AIChE Journal最新文献

We present high-fidelity numerical simulations of the centrifugal microencapsulation process, that is of interest for biomedical applications as cell therapy. We provide first a comprehensive rheological characterization of high-molecular-weight calcium alginate, a commonly used material in microencapsulation. Building upon this, we employ a fluid model that accurately replicates the relevant non-Newtonian properties of the fluid. This model is applied to numerical simulations of the first three stages of the centrifugal microencapsulation process: capillary flow, ejection from the capillary, and fall through the air. The results are successfully compared with experiments. Furthermore, this model, which can be adapted to various centrifugal microencapsulation devices, effectively elucidates the physical factors contributing to different capsule shapes that can be achieved at the end of the process. This breakthrough opens the door to precise control of capsule shapes and production rates.

Herein, we report a controllable and versatile strategy for the synthesis of highly dispersed Co nanoparticles embedded in open-channel hierarchically porous N/O-doped carbon skeleton. Moreover, the pore sizes of the hierarchical structures can be easily tuned by adjusting the size of precursors. The as-obtained Co@NC-2ST exhibits unprecedented activity and selectivity in the oxidative esterification of 5-hydroxymethylfurfural (HMF) to dimethyl furan-2,5-dicarboxylate under base-free and atmospheric conditions. In particular, the achieved turnover frequency value is an order of magnitude higher than that of the state-of-art heterogeneous catalysts reported to date. A combination of experimental and density function theory studies reveals that the unique features of Co@NC-2ST enable a novel reaction route, that is, the CHO group of HMF is preferentially esterified instead of the OH group. This can be attributed to the nucleophilic addition reaction caused by the attack of methoxy anion on the CHO group of HMF.

In this study, particle-resolved computational fluid dynamics (CFD) simulations were performed to analyze fluid flow, mass transport, and reaction phenomena in methanol-to-olefins packed bed reactors with diverse cylindrical configurations and operating conditions. Utilizing validated CFD data, data-driven surrogate models were developed based on several representative machine learning (ML) techniques. Comprehensive training and optimization of ML model hyperparameters were performed, followed by a comparative assessment of their capabilities to predict reactor performance. Subsequently, data-driven surrogate models together with CFD simulations were applied to optimize catalyst structure design and operating conditions. Finally, a hybrid approach was developed that couples the ML-aided data-driven model with a genetic algorithm-based multi-objective optimization. The resulting hybrid method was applied to find the Pareto-optimal compromise between pressure drop and light olefins yield.

Spherical particles stand out as high-value products with superior macroscopic properties and enhanced downstream processing efficiency. In this study, an integrated digital design strategy, combining artificial neural networks (ANN) and genetic algorithms (GA) has been employed to optimize the spherical agglomeration (SA) process. Initially, a dataset of benzoic acid SA processes was created, which was subsequently employed for training and testing the ANN model. An environmental impact sustainability index (STI) was constructed to assess the environmental effects associated with each operational variable in the SA process. To attain multi-objective optimization, a GA was employed in combination with the ANN model. In addition, a Score function was formulated to generate Pareto fronts, tailored to meet the specific needs of real scenarios, considering variations in the assigned weights. Furthermore, the model was adapted for aspirin SA process, enhancing predictive abilities with only 20% of original data on operating conditions.

Challenges in the mechanistic and kinetic study on the polymerization with multiple functional monomers hinder the scale-up for the controllable reaction process. Herein, poly (isosorbide carbonate) synthesized from isosorbide (ISB) was employed to investigate the reaction behavior of functional monomers during polymerization. DFT calculations not only determined the energetically preferable pathways but also provided explanations for the significant differences between terminal groups at the molecular level. Subsequently, the characteristic absorption bands were detected from 1000 to 1100 cm⁻¹ for hydroxyls on ISB, providing a quantitative measure for asymmetric hydroxyls. The reaction network indicated that the reactivity was dominated by the types of terminal groups instead of the chain length. Thereafter, a functional group model with six kinetic parameters was built, acting a crucial role in reaction control and reactor design. This method can be promoted to other functional monomers, conducing to the industrialization of high-performance polymers.

Porous liquids (PLs) with unique porous frameworks and good flow properties can achieve coupling enhancement for CO₂ capture and conversion. In this paper, a series of novel PLs were designed and synthesized using UiO-66 as the framework and novel bi-cationic ionic liquids (ILs) as an excluded solvent. The prepared PLs showed significant improvement in CO₂ uptake capacity over ILs at different pressures and exhibited excellent CO₂ catalytic conversion performance, exceeding the sum of the effects of ILs and UiO-66. Especially at low pressure, the PLs still showed excellent catalytic performance, but the catalytic performance of the corresponding ILs was significantly reduced, which was due to the rapid adsorption and conversion of CO₂ by the porous framework of UiO-66 to improve the CO₂ uptake and transfer efficiency within the ILs, thus achieving coupling enhancement. It can provide a new way to realize the efficient conversion of CO₂ under milder conditions.

Due to size limitations, the gas–liquid absorption capacity of a single microchannel is limited, making it difficult to achieve large-scale CO₂ capture. Therefore, the parallel microchannels combining the advantages of high efficiency and large throughput stand out. However, when the operating condition is high gas–liquid flow rate ratio, the liquid phase between bubbles almost disappears after multiple distributions, which affects the amount of gas–liquid absorption. In this study, the numbering-up of the asymmetric parallel microchannels in the gas–liquid absorption process was investigated by splitting the liquid feed stream in two. The flow patterns under different operating conditions were obtained. The flow and distribution of gas–liquid two-phase flow were investigated, and the reason of the distribution deterioration caused by appearance of long slug bubbles was explained by the pressure drop distribution. The total liquid mass transfer coefficient and bubble residence time were derived and obtained, and the mass transfer was further discussed.

Strongly oxidizing ·OH can non-selectively degrade various organic pollutants, but how to selectively generate ·OH is a great challenge. In this study, the directed generation of ·OH was achieved based on Ni–Ca metastable–nonmetastable bimetallic sites, Ni²⁺/Ni³⁺ valence cycling provided electrons for ·OH generation induced by the non-variable Ca-based sites, which constructed a nearly 100% selective generation pathway of ·OH (O₃ → HO₃/HO₂ → OH). The antibiotic pefloxacin could be completely removed in 15 min, and the COD removal efficiency for other hard-to-degrade pollutants such as oxalic acid and chlorobenzoic acid could reach more than 90%. Ni doping significantly increased the oxygen vacancy and Lewis acid content, and DFT calculations showed that Ni–Ca dual-site had a lower reaction energy barrier and the complexed hydroxyl radical intermediate *OO had a higher spin density (−0.6), which was more favorable for the generation of ·OH. Therefore, this study provides new ideas for efficient treatment of actual wastewater.

Split-and-recombine (SAR) microreactor is an advanced reactor for chemical process intensification. Bubble flow in the SAR microchannel is an important phenomenon that affects reaction efficiency, however drew little attention before. This study aims to explore the underlying mechanisms of bubble splitting, retraction, and breakup behaviors in a compact SAR microchannel. Two breakup flow patterns, unilateral flow and unilateral alternate flow were identified with symmetric or asymmetric splitting, respectively. Mechanism analysis indicates that the splitting symmetry issue is related to liquid slug size, viscous effect and novel retraction behavior of a splitting filament. The retraction is induced by the interconnection and unequal pressures between the splitting filaments. The correlation between normalized breakup time and Ca number confirms the Capillary-pressure breakup mechanism for the splitting gas filaments. Two empirical correlations for the two breakup flow patterns were proposed, which illustrate the significant contribution of bubble retraction to the breakup degree.

For low-pressure pervaporation, the performance of spiral wound pervaporation membrane (SWM-PV) module is significantly influenced by permeate spacer structure. This study addresses mass transport challenges in SWM-PV modules, focusing on increased gas flow resistance and vacuum attenuation due to membrane envelope deformation in the permeate side channel. Employing fluid and structural simulation models to evaluate phase change and membrane deformation, we successfully optimized SWM-PV module configurations for improved ethanol recovery. Our strategies included a mass transfer-enhanced feed spacer to mitigate concentration polarization, a high-strength permeate spacer to alleviate membrane deformation, and tailored membrane envelopes to balance packing density and mass transfer efficiency. These synergistic optimizations led to a 22.1% improvement in ethanol mass transfer coefficient and a 78.5% reduction in module's specific energy consumption. Our work reveals the importance of permeate spacer structure in optimizing SWM-PV modules, offering clear guidance for the development of mass transfer-enhanced SWM-PV modules.