AIChE Journal最新文献

Porous liquids (PLs) are a novel material that combines the advantages of porous solids and liquid fluidity. In this study, we propose an imprinted porous liquid (IPL) with imprinted polymers as the porous framework and a mixture of TOP + FeCl₃ as sterically hindered solvents. Quantum chemical computations and characterization results demonstrate the presence of unoccupied pore structure in IPLs. The prepared IPLs exhibit excellent selective adsorption and extraction performance for lithium extraction, achieving a Li/Mg separation factor of 1540 and a single-stage Li⁺ extraction efficiency of 86%. The Li⁺ extraction efficiency remains above 84% even after eight cycles. Analytical characterization along with quantum chemical computations elucidates the mechanism underlying the coupling between extraction and adsorption in IPLs, enabling efficient lithium extraction. By combining imprinting technology with PLs, IPLs expand upon existing frameworks for PLs materials while providing new insights for designing functional solvents.

Plastic transformations are critical to ongoing recycling and upcycling efforts, but the complexity of the reactions makes it difficult to understand the effect of individual factors on reaction rates and product distributions experimentally. In this work, we report on a multiscale simulation framework for studying polymer transformations that incorporates affordable high-level coupled cluster calculations combined with benchmarked density functional theory calculations, detailed conformer search, and lattice-based kinetic Monte Carlo simulations to provide the temporal and spatial evolution of the polymer during transformations. Our framework can match experimentally observed reaction times within an order of magnitude without any parameter estimation in base-assisted dehydrochlorination of polyvinyl chloride. We determine that the E2 reaction mechanism dominates the reaction and demonstrate that different structural defects can inhibit or promote directional polyene growth as well as affect the structure of the dehydrochlorination product.

Bicarbonate electrolysis, as a carbon utilization technology with high efficiency and potential for industrial applications, provides a promising pathway for CO₂ emission reduction. However, how to inhibit serious hydrogen evolution reaction (HER) and increase the relatively low CO₂ concentration at the electrode-electrolyte interfacial is challenging. Here, we introduce three typical aminopolycarboxylic acids (APCAs) with different amounts of carboxylic acid roots into 3 M KHCO₃ to enhance the Faradaic efficiency of CO (FE_CO) from 51.2% to 68.0% at 100 mA cm⁻². Spectroscopic characterization confirms that the role of APCAs in confining the activity of water dissociation and improving the availability of CO₂. The strategy adopted in this work that introducing APCAs into the electrolyte to balance the content of CO₂ and H₂O for improving the electrocatalytic performance, can serve as a reference for other electrocatalytic systems.

Diffusion of hydrocarbon species in an MFI-type zeolite was investigated using a coarse-grained approach combined with Kinetic Monte Carlo (KMC) simulations. The model was employed to capture and isolate the essential characteristics of hydrocarbon diffusion such as molecular pushing, passing, and blocking. A modified Lennard-Jones type forcefield was used to approximate interactions between molecules, and molecules with the oxygen in the zeolite lattice. The basis for the rate expressions is configurational diffusion theory, which has been adjusted to account for an accurate representation of the motions of hydrocarbon molecules trapped in the zeolite. Diffusion coefficients were estimated for low and high loading of single hydrocarbons as well as binary mixtures. In all cases studied, reasonable agreement was achieved with reported experimental data and molecular dynamics simulations. The model is conceptualized as an analytical tool that may be used to address key engineering topics such as applications of zeolites as size-selective barriers.

This study demonstrates fluorine-free cross-linked (meth)acrylate polymers as alternatives to polyvinylidene fluoride (PVDF) in LiNi_0.33Mn_0.33Co_0.33O₂ (NMC111) cathodes. We determine the effects of thermal initiator content, polymer content, and curing environment for two polymer chemistries: a flexible acrylate polymer, and a stiff methacrylate polymer. Electrodes are manufactured and tested for final electrochemical performance and mechanical properties. The results show that the flexible acrylate polymer exhibits higher rate capability compared to the stiff methacrylate polymer because calendering fractures the brittle network of stiff polymer. Electrode adhesion to the current collector and cohesion between particles are found to be a strong function of thermal initiator ratio and oxygen inhibition. Furthermore, there exists an optimal binder concentration that maximizes rate capability performance. Under the right conditions, the two polymers exhibit comparable performance to PVDF electrodes. These results provide important implications for designing cross-linked polymers as cathode binder alternatives to PVDF.

A universal machine learning framework is proposed to predict and classify membrane performance efficiently and accurately, achieved by combining classical density functional theory and string method. Through application of this framework, we conducted high-throughput computations under industrial conditions, utilizing an extensive database containing nearly 70,000 covalent organic framework (COF) structures for CH₄/H₂ separation. The best-performing COF identified surpasses the materials reported in the previously documented MOF and COF databases, exhibiting an impressive adsorption selectivity for CH₄/H₂ exceeding 82 and a membrane selectivity reaching as high as 248. More impressively, some of the best candidates identified from this framework have been verified through previous experimental works. Furthermore, the automated machine learning framework and its corresponding scoring system not only enable rapid identification of promising membrane materials from a vast material space but also contribute to a comprehensive understanding of the governing mechanisms that determine separation performance.

Developing the sustainable and cost-effective heterogeneous catalytic system for controlling chemoselectivity holds substantial importance in fine organic chemicals. Herein we construct a unique Zr(OH)₄ + CuO physically hybrid system for selective oxidation of anilines. Zr(OH)₄ alone leads to azoxybenzene formation, and Zr(OH)₄ + CuO shifts the reaction favorably toward nitrosobenzene. The proximity study indicates Zr(OH)₄ + CuO outperforms its counterparts synthesized through methods like ball-milling, loading, and coprecipitation, because the closer proximity exhibits stronger chemical interaction, restricting the activity of Zr-OH hydroxyl sites. Through mechanistic experiments, in situ DRIFT-IR and DFT calculations, a new Ph-$��\dot{N}�$OH intermediate mechanism is firstly proposed. Two Ph-$��\dot{N}�$OH self-condensate to form azoxybenzene for only Zr(OH)₄, whereas Zr(OH)₄ + CuO could promote rapid transformation of Ph-$��\dot{N}�$OH to nitrosobenzene on CuO through a hydrogen transfer process. Moreover, Zr(OH)₄ + CuO displays good recyclability and robust scalability. This is the first report demonstrating the utilization of a physically hybrid catalyst to adjust the selectivity of the aniline oxidation reaction.