Aiche Journal

This study presents a data‐driven modeling and multi‐objective optimization framework for an integrated section of continuous pharmaceutical manufacturing, focusing on flow synthesis and continuous crystallization. To address data scarcity and trade‐offs among product quality, efficiency, and environmental impact, the framework combines generative adversarial networks (GANs), artificial neural networks (ANNs), and genetic algorithms (GAs). An integrated dual‐GAN (ID‐GAN) generates data under physicochemical constraints, which are merged with real data to train an ANN with 15%–20% mean absolute errors for particle size, productivity, and a sustainability throughput index. The ANN is then coupled with a GA to identify Pareto‐optimal solutions based on user‐defined objectives and constraints. Case studies validate the framework's capability to facilitate process design decisions by systematically exploring trade‐offs among competing objectives, underscoring its potential utility in the digitalization of critical units within continuous manufacturing systems.

Hydrogen peroxide (H2O2) is a platform green oxidant for high‐value chemical synthesis, but its centralized production hinders its widespread use in a safe manner. Here, we describe a practical tandem electro‐thermochemical H2O2‐mediated oxygenation platform for the synthesis of various high‐value oxygen‐containing compounds. The integration of solid‐electrolyte H2O2 electrosynthesis with heterogeneous zeolite thermocatalysis enables atom‐efficient oxygenations without the need for downstream electrolytes or catalysts separation. A spatially decoupled tandem system integrating aqueous H2O2 electrosynthesis with nonaqueous thermocatalysis offers independent optimization capabilities, thus maximizing the overall space–time yield (STY). With microfluidic packed‐bed intensification for heterogeneous thermocatalysis, this tandem system achieved H2O2‐mediated oxygenation of thioesters to sulfoxide at a high current density (300 mA cm⁻²) and STY (7.07 mmol cm⁻³ h⁻¹). Furthermore, the platform's broad applicability was showcased with titanium‐silicalite‐1 zeolite catalyzed olefin epoxidation and cyclohexanone oxime synthesis, underscoring its potential for diverse catalytic oxygenation applications.

Rigid molecular sieve is highly desirable in industrial gas separation, but persistently challenged by sluggish adsorption within inherent rigidity‐confined narrow sieving pores. Herein, we report a rigid carbon‐based molecular sieve featuring ink‐bottle bimodal sub‐nanopores for the ideal fast sieving separation of propylene/propane mixture. The tailor‐made narrow pore entrance, centered at 5.0 Å, affords precise sieving capacity for propylene over propane with a high selectivity exceeding 200. Concurrently, the larger cavity located at 6.4 Å allows the exceptional fast adsorption kinetics of propylene. The measured diffusion coefficient of propylene (4.2 × 10–3 s⁻¹) is one to two orders of magnitude higher than state‐of‐the‐art rigid molecular sieves and comparable to the non‐steric diffusion observed in mesoporous zeolite. High‐purity C3H6 production (>99.2%) is achieved in breakthrough experiments through a single adsorption–desorption cycle. This study paves an avenue to unlock rigid molecular sieves toward advanced separation of challenging gas analogues.

Microannular rotating bed (MARB) is a newly designed reactor that integrates high‐gravity fields and microscale effects to enable efficient liquid mixing. This study systematically investigated the hydrodynamic and liquid–liquid dispersion characteristics of the MARB, including residence time distribution, liquid holdup, energy dissipation rate, and Sauter mean diameter (d32). Mathematical correlations for predicting these parameters were established. The results showed that the MARB operates with a flow pattern similar to that of a continuous stirred‐tank reactor. Liquid holdup increased linearly with flow rate and decreased with rotational speed, while energy dissipation rate was primarily governed by rotational speed. Notably, the MARB demonstrated excellent liquid–liquid dispersion performance, attaining a minimum d32 of 4.9 μm at a flow rate of 5 L/min, along with improved energy efficiency compared to conventional reactors. With its simple, high‐throughput, and effective design, the MARB offers a highly promising solution for efficient liquid–liquid dispersion in industrial applications.

Developing efficient and stable electrocatalysts for seawater splitting remains a huge challenge because of low catalytic selectivity and poor resistance to chlorine‐induced corrosion. Here, we developed a nickel‐iron layered double hydroxide nanosheets doped with chromium and sulfur dual atoms (Cr,S‐NiFe LDH). Cr,S‐NiFe LDH exhibited low overpotentials of 321 and 406 mV at industrial current densities of 500 and 1000 mA cm⁻², respectively. An anion exchange membrane electrolyzer based on Cr,S‐NiFe LDH anode can maintain 2000 mA cm⁻²@1.764 V for 100 h. Electronic structure analysis revealed that the sulfur doping facilitates electron transfer from nickel to sulfur sites, while chromium incorporation strengthens the electronic interactions between iron and chromium sites. This modification induced the formation of high‐valence nickel and chromium species, which favor seawater electrolysis. Mechanistic studies revealed that dual heteroatom doping modifies the local electronic environment of nickel/iron sites, repelling chlorine ions and optimizing the adsorption of oxygenated intermediates.

Large‐scale bioreactors in industrial bioprocesses pose challenges due to extracellular concentration gradients and intracellular heterogeneity. This study introduces a novel approach integrating the method of moments with truncated normal distributions (MM‐TND) to model intracellular heterogeneity while maintaining computational feasibility compared to continuum simulations. The MM‐TND framework reconstructs intracellular state distributions while respecting physical constraints, which previous methods could not ensure. Validation against experimental data confirms that MM‐TND effectively captures microbial population dynamics, particularly in large‐scale systems where convection and metabolic adaptation timescales are comparable. The results underscore the importance of intracellular heterogeneity in bioprocess modeling and highlight computational advantages of the MM‐TND approach. This approach offers valuable insights into microbial behavior under industrially relevant conditions.

The drop viscosity may play an important role in determining drop size distribution in multiphase reactors. However, most of the existing breakage models could not reasonably predict the effect of drop viscosity in a relatively wide range. In this work, an improved model is developed by considering this effect on the breakage constraint and surface oscillation for multiple breakages. Besides, the whole energy spectrum (i.e., including energy‐containing, inertial and dissipation subranges simultaneously) with the bottleneck effect is considered to determine the turbulent parameters. The predictions of the present model and other breakage models are compared with the available experimental data for breakage frequency, daughter drop size distribution, and drop size distribution (with population balance equation). For both high‐viscosity and low‐viscosity drop breakages, the results show that the present model has a better prediction ability compared with other models. Its application range is relatively wider as a whole.

Covalent organic frameworks (COFs), as potential heterogeneous catalysts, face the problem of single functional active sites in one‐pot catalysis. Herein, a polyoxometalate (POM) species, phosphomolybdic acid hydrate (PMA, H3PMo12O40) was stably integrated into the nanocages of an ionic COF (EB‐TFP). Considering practical applications, the resulting composite (EB‐TFP/PMA) powder was shaped into monolithic pellets with sufficient crushing strength and thermal stability. These materials were used in a one‐pot reaction of CO2 and olefins to obtain value‐added cyclic carbonates. Detailed activity evaluations revealed that the excellent catalytic performance (90% of main yield under the conditions of 80 C, 1 bar, 24 h and no co‐catalysts) of EB‐TFP/PMA arose from the synergistic effect of acid/base sites. The pellets also showed satisfactory catalytic performance (83% of yield under the same conditions) and good reusability. This study highlights the potential of COFs as platforms to construct synergistic active sites tailored for one‐pot catalysis.

This study presents the development of a computational fluid dynamics model for predicting ultra‐low temperatures (less than −100°C). The frost formation rate was characterized using dimensionless numbers derived from operating conditions. To better capture the underlying physical phenomena of ultra‐low temperature frosting, various physical parameters were introduced and systematically adjusted. Additionally, an ice deposition model—often overlooked in existing studies—was incorporated to enhance the model's accuracy. The influence of each parameter on predicted frost thickness was analyzed, and the simulation results were validated against experimental data. Using the established model, the impact of operating conditions on frost growth was investigated. The predicted trends in frost growth under varying conditions showed strong agreement with experimental observations. This model lays the foundation for simulating ultra‐low frost formation in more complex geometries at different operating conditions.

Deep eutectic solvents (DESs) are promising green solvents, yet their high and variable viscosity presents challenges in practical applications. Traditional viscosity measurements are labor‐intensive and time‐consuming due to numerous influencing factors. This study introduces a novel prediction framework integrating message passing neural networks (MPNN)‐graph attention networks (GAT)‐multilayer perceptron (MLP). Using a dataset of 5790 DESs, recognizing the essential role of SMILES in predicting DESs viscosity, two stacked GAT layers were utilized to implicitly capture interdependencies among molecular substructures, enabling the extraction of significant features. Given that DESs are typically binary systems, the predicted density is incorporated as an additional input, reducing reliance on experimental data. The MLP combines these extracted features with physical and chemical properties for accurate viscosity prediction. This multiscale, data‐driven approach significantly improves prediction performance (R² = 0.9945, AARD = 2.69%), surpassing conventional methods and advancing green solvent design.

Laminar‐structured covalent organic framework (COF) membranes hold great promise in molecular separation. Precise nanochannel manipulation of laminar‐structured COF membranes is of critical significance. In this study, COF membranes are engineered by assembling COF‐TbTG nanosheets and sulfobutylether‐β‐cyclodextrin (SCD) into laminar structures. The interlamellar spaces of COFs are regulated to achieve molecular sieving for precise separation; the intrinsic pores of COFs are utilized as fast molecule‐transport channels. The obtained COF membranes exhibit a superior ethanol dehydration performance with a permeation flux of 5.2 kg m⁻² h⁻¹ and a separation factor of 1072, which exceeds the performances of state‐of‐the‐art membranes for water/ethanol separation. Moreover, the optimal membranes show a steady permeation flux maintaining around 5.0 kg m⁻² h⁻¹ during a 72‐h operation test. This work may provide a new approach to the design of molecular‐sieving COF membranes for precise separation.

The actual applications of extraction methods for α‐olefins separation are limited by their long time and high energy consumption. Hence, this study employs microwave technology to intensify the extraction process using Ag‐based ionic liquid (Ag‐IL), where the influence of microwave irradiation and the mechanism of microwave‐assisted ionic liquid extraction (MAILE) are investigated, along with a comprehensive techno‐economic analysis of process feasibility. The results of COSMO‐RS and DFT simulations demonstrate the dominant role of π‐complexation in identifying Ag‐IL with high selectivity, indicating the possible enhancement caused by microwave irradiation. The subsequent kinetic experiments show that compared with conventional routes, the MAILE accelerated the extraction process by approximately 89.72%. As a result, the total annual cost of unit product of the overall process is reduced by 6.43% according to techno‐economic analysis by Aspen Plus, indicating that MAILE is a cost‐effective, scalable, and sustainable approach to α‐olefin separation, offering process efficiency and environmental sustainability.

Despite the rapid development of micro‐extraction technology in recent years, achieving simple and robust countercurrent micro‐extraction remains a challenge. In this study, a novel rotating micro‐extractor was developed, and robust continuous countercurrent flow can be successfully achieved in it. The effect of device structure, operation condition, and system physical properties on the hydrodynamic characteristics was investigated. Mathematical models were also established to predict the operating region of different flow patterns, the liquid layer thickness, and the maximum throughput. The throughput is up to 18 mL/min in our experimental range and can be further improved by simply increasing the pitch of the spiral microchannel. The increase in channel length will not reduce the maximum throughput, which is quite different from the reported countercurrent micro‐extractors. The unique property enables the newly developed device to achieve both high throughput and large theoretical stages and provides a promising micro‐extraction technique.

Deep eutectic solvents (DESs) were regarded as promising absorbents in many absorption processes. Here, we use randomly methylated β‐cyclodextrin (RAMEB) to further improve the absorption capacity of DESs for aromatic VOCs. We found benzene and toluene vapor pressures obviously decreased after adding 2% RAMEB (molar fraction) to DESs. Dynamic absorption experiments also confirmed this enhancement effect; the dynamic absorption efficiency for benzene and toluene increased by 6.12% and 9.23%, respectively, at a 5 mL/min solvent rate. Water was used to reduce the viscosity of DESs; the humidity and regeneration stability were evaluated experimentally. At the molecular level, the strong host–guest interactions between RAMEB and aromatic VOCs were identified as the main reason for improving the absorption capacity of DESs. Additionally, the roles of hydrogen bond donor and acceptor molecules were analyzed. π–π stacking and CH–π interactions were also identified as significant contributors to the aromatic VOCs absorption process.

The determination of the critical collision velocity for bubble coalescence plays a crucial role in predicting bubble size distribution within bubble column reactors through population balance modeling. In this study, experimental measurements in surfactant–laden systems demonstrate that even trace amounts of surfactant significantly reduce the critical velocity. We propose the Marrucci number—a dimensionless parameter derived from the Marrucci film drainage model—as a fundamental metric for quantifying surfactant effects. This parameter is formally defined as the ratio between the film drainage resistance caused by the Marangoni effect and the driving force resulting from capillary pressure. Furthermore, we developed a novel correlation for critical velocity by establishing a quantitative relationship between the critical Weber number and the Marrucci number. This correlation successfully predicts critical velocities in ethanol solutions and shows potential applicability to other systems, such as propanol solutions.

Liquid α‐olefins are important basic chemical raw materials, and the solvent extraction is one of the effective methods for their separation. In this paper, Ag⁺ is used as the coordinating metal, and NTf2−${\mathrm{NTf}}_2^{-}$, which has a weak interaction with it, is selected as the anion. Based on the interaction between the carbonyl oxygen and −NH2, propionamide is selected as the organic ligand. Thus, a deep eutectic solvent of [AgNTf2:2propionamide], with a competitive coordination mechanism for the efficient separation of olefins, was proposed. For the 1‐hexene/hexane, the selectivity is up to 215.24, and the olefin removal rate of single‐stage extraction is up to 90.55%. Using ESI‐MS and XAFS, combined with experimental and calculations, the mechanism of competitive coordination and the coordination structure of C2‐Ag‐O2 were revealed. This solvent can be used to effectively separate olefins from simulated oil, as well as effectively extract and separate unsaturated hydrocarbons such as aromatics/alkanes.

Alkali cations impose a conducive effect for acidic electrocatalytic CO2 reduction reaction (eCO2RR) to high‐value chemicals. However, the intrinsic configuration of active cations at complex electrode–electrolyte interfaces remains elusive, limiting the deployment of the cation effect. Herein, we identify the crucial effect of specific adsorption of K⁺ at electrode–electrolyte interfaces on improving acidic eCO2RR. The specifically adsorbed K⁺ occurs at electrode–electrolyte interfaces after implanting sulfonic acid groups on the system of carbon nanotubes and nickel phthalocyanine (NiPc/CNT−SO3H). Importantly, specifically adsorbed K⁺ on NiPc/CNT−SO3H generates a 2.3‐fold enhancement of acidic eCO2RR and enables attaining high CO Faraday efficiency of >90% at −450 mA cm⁻² in acid, surpassing most reported catalysts. Specifically adsorbed K⁺ residing in the inner Helmholtz plane can promote *CO2 to *COOH and disrupt the hydrogen‐bonding network connectivity, thus facilitating the eCO2RR process. This work identifies the novel feature of alkaline cations and provides an effective platform to improve electrocatalysis.

This study employs thermodynamic methods and molecular dynamics simulations to predict the CO2 absorption capacity, reaction free energies, and densities in aqueous solutions of 1‐dimethylamino‐2‐propanol (1DMA2P). By combining quantum chemical calculations and classical molecular dynamics with optimized force field parameters, the model accurately predicts solution densities, pH values, and CO2 absorption properties. The results show significant non‐ideal behavior in 1DMA2P solutions during CO2 absorption, demonstrating the reliability of the developed model for predicting reaction equilibria and absorption performance, thus providing theoretical support for carbon capture technologies.

This study provides an experimental validation of a multiple‐input multiple‐output (MIMO) model predictive control (MPC) strategy, coupled with dynamic risk modeling, to address two critical aspects of proton exchange membrane water electrolysis (PEMWE) operation: (i) process safety, by mitigating temperature imbalances, and (ii) system performance, through precise hydrogen production control. A cyber‐physical platform was developed for real‐time monitoring, state‐space modeling and validation, risk metrics analysis, control implementation, and visualization. Open‐loop experiments revealed limitations in managing thermal gradients, underscoring the need for feedback operating strategies. The proposed closed‐loop MPC approach achieved precise tracking of hydrogen production while maintaining safety by ensuring temperature stability. Moreover, the dynamic risk metrics show how thermal risk evolves with temperature and offer guidance for decision‐making. These findings demonstrate the effectiveness of MIMO MPC in enhancing the operational safety and efficiency of PEMWE systems, providing a foundation for scalable and sustainable hydrogen production.

This work proposes a novel strategy for enhancing Li⁺ extraction from salt‐lake brines with the high Mg²⁺/Li⁺ ratio using dicationic ionic liquid (DIL)‐based extractants. The ternary mixture of the DIL [DOMIM][Tf2N]2, tributyl phosphate (TBP), and dichloromethane (DCM) as a diluent achieved a higher single‐stage Li⁺ extraction efficiency (86.40%) and separation selectivity of Li⁺/Mg²⁺ (302.37) compared with the ternary mixture based on monocationic IL [OMIM][Tf2N] instead of the DIL. The high Li⁺ extraction performance could be maintained over five‐cycle regeneration. Electrolyte perturbed‐chain statistical associating fluid theory was used to qualitatively predict activity coefficients of Li⁺ and Mg²⁺ in the organic phase of the so‐called “organic–inorganic complex strong electrolyte system.” The DIL‐enhanced extraction mechanisms at the molecular level (i.e., Li⁺ extracted the form of 2Li⁺ + 3TBP + 2[Tf2N]⁻ complex) was revealed by slope analysis spectrum characters and quantum chemical calculations. This study provides guidance for the rational design of new IL‐based extractants for high‐efficiency Li⁺ extraction from brines.

The cycloaddition of CO2 and epoxides can produce high‐value cyclic carbonates. This study developed a series of hydroxyl functional imidazolium‐based poly(ionic liquid)s (PILs) by copolymerization of ionic liquids ([HeVIM]Br or [BVIM]Br), 4‐vinylphenol, and divinylbenzene. The as‐synthesized PILs were investigated as catalysts for the cycloaddition of CO2 with epichlorohydrin, and higher catalytic activity was observed over PILs with the cooperative activation effect between imidazolium and hydroxyl groups. The optimized PILs could achieve a 92.9% yield of cyclic carbonate in 2 h at 1.0 MPa CO2 and 393 K, and a considerable cyclic carbonate formation rate of 1.7–2.8 h⁻¹ at ambient reaction conditions (0.5 MPa CO2 and 303 K). Kinetic experiments and theoretical calculations indicate that the presence of a hydrogen bond network lowers the energy barrier of the ring‐opening step in CO2 cycloaddition, further facilitating the CO2 conversion over imidazolium groups.

The cumene autoxidation process holds great significance in the chemical industry. However, existing kinetic models are marred by limitations such as prolonged reaction and sampling intervals, along with the failure to account for the impact of phenol, a key substance. In this work, in the microreactor system, we successfully realized high time resolution data acquisition (5–10 min) and used it to study the effects of various factors, especially phenol, on the oxidation reaction, pointing out the obvious inhibitory effect of phenol. Further, based on the data‐driven modeling, we achieved a good prediction of the kinetics (R² > 0.9) and included phenol in the model. Finally, based on the model, we can successfully optimize and design the reaction.

The conventional hydrodeoxygenation process for sustainable aviation fuel production using Al2O3‐supported Ni‐Mo sulfide catalyst faces dual challenges: sulfur contamination and catalyst hydrothermal instability. This work develops a hydrothermally stable 5% Ni/Nb2O5‐SiO2 catalyst, where strong metal‐support interaction drives Nb to Ni electron transfer to form oxygen vacancies activating oxygen‐rich groups. The addition of SiO2 increases the specific surface area of the catalyst, while niobium oxide enhances its water resistance. The catalyst exhibits highly catalytic activity in the hydrodeoxygenation of methyl palmitate with >99% conversion and 96% liquid alkane yield, maintaining activity over a 1000‐h on a fixed‐bed continuous‐flow reactor. Furthermore, the catalyst demonstrated stable and reliable performance over a cumulative period of 500 h, comprising 240 h during the hydrodeoxygenation of palm oil and an additional 260 h of continuous operation with waste cooking oil. This work provides a green, non‐sulfur, and stable approach for the production of renewable fuels.

Photothermal CO2 hydrogenation into value‐added products represents an optimal strategy for simultaneously addressing energy and environmental crises. However, achieving high production with high selectivity for target products remains a grand challenge. Herein, we constructed an S‐scheme ZnO/CeO2 decorated by a bifunctional Pt cocatalyst. This photothermal catalyst exhibits both remarkable yield and selectivity of the CO product. The bifunctional Pt nanoparticles can effectively enhance the separation and utilization of charge carriers, facilitating this reaction. Notably, characterization techniques, in situ experiments, and theoretical simulations have demonstrated that the generation of active surface lattice oxygen and oxygen vacancies leads to a trapping effect on carbon atoms and oxygen atoms in CO, thereby playing a crucial role in modulating CO selectivity comparable to the impact of single‐atom metals. Integrating Pt nanoparticles to promote reaction and CO‐sensitive supports for improved CO selectivity offers novel insights into designing photothermal catalysts for efficient CO2 hydrogenation.

Ion‐distillation, as an innovative electro‐membrane approach, efficiently separates various ions, revolutionizing the lithium mining industry. However, the suboptimal performance of ion perm‐selective membranes and the low concentration of lithium necessitate additional separation stages, thereby increasing energy consumption in industrial applications. To address this, we propose a novel packed‐bed ion‐distillation system that integrates ion‐distillation with electro‐deionization by packing ion‐exchange resin within the ion‐distillation chambers. This strategy ensures precise lithium separation and reduces the electric resistance within the distillation chamber. Results show that when processing lake brine with a magnesium–lithium ratio of 1000, the permselectivity of Li⁺/Mg²⁺ reaches an impressive 8,124,599, with product purity exceeding 99.9%. The internal resistance of the packed‐bed system is reduced by 41% compared to a resin‐free ion‐distillation system. This technology holds significant promise for the direct and efficient extraction of lithium from lake brines, enhancing the sustainability and economic viability of the lithium mining industry.