Reaction Chemistry & Engineering最新文献

In this work, a series of alkaline earth metal-modified manganese oxide catalysts were prepared via the impregnation method and applied to the oxidative coupling reaction of alcohols and amines to imine. The prepared catalysts were characterized by X-ray diffraction (XRD), N₂-adsorption, field emission-scanning electron microscopy (FE-SEM), H₂ temperature-programmed reduction (H₂-TPR), NH₃-temperature-programmed desorption (NH₃-TPD), CO₂-temperature-programmed desorption (CO₂-TPD) and X-ray photoelectron spectroscopy. Among the catalysts, Ba/MnO₂ showed the best catalytic performance in the reaction and exhibited the highest Mn³⁺/Mn⁴⁺ ratio, surface weak basic sites and a relatively small number of weak acidic sites. Lattice oxygen mobility and Mn³⁺/Mn⁴⁺ ratio were found to play important roles in the catalytic activity of aerobic reactions. The weak and medium basic sites on the catalyst surface can further promote the alcohol–amine oxidative coupling process, as they serve as active centers for the activation of benzyl alcohol, which is the rate-determining step for this oxidative coupling reaction.

Systematic kinetic screening of chain transfer radical polymerizations was carried out using a continuous flow-based automated synthesis platform tailored for high-throughput screening of polymer reactions. The system features real-time online monitoring of monomer conversion and molecular weight distributions of residual polymers, enabling the generation of consistent, machine-readable kinetic datasets while minimizing user bias and experimental variability. A consistent dataset was obtained for the homopolymerization of butyl acrylate (BA), vinyl acetate (VAc) and methyl methacrylate (MMA) mediated by 1-dodecanethiol as the chain transfer agent, across a temperature range of 70 °C to 100 °C. A highly consistent dataset was obtained, allowing the determination of the respective chain transfer constants for each monomer at each temperature. On the test case of vinyl acetate polymerization, a generalized kinetic model for the rate of polymerization in the given parameter space was created via fitting of the individual overall kinetic coefficients for the rate of polymerization, obtained from 1st order kinetic data analysis. Bayesian optimization was then applied to predict which experimental conditions have the best potential to gradually improve the kinetic model, and interactive model improvement is demonstrated. This provides an important stepping stone for the development of self-driving labs that use databases to autonomously pick future experiments to carry out in order to improve their own data basis.

Monosaccharide D-mannose (D-Man) is of great interest in the food and pharmaceutical industries as a low-calorie sweetener and precursor for D-mannitol and medicaments. Nowadays, large-scale production of D-Man remains challenging due to a lack of efficient chemo-catalytic processes using D-glucose (D-Glc) as educt. In this work, heterogeneous catalytic epimerization of D-Glc to D-Man by a tin-organic framework (Sn-OF-1) was achieved. The reaction kinetics were explored using both conventional methods and time-resolved operando MAS ¹³C NMR spectroscopy. Under optimized reaction conditions (100 °C, 5 wt% D-Glc, 20 mg(cat) g⁻¹(EtOH : H₂O)), epimerization yielded a 77 : 23 equilibrium mixture of D-Glc : D-Man after 1.5 h reaction time. Most D-Glc (ca. 73%) was recovered from the obtained mixture of saccharides by crystallization from EtOH : MeOH (4.7 : 1). The remaining mixture of D-Man and D-Glc was separated via adsorption on CaY zeolite, resulting in a stream containing D-Man at 70% purity.

Hydrogenated toluene diisocyanate (HTDI) is crucial in military and new energy industries, with its synthesis challenged by the deamination side reaction during the hydrogenation of 2,4-toluenediamine (2,4-TDA) to 1-methyl-2,4-cyclohexanediamine (2,4-MCDA). This study addresses this by designing Ru-based catalysts with controlled acidity through LiOH-induced surface defect engineering on γ-Al₂O₃ supports. Ru/γ-Al₂O₃ catalysts were synthesized via impregnation–precipitation and characterized using TEM, NH₃-TPD, and XPS. Optimal LiOH concentration (5 wt%) enhanced the Ru loading and dispersion, improving catalytic activity and 2,4-MCDA selectivity. At 180 °C and 5.0 MPa, the 2,4-TDA conversion reached 67.5% with 78.58% 2,4-MCDA selectivity. The catalyst maintained high performance over 10 cycles, offering a theoretical basis for advancing 2,4-TDA hydrogenation and catalyst design.

Amino-methyl-N-phenylcarbamate (TMC) is an important organic intermediate. In this study, a new two-step route, i.e., methoxycarbonylation and a direct amination reaction, was designed for synthesis of TMC. During this process, p-toluidine first reacted with dimethyl carbonate to form metholylcarbamate (MTCM), and then MTCM further converted to TMC via the direct amination reaction. It was found that in the methoxycarbonylation process, the Zn(OAc)₂ catalyst was a better choice and p-toluidine was almost completely converted into MTCM, corresponding to 99% p-toluidine conversion and 95.4% MTCM yield. As for the direct amination reaction, the Fe–V/ZSM-5 bimetallic catalyst was selected and a high yield of total TMC was obtained at 69.6%. The catalyst characterization results showed that the synthesized bimetallic catalysts retained the structural features of ZSM-5, while the abundance of metal ions on the surface promoted the reaction.

Magnetically agitated miniaturised continuous stirred tank reactors (m-CSTRs) are an attractive tool for the investigation of reaction kinetics, as they combine active stirring with enhanced heat and mass transfer due to their small dimensions, while their compatibility with in situ spectroscopic techniques enables reaction monitoring and high-throughput data acquisition. This study presents the development of a 2.65 mL m-CSTR, integrated with in situ Raman spectroscopy for real-time kinetic data acquisition in continuous flow. The reactor, featuring a temperature-controlled stainless-steel chamber with a top quartz glass window and a PTFE slotted impeller, was assessed for its macro- and micromixing characteristics at flowrates between 0.5 and 4 mL min⁻¹. The slotted impeller led to near-ideal CSTR behaviour and improved micromixing quality in comparison to conventional cross stir bars of similar dimensions. Using the imine synthesis of n-benzylidenebenzylamine from benzaldehyde and benzylamine as a model reaction, kinetic parameters were determined with direct composition measurement inside the reactor and the most informative region of the design space, i.e., the experimental conditions that provide the most useful data for accurate kinetic parameter estimation and model validation, was identified to be in the region of high reactant concentrations and short residence times within the temperature range investigated (15–45 °C).

In this study, nitrogen and iron–copper co-doped biochar was prepared and utilized to remove bisphenol A (BPA) from an aqueous solution via the activation of peroxymonosulfate (PMS) over a wide pH range. It was found that the entire degradation system was dominated by a complete non-radical process, where singlet oxygen played a major role and Cu(III) played a minor role, and oxygen vacancies and surface catalytic metals were the active sites responsible for their generation. Furthermore, it is PMS that originated singlet oxygen rather than dissolved oxygen or lattice oxygen. XRD, XPS and EPR analyses revealed that the introduction of nitrogen in the biochar composite promoted ferroferric oxide crystal growth and the formation of oxygen vacancies. The quantitative structure–activity relationship (QSAR) model indicated that the degradation rate of phenolic compounds in this catalytic system was related to the minimum value of charge on their carbon atom (q(C)_n), which also revealed that through the oxidation process, singlet oxygen could easily attack partially negatively charged carbon atoms in phenolic compounds.

This paper introduces the neural tanks-in-series (NTiS) model, an extension of the traditional tanks-in-series (TiS) model using physics-guided neural networks (PGNNs). The NTiS model integrates physical principles with data-driven approaches to improve the accuracy and reliability of flow reactor modeling. The NTiS can optimize physical parameters and learn unmodeled dynamics while ensuring physically feasible predictions, even for out-of-domain predictions. The approach is validated using simulations and experimental data from a Paal–Knorr pyrrole reaction, demonstrating its capability to model flow reactor systems under varying conditions. The NTiS framework offers a new, robust, and flexible tool for advancing chemical flow reactor modeling.

High-throughput experimentation enables rapid reaction optimization by leveraging reaction miniaturization, automated processes, and advanced high-throughput analytical methods. To more effectively apply these principles to reactions mediated by photoredox catalysis, we developed the photoredox optimization (PRO) reactor. PRO is an automated platform that provides precise control over the delivered light irradiance to optically thin, temperature-controlled reaction volumes. Combined with high-intensity laser illumination, PRO facilitates accelerated photoredox reaction scouting using <10 μL of reaction material. Crude products from PRO reactions are automatically transferred to microplates for analysis by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS) which can quantify 384 reactions in under 6 minutes. Validation of the PRO reactor was achieved through a series of challenging decarboxylative cross-coupling reactions, which resulted in improved isolated yields up to 58%. PRO then enabled the design and execution of higher throughput 384-reaction HTE arrays which achieved improved yields for two previously unsuccessful photoredox cross-couplings, ultimately identifying novel reaction conditions outside the scope of our traditional 96-reaction arrays.

Low-temperature CO₂ methanation technology is a promising way for utilization of CO₂. Nickel (Ni)-based catalysts have been widely investigated in such a methanation reaction due to their excellent catalytic performances and relatively low costs. This review thereby focuses on the current research progress on Ni-based catalysts in low-temperature CO₂ methanation. It firstly summarizes the possible reaction mechanisms of CO₂ methanation. Based on these reaction mechanisms as well as the activation mechanisms related to H₂ and CO₂ molecules, it also discusses the structural requirements and preparation methods used to improve the performances of low-temperature CO₂ methanation reactions of Ni-based catalysts by constructing the structured catalyst and tailor-designing the structures of Ni⁰ sites, the support and the Ni/support interface. Finally, this review provides several suggestions for the future development of Ni-based catalysts in the low-temperature CO₂ methanation reaction.