their widespread application, lithium-ion batteries (LIBs) have recently gained growing acceptance as a sustainable and clean technology. In this regard, the present study proposes a two-phase approach based on a new hybrid multicriteria decision-making (MCDM) method and sustainable robust optimization (RO) approach to design and plan a LIBs supply chain (SC) under uncertainty. In the first phase, the most appropriate possible locations for battery manufacturing zones are determined based on various ecological, social, and technical criteria. For this purpose, the Bayesian best-worst method (BBWM) and technique for order of preference by similarity to ideal solution (TOPSIS) are combined through the hybrid MCDM analysis. In the second phase, a two-stage stochastic RO model is formulated to optimize a set of strategic and tactical decisions for LIBs SC. The proposed LIBs SC design is a sustainable mixed-integer linear programming (MILP), multiproduct, and multiperiod model that addresses environmental, social, and economic objectives. Finally, the model’s performance is evaluated by conducting an actual case study in Iran, offering key managerial insights. Findings reveal that the hybrid BBWM-TOPSIS method reduces the optimization model’s computational complexity by eliminating 45% of inappropriate locations. Furthermore, raw material supply cost and manufacturing activities account for the highest portion of the total cost and EI elements by 53% and 60%, respectively.

Pervaporation, combined with other separation processes,can effectivelyremove water from fermentation product streams, making it highly suitablefor purifying alcohols like 2,3-butanediol (BDO). In this study, adense poly­(vinylidene fluoride) (PVDF) hollow fiber membrane moduleprototype was fabricated for BDO dehydration, achieving >0.2 LMHtotalflux and >95% BDO rejection. With a Markov chain Monte Carlo (MCMC)approach, Bayesian inference was used to quantify the uncertaintyof the permeance parameters. A membrane cascade model was developedto scale up a process that purifies a preconcentrated BDO feed (70wt %) to high purity (90 wt %). Through propagation of the uncertaintyof the parameters and sensitivity analyses of the process variables,a cascade design was recommended. Despite data and model limitations,the framework enabled a reliable system analysis and economic evaluation,validated through tight confidence intervals in key process metrics,establishing the foundation for future applications of Bayesian methodsin membrane-based processes.