Reaction Chemistry & Engineering最新文献

In recent years, imidazolium-based ionic liquids (ILs) and pyrazolium-based ILs have shown efficient catalytic abilities in CO₂ cycloaddition reactions. However, these catalysts require stringent conditions for the reactions in the absence of co-catalysts, thereby limiting their applicability. Therefore, there is an increasing demand for developing new IL catalysts capable of operating under milder conditions. Traditional methods for designing these ILs, whether through theoretical calculations or experimental exploration, are both costly and challenging. This study presents a deep learning model for predicting the yield of CO₂ cycloaddition reactions catalyzed by imidazolium-based and pyrazolium-based ILs. The model utilizes hybrid fingerprint features to describe the structural information of molecules, achieving a squared correlation coefficient (R²) value of 0.85. Moreover, the SHapley Additive exPlanations (SHAP) technique is employed to identify the key factors influencing yield. Additionally, a molecular generation scheme is established to create new IL structures. Through a two-step screening strategy involving yield prediction using the deep learning model and energy barrier calculations via density functional theory (DFT), 14 promising imidazolium-based ILs are identified as potential efficient catalysts for CO₂ cycloaddition reactions with epichlorohydrin under mild conditions. This work introduces a novel machine learning approach for designing imidazolium-based IL and pyrazolium-based IL catalysts, aimed at reducing the experimental burden and exploration costs associated with catalyst development.

A new electrochemical sensor incorporating a molecularly imprinted polymer and multi-walled carbon nanotubes was successfully created for the sensitive detection of quercetin (Qu). The molecularly imprinted polymer was prepared by using quercetin as the template, 4-vinyl pyridine as the monomer, 2,2′-azobis (2-methylpropionitrile) as the initiator agent and ethylene glycol dimethacrylate as the cross-linker, respectively. A series of electrochemical experiments were conducted to evaluate the performance of the developed sensor and the experimental results demonstrate that the sensor for quercetin demonstrates a broad detection range of 1–245.5 and 245.5–630.5 μM with a low limit of detection of 0.23 μM. Additionally, this quercetin sensor exhibited long-term durability, good repeatability, and excellent selectivity in the presence of other interferents. In addition, the sensor was used for the evaluation of quercetin in human serum samples and ginkgo leaves, showing satisfactory recovery results of 99.04–103.85% and 98.90–103.07%, respectively, indicating that the sensor has great potential for practical applications.

This work involved a series of studies on liquid–liquid phase equilibrium in chemical non-equilibrium and chemical equilibrium states, i.e. corresponding to chemical equilibrium heterogeneous compositions, at a fixed temperature and pressure in a system consisting of n-butyl alcohol and n-butyl acetate as potential fuel components. Phase equilibrium was studied for two binary (n-butyl alcohol–water and n-butyl acetate–water), three ternary (acetic acid–n-butyl alcohol–water, acetic acid–n-butyl acetate–water, and n-butyl alcohol–n-butyl acetate–water) and one quaternary (acetic acid–n-butyl alcohol–n-butyl acetate–water) systems at 303.15 K and 101.3 kPa. Chemical equilibrium heterogeneous compositions were found for the acetic acid–n-butyl alcohol–n-butyl acetate–water system under the same conditions. Chemical equilibrium was reached in the presence of a catalyst (hydrochloric acid). All results are presented in two-dimensional and three-dimensional composition spaces. For further visual representation of the obtained data, the compositions of chemical equilibrium phases are presented in the square of concentration α-variables. A comparative analysis of the obtained compositions was carried out. Correlation analysis was performed using the NRTL model, taking into account vapour–liquid equilibrium data for binary mixtures reported in the literature. Thus, we attempted to thoroughly estimate the possibility of mutually correlating vapour-liquid and liquid–liquid equilibrium data for the studied system. Calculations showed sufficient agreement between the experimental values and the calculated data.

Photochemistry screening platforms can accelerate the discovery and development of novel photocatalysts for water remediation. This study presents the design, characterization, and optimization of an innovative flow-based screening platform for evaluating immobilized photocatalysts in the photodegradation of water pollutants. The compact system is engineered with four 3D-printed polymeric microreactors and a multi-wavelength LED light source capable of emitting at four distinct wavelengths. Therefore, the platform design allows at least 16 unique testing conditions through light source rotation. The performance of the microfluidic platform was evaluated via the photocatalytic degradation of imidacloprid, a pesticide, using P25/20 TiO₂ immobilized as a thin film. The results demonstrated a consistent degradation efficiency of approximately 35% at 395 nm with negligible variation across the four microreactors and no dependence on the testing order at 395, 409, 413, and 443 nm. During the wavelength-dependent screening, the photocatalytic film activity did not decrease after 6 hours of operation and under five successive illumination conditions, while only 46 mg of photocatalyst and 21 mL of imidacloprid aqueous solution were consumed. Moreover, automated dynamic flow and dynamic irradiation were used to optimize degradation efficiency and a guide on how to use them to improve energy efficiency and overcome common limitations of in-flow testing was provided. This microfluidic platform diminishes manual effort and enables efficient and sustainable photocatalytic studies while establishing itself as a promising tool for the automated screening of immobilized photocatalysts.

Manganese (Mn), cobalt (Co), and nickel (Ni) are designated as critical elements by the U.S. Department of the Interior. Acid mine drainage (AMD) is a viable secondary source for these metals. Conventional AMD treatment processes necessitate high pH levels (∼pH 9) or costly oxidants to recover these elements. Building upon prior work, this study utilizes an ozone oxidative precipitation method, currently patent-pending, to reduce chemical use and recover Mn, Co, and Ni from AMD. Saturation index calculations and Pourbaix diagram analyses demonstrated that ozone could recover these elements across a broad pH range (2–8). The effects of process parameters, particularly gas flow rate, stirring rate, and temperature, on the precipitation of these elements from AMD were investigated. It was found that the recovery of Mn–Co–Ni is enhanced when there is an increase in these parameters to a certain level, below which no statistically significant differences were observed. Additionally, a kinetic study on the oxidative precipitation of Mn–Co–Ni was conducted employing the pseudo-homogeneous model, and the activation energies were calculated. The effect of the process parameters, along with the calculated activation energy values (E_a(Mn) = −13.9 kJ mol⁻¹; E_a(Co) = 16.3 kJ mol⁻¹; E_a(Ni) = 14.5 kJ mol⁻¹), collectively suggests that the ozone oxidative precipitation process of Mn–Co–Ni is diffusion-controlled.

We developed a UV-assisted microfluidic system to synthesize FeCrAl–Al₂O₃ composite microparticles for additive manufacturing. The system ensures precise particle size, morphology, and elemental distribution control. Increasing the dispensing pressure while keeping the oil flow rate constant resulted in larger microparticles. Laser fusing revealed FeCrAl and Al₂O₃ phases, showing their potential as feedstocks for 3D printed heterogeneous materials such as FeCrAl/Al₂O₃ bi-phase materials.

The kinetic profile of the reaction of O-methyl-N-aryl carbamates with aliphatic alcohols in the presence of their respective alkoxide catalysts was investigated across a temperature range from 323 K to 373 K. In alcoholic media, the reaction exhibits selectivity and follows first-order kinetics relative to the substrate carbamate. Kinetic constants for the O-methyl-N-aryl carbamate reaction with a series of alcohols were quantified. The mechanistic pathway was elucidated, revealing that the nucleophilic attack by the alkoxide ion on the carbonyl carbon dominates under the examined conditions. Correlation equations were employed to articulate the impact of alcohol structural characteristics on the interaction rate with O-methyl-N-phenyl carbamates, demonstrating that less polar alcohols promote faster reactions. The Hammett equation was applied to describe how substituents on the aromatic moiety of O-methyl-N-phenyl carbamate influence the reaction kinetics with ethanol and isopropanol, showing that electron-withdrawing substituents facilitate the process, consistent with the established mechanistic framework. Activation parameters relevant to this reaction series were evaluated, revealing isokinetic temperatures that suggest a change in the reaction mechanism at 100–250 K above the experimental temperatures. The experimental data were applied to the synthesis of chlorpropham (O-isopropyl-N-(3-chlorophenyl)carbamate), demonstrating their practical utility in herbicide production.

This study presents the development of an electrically driven dual-stage reactor system for efficient syngas production via integrated CO₂ methanation and methane partial oxidation. A spiral-shaped metallic catalyst structure enables localized Joule heating by direct current, allowing rapid and energy-efficient temperature control. In the first stage, the Ru/CeO₂ catalyst achieved a high CO₂ conversion of 78% and CH₄ selectivity exceeding approximately 100% under low input power (10 W). In the second stage, the Ni/CeO₂ catalyst facilitated CH₄ partial oxidation with 91% CH₄ conversion and syngas production exhibiting an H₂/CO ratio of approximately 2.8. By shortening the catalyst length and increasing flow rates, the system further enhanced heat utilization and CO yield. Notably, while the standalone partial oxidation system suffered from carbon deposition, the integrated configuration demonstrated improved stability due to the presence of residual hydrogen and water from the methanation stage, which effectively suppressed coke formation. To our knowledge, this work is the first to experimentally demonstrate a fully electrified, tandem CO₂-to-syngas process combining e-methanation and e-POM in a compact system, offering a promising platform for renewable-energy-compatible chemical conversion.

In the past years, ultrasound has been considered a sustainable process intensification technique for zeolite synthesis. However, understanding the link between ultrasound phenomena and their related effects has remained a challenge due to the limited availability of hydrothermal ultrasonic reactors and parameter standardization among the studies. In this work, a novel ultrasound-integrated tubular coiled reactor is presented, which enables fast and efficient ultrasonic hydrothermal zeolite synthesis. Specifically, the effect of ultrasound irradiation and its underlying mechanisms on high silica FAU-to-MFI interzeolite conversion is studied. Unseeded syntheses in the presence of an organic structure-directing agent (OSDA) are performed at 160 °C for residence times up to 2 h. The presence of hydroxyl radicals generated by ultrasound is assessed via terephthalic acid dosimetry at different temperatures and pressures as a measurement of the cavitation activity. The application of 20 W mL⁻¹ of suspension reveals an enhanced MFI growth rate and faster crystallization completion, resulting in an overall increase in the mean crystal size. Ultrasound is also successful in counteracting solid deposition on the walls of the coiled reactor. Applying hydrothermal conditions to this setup suppresses radical formation, indicating very weak transient cavitation activity. Therefore, these observations are attributed to the enhanced mass transfer via ultrasonic wave propagation, which renders the dissolved material more readily available for crystal growth.

The electrochemical reduction of CO₂ combined with efficient CO₂ capture is a promising approach to close the carbon cycle. We studied the effect of pore size on the activity and selectivity of porous Ag electrodes using template-based electrodes as model catalysts. Using polymer spheres with sizes between 115 nm and 372 nm as templates, ordered porous Ag catalysts with different pore diameters were obtained. These well-defined model systems allowed us to understand the effect of pore size on CO and H₂ production. At the most cathodic potential, around −1.05 V, up to 4 times more CO than H₂ was formed. The intrinsic CO production depends on the pore size, as it increases when changing the pore diameters from ∼100 nm to ∼300 nm. At pore diameters above ∼300 nm, the pore size does not affect the intrinsic CO production anymore. For the first time, FIB-SEM was used to quantitatively analyse the porosity of the electrodes and correlate it with trends in intrinsic activity. The catalyst with a pore diameter of ∼200 nm had the highest tortuosity of 2.41, which led to an increased CO production. The catalysts with a pore diameter of ∼200 nm and smaller have pore networks that are twice as long as the pore network of catalysts with ∼400 nm pores. This leads to an additional potential drop, which lowers the effective driving force for the electrochemical reaction. Disentanglement of these different factors is important for rational design of porous CO₂ reduction catalysts.