Reaction Chemistry & Engineering最新文献

In this study, Ga-doped MnMoO₄ self-supported flower-like structured electrode materials were successfully prepared by the sol–gel method. The research results show that the introduction of gallium not only enhances the conductivity and charge transfer rate of MnMoO₄, but also improves the electrolyte permeability and ionic transport capacity by introducing oxygen vacancies and lattice defects. In addition, the self-supported flower-like structure increases the specific surface area of the material, enhances the structural stability of the material, provides more transport channels for ions, and improves the electrochemical reaction rate and cycling stability of the material. In the three-electrode test system, the specific capacitance of Ga-doped flower-like MnMoO₄ decreased from 1376 F g⁻¹ to 1358 F g⁻¹ after 10 000 cycles at a high current density of 15 A g⁻¹, with a retention rate of 98.6%. This fully demonstrates that this material has excellent stability in terms of cycle life. It exhibits outstanding cycle life. Moreover, after the performance of the carbon nanotube (CNT) material is enhanced, its excellent conductivity and ionic diffusion properties provide strong support for efficient energy storage. The Ga-doped flower-like MnMoO₄//CNT device, after 10 000 cycles at 5 A g⁻¹, saw a decrease in specific capacitance from the initial 255 F g⁻¹ to 249 F g⁻¹, with a capacitance retention rate of 97.6%, providing an effective strategy for the design and development of high-performance supercapacitors.

Recovery of excess acid after leaching is essential in circular hydrometallurgical processes, because it reduces reagent consumption and generates less waste. Solvent extraction can be used for acid recovery from aqueous solutions. This study presents a thermodynamic model for the synergistic solvent extraction of H₂SO₄, HCl, and methanesulphonic acid (MSA) using tris(2-ethylhexyl)amine (TEHA) and 1-octanol in n-dodecane. The model is developed using the mixed-solvent electrolyte (MSE) framework of OLI Systems, integrating an extensive set of own experimental data and literature data. It captures both individual and synergistic extraction behaviours and accurately calculates equilibrium properties such as acid distribution, water uptake by the solvent, volume change during extraction, and organic phase mass density at room and elevated temperatures. Validation with H₂SO₄ recovery from NiSO₄ solutions confirms its predictive capabilities for industrially relevant conditions. This work offers a robust tool for designing acid recovery processes through solvent extraction and gives mechanistic insights into the studied extractant systems.

Colloidal semiconductor nanocrystals or quantum dots (QDs) are a class of materials with size and shape-dependent optoelectronic properties that show potential for a range of applications. Discovery of new QDs with interesting properties and optimization of their synthesis require a rapid, generalizable, and scalable purification method to separate QDs from reaction mixtures. This paper describes a size-exclusion chromatography (SEC)-based approach that enables rapid, efficient separation of QDs from crude QD reaction mixtures. Using commercially available C-18 capped silica columns and off-the-shelf components, we report an automated liquid-chromatography platform with integrated optical characterization (UV-vis) for in-line optical characterization. This platform was used to investigate the effects of column operating parameters on QD separation performance and was further validated using six crude QD samples of different sizes, shapes, and compositions. Ligand coverage of the purified QD fractions can be tuned by controlling column parameters, with higher temperatures and residence times leading to ligand shedding of QDs. NMR analysis of purified QDs showed reduced solvent and ligand impurities when compared to samples purified using a precipitation–redissolution method. This SEC method provides a rapid (<2 min) approach for one-step purification of crude QDs on analytical or preparative scales and can be seamlessly integrated into existing QD or other nanocrystal research workflows.

Photochemistry has recently re-emerged at the forefront of chemical development, however, access to affordable and reliable photoreactors that generate reproducible results is a continued challenge for researchers in the field. Herein we present an open-source 3D printable ‘M-Arc’ photoreactor, named for its modularity and internal arc structure. The M-Arc reactor features modular batch and flow reactor inserts, ports for one or two light sources and a fan unit for maintaining temperature control. The reactor was benchmarked against commercially available photoreactors using chemical actinometry and three classical photochemical transformations: photoisomerisation, dehalogenation and a cross-coupling amination reaction. Photon delivery in the M-Arc reactor was improved 3.25-fold compared to a commercial reactor which translated into enhanced rate of reaction for all three tested photoreactions. Using the flow reactor insert, a further rate improvement for photoisomerization was achieved, ultimately demonstrating a 15 times rate improvement versus the HepatoChem PhotoRedOx Box™ market product.

ZnZrO_x solid solutions have been extensively reported for methanol production from the hydrogenation of carbon dioxide (CO₂) on account of their high selectivity, prominent stability and sulfur tolerance. Herein, a series of ZnZrO_x supported-CuNi catalysts were fabricated using a liquid-phase reduction-deposition method and then utilized for CO₂ hydrogenation. The impact of the Cu : Ni molar ratio on the physicochemical properties of the catalysts and their CO₂ hydrogenation performance was systemically studied and discussed. The synchronous introduction of Cu and Ni into ZnZrO_x not only improved the BET-specific surface areas and the reducibility of the metallic species but also markedly increased the concentration of surface oxygen vacancies and the amount of CO₂ desorbed, thereby leading to excellent reactivity. Moreover, the CH₃OH space-time yield (STY) was positively correlated to the concentration of surface oxygen vacancies and the amount of desorbed CO₂. Because of the outstanding reducibility, high metal dispersion, superior CO₂ adsorption ability, sufficient surface oxygen vacancies, and the proper interaction between the metals and support, Cu₂Ni₁/ZnZrO_x achieved a CH₃OH selectivity close to 82% with a CO₂ conversion greater than 10% at 3.0 MPa, 15 000 mL g_cat⁻¹ h⁻¹ and 280 °C.

Recent progress in brain research reflects an exciting interface of technology and biology, leading to the development of effective therapeutic compounds and site specific delivery systems to address complex neurological disorders. These innovative therapies also serve as novel diagnostic and therapeutic platforms for drug delivery (DD) to the brain and soft tissue in the context of brain injury, aiming to enhance drug penetration and targeting while improving efficacy and minimizing systemic toxicity. Hence, the innovative approach of this project lies in the development of a network structure in the form of hydrogels derived from bioactive sulphated polysaccharide & zwitterionic polymers by the copolymerization technique for the delivery of the neuroprotective & neurorestorative (citicoline) compound at the site of nerve injury. The biocompatibility, protein adsorption, antioxidant, mucoadhesion, drug delivery and cell-viability of rhabdomyosarcoma cell properties of hydrogels were analyzed. Hydrogels expressed 165 ± 0.19% cell viability of RD cells and promoted cell adhesion and proliferation, signifying their compatibility with mammalian cells. DPPH assay revealed 39.82 ± 1.65% free radical scavenging ability of the materials, highlighting their strong intrinsic antioxidant potential for neutralizing oxidative stress at the site of nerve injury. The mucoadhesion of the materials was signified from a force of 75 ± 4.00 mN, desirable for adherence to mucosal surfaces and helps in cell attachment and alignment during the nerve regeneration process. The citicoline anchored brain drug delivery carrier released the drug in simulated brain fluid in a sustained pattern and followed the non-Fickian diffusion mechanism. The release profile was best explained by the Hixson–Crowell kinetic model. The materials were also characterized by FESEM, EDAX, AFM, FTIR, ¹³C-NMR & XRD techniques. Overall, the presented synergistic therapy for treatment of brain injury involved the delivery of the bioactive nerve regenerating agent from functional materials. It will not only deliver therapeutic molecules to nerve injuries but its inherent antioxidant, haemostatic & non-cytotoxic nature with cell viability properties may also contribute to enhancing the nerve repair process of brain injury.

In this study, we report for the first time the electrocatalytic performance of Pr-based metal oxides, PrCuO (PCO), PrNiO (PNO), and PrZnO (PZO), toward methanol electro-oxidation. Results show that PCO exhibits superior activity with a low onset potential of 0.96 V vs. RHE and strong resistance to CO poisoning. Electrochemical impedance spectroscopy (EIS) reveals a low charge transfer resistance (R_ct), indicating fast electron transfer kinetics. Mass activity of PCO reaches 0.75 A mg⁻¹, surpassing the various Pt-based catalysts such as Pt₆₂Ru₃₅/C (0.47 A mg⁻¹), Pt₆₂Ru₁₈Ni₂₀–O/C (0.30 A mg⁻¹), and PtZn NPs (0.58 A mg⁻¹). Density functional theory (DFT) calculations indicate that PCO facilitates methanol oxidation via a COH* intermediate, enhancing CO oxidation and CO₂ evolution. The favorable d-band center and strong Cu 3d–O 2p orbital interaction contribute to its high activity. These findings establish PCO as a promising and durable electrocatalyst for energy conversion applications.

Micro-packed bed reactors (μPBRs), which are widely used in multiphase reactions, have the advantages of high mass transfer efficiency and excellent safety. However, the identification of flow behavior in μPBRs with various packings remains a challenge. Rapid characterization of flow regimes needs to be taken into consideration for improving reactor research efficiency. In this work, a transfer learning conventional neural network (CNN) based on LeNet-5 was developed to recognize the flow regime of μPBRs for the first time. Micropillars and spherical particles as typical packings were employed to inspect the applicability of the model successively. The flow regimes of μPBRs with micropillar structure and spherical particles were classified using a trained transfer learning model based on LeNet-5, obtaining high accuracies of 97.5% and 94.3%, respectively. Notably, a highly integrated software platform coupling the trained CNN for analyzing flow regime with a user-friendly graphical interface was constructed, achieving online acquisition and analysis of data efficiently.

The search for efficient electrocatalysts to drive the oxygen evolution reaction (OER)/oxygen reduction reaction (ORR) has reached a pivotal juncture with the emergence of transition metal dichalcogenides (TMDs), particularly WS₂, WTe₂ and MoTe₂. These materials, with their unique electronic structures, tunable surface properties, and exceptional stability, have opened new frontiers in electrocatalysis. This review provides a comprehensive exploration of the synergistic interplay between experimental validation and computational modeling in unraveling the electrocatalytic potential of these TMD materials. Advanced experimental techniques, such as in situ spectroscopy and electrochemical microscopy, have unveiled the dynamic structural transformations and active site engineering under operational conditions. Currently, state of the art computational approaches, including density functional theory (DFT) and machine learning (ML)-guided descriptor analysis, have enabled the rational design of TMD-based catalysts by predicting reaction pathways, overpotentials, and selectivity. This review presents a novel integrated approach combining experimental techniques and computational modeling to explore the electrocatalytic potential of TMDs for the OER and ORR. By focusing on defect engineering, heterostructures, and phase transitions, this work provides a comprehensive roadmap for the development of next-generation electrocatalysts for sustainable energy application.

Amines represent crucial intermediates in fine chemical synthesis, finding extensive applications across pesticide, dye, and pharmaceutical industries. N,N-Dimethyl tertiary amines can be efficiently synthesized through reductive amination of dimethylamine. We developed an environmentally benign continuous flow reductive amination system employing a micro-packed bed reactor (μ-PBR) with a Pd/C catalyst prepared via direct impregnation. This system successfully produces N,N-dimethylcyclohexylamine (DMCHA) in an aqueous system, achieving high selectivity (99.5%), impressive space–time yields (2.7 × 10⁴ g L⁻¹ h⁻¹), and operates without requiring additional additives. In addition, the reaction system demonstrated excellent stability during a 120-hour continuous test and proved suitable for both aromatic aldehydes and aromatic amines.