AIChE Journal最新文献

Solid oxide cells (SOCs) are a promising dual-mode technology for the production of hydrogen through high-temperature water electrolysis, and the generation of power through a fuel cell reaction that consumes hydrogen. Switching between these two modes as the price of electricity fluctuates requires reversible SOC operation and accurate tracking of hydrogen and power production set points. Moreover, a well-functioning control system is important to avoid cell degradation during mode-switching operation. In this article, we apply nonlinear model predictive control (NMPC) to an SOC module and supporting equipment and compare NMPC performance to classical proportional-integral (PI) control strategies, while switching between the modes of hydrogen and power production. While both control methods provide similar performance across various metrics during mode switching, NMPC demonstrates a significant advantage in reducing cell thermal gradients and curvatures (mixed spatial-temporal partial derivatives), thereby helping to mitigate long-term degradation.

Electrocatalytic nitrite reduction (e-NO₂⁻RR) offers an attractive strategy for industrial green ammonia synthesis. The understanding of electrochemical kinetics is the core to guarantee the efficient operation of e-NO₂⁻RR system. However, the application of the widely used Butler–Volmer equation should be restricted to the constraint of non-mass transfer effects. In this work, an electrochemical macrokinetics equation for mass transfer restriction region was developed based on the traditional macrokinetics thought, which combined the Practical Butler–Volmer equation and Nernst-Plank equation. The model validation was carried out by the combination of multiphysics-field simulation, computational fluid dynamics simulation and experiments, and the results show that the average relative error between experiments and simulations is less than 2%. The results in this article contribute to an in-depth understanding of the kinetics behavior for e-NO₂⁻RR and achieve the extension of electrochemical kinetics equation from non-mass transfer restriction region to mass transfer restriction region.

Heterogeneous catalytic ozonation (HCO) emerges as a promising chemical industrial wastewater treatment solution, offering enhanced ozone utilization and reduced secondary pollutants. However, challenges in scaling HCO arise from a limited understanding of the catalytic mechanisms of metal oxides, particularly in generating active ozone sites. Here, we demonstrated the improvement of catalytic ozonation efficiency by enhancing the covalent bonding between FeO in Fe/Co spinel oxides. This alteration exploits the stronger electron-donating capacity of Fe (II), enhancing FeOM bonds and electron enrichment at iron sites, leading to a significant reduction in the activation energy for ozone. Pilot experiments demonstrated a 75.3% COD removal efficiency and a threefold increase in ozone utilization efficiency compared to pure ozone system for chemical industrial wastewater treatment. This study not only advances our understanding of spinel oxides in ozone catalysis but also opens new avenues for practical HCO applications in water treatment.

The molecular mechanisms that drive adsorption are critical for engineering new adsorbents to capture environmental contaminants, such as perfluoroalkyl substances (PFAS). Metal–organic frameworks (MOFs) have been shown to adsorb some classes of PFAS, yet a fundamental understanding of how PFAS identity and water competition affect adsorption capacity is unknown. Here, grand canonical Monte Carlo simulations of perfluoroalkanoic acids (PFAAs) adsorption in the MOF NU-1000 were performed with coadsorbed water and varying carbon chain length sizes to interrogate how PFAS structure affects adsorption capacity. We found that larger PFAAs adsorb favorably into NU-1000 than shorter chain PFAAs due to the formation of pore-filling aggregates that stabilize anionic adsorption to the node. Due to their size and hydrophilicity, shorter chains tend to limit interactions with the adsorbent. These insights offer directions for developing novel materials that promote aggregate formation to capture and retain a wider set of PFAS from aqueous solutions.

Titanosilicate with H₂O₂ stands out as a highly consequential oxidized catalytic system, prized for its user-friendly operation, mild conditions, and eco-friendly attributes. However, a synthesis strategy for large surface area titanosilicalites approaching the theoretical lowest Si/Ti ratio without extra-framework Ti species remains an ongoing challenge. In this study, we successfully synthesized single-crystalline Ti-rich nanosized aggregated TS-1 by shielding effect with a Si/Ti polymer. This polymer demonstrated effectiveness in restraining TiO₂ species by regulating the proximity of Si/Ti species in Ti-Diol-Si polymers. The polymer not only facilitated the synthesis of single-crystalline Ti-rich TS-1 but also exploited the chain length of PEG, functioning as a shielding cage by hydrogen bonds, to synthesize nanosized aggregated TS-1 (TS-1-PEG400). This TS-1-PEG400 exhibited superior conversion (~60%), selectivity (~90%), and stability in 1-hexene epoxidation. This study not only establishes a synthesis pathway for Ti-rich TS-1 but also holds the potential to enhance related industrial oxidation reactions involving titanosilicates and H₂O₂.

Ionic liquids (ILs) are promising solvents for separating aromatics from fuel oils. However, studies for separate polycyclic aromatics with ILs are rare and insufficient, and the impact of solute structure on extraction performance still needs to be determined. In this work, we use 1-ethyl-3-methylimidazolium bis([trifluoromethyl]sulfonyl)imide ([EMIM][NTF₂]) as an extractant to separate 1-methylnaphthalene, quinoline, and benzothiophene from dodecane mixtures. Liquid–liquid equilibrium experiments identified the optimal operating conditions. Nine solute molecules, including five alkanes and four aromatic hydrocarbons, were used to study the relationship between extraction performance and solute structure. Molecular dynamics simulation and quantum chemistry calculations gave a deep insight and reasonable interpretation of the structure-performance relationship at the molecular level. An industrial-scale extraction process was proposed. The IL can be easily regenerated using heptane as a back-extractive solvent. A high-purity fuel oil with aromatic content below 0.5 wt% is obtained after 8-stage extraction.

The influence of silo width on dense granular flow in a two-dimensional silo is investigated through experiments and simulations. Though the flow rate remains stable for larger silo widths, a slight reduction in silo width results in a significant increase in flow rate for smaller silo widths. Both Beverloo's and Janda's formula accurately capture the relationship between the flow rate and outlet size. Flow characteristics in the regions near the outlet exhibit local self-similarity, supporting Beverloo and Janda's principles. Moreover, global self-similarity is analyzed, indicated by the transition in flow state from mass flow in regions far from the outlet to funnel flow near the outlet. The earlier occurrence of this transition favors to enhance the grain velocity and consequently increases the dense flow rate. An exponential scaling law is proposed to describe the dependencies of flow rate, grain velocity, and transition height on silo width.

Precise control over sequence structure in copolymers is essential for chemical product engineering. The complexity of sequence structures results in the challenging characterization of monomer sequences. Herein, a chemical composition model (CD model) is developed to record the distribution density of monomers in the chain segment, where the deviation of the chemical composition function between a copolymer and its ideal sequence structure can directly map the sequence structure quality. The application of the CD model in randomly generated virtual copolymers demonstrates that the model has great sensitivity and discrimination to evaluate sequence structures accurately. Furthermore, the CD model is combined with the kinetic Monte Carlo algorithm to explicitly track the evolution of sequence structure quality in the copolymerization process. The CD model provides an insight into the evolution of sequence structure, which is conducive to building the bridge between molecular structure and properties for the development of chemical product engineering.

Polymer crystal hydrates (PCHs) are crystalline solids that form between a polymer and water. To date, only four distinct PCHs have been discovered—one of polyoxacyclobutane (POCB) and water, and three different polymorphs of polyethyleneimine (PEI) and water. These PCHs were first reported decades ago and have fascinating structures and peculiar properties that make them potentially useful for a wide range of applications including refrigeration, proton conduction membranes, and desalination. This perspective revisits what is known about these compounds, categorizes their similarities and differences with other known compounds, and offers a perspective into future efforts to discover new PCHs to address technological needs for society.

Reducing emissions requires transitioning towards decarbonized systems through avoiding, processing, or offsetting. Decisions on system design are associated with high costs which can be reduced at the planning stage through optimization. The temporal variations in power demand and renewable energy supply significantly impact the design of a low-emissions energy system. Effective decision-making must consider such impact in a comprehensive framework that accounts for the potential synergies between different options. This work presents a mixed integer linear programming model that considers the impacts of energy supply and demand dynamics to optimize the design and operation of an integrated energy system while adhering to a set emissions limit. The model integrates renewable power with CO₂ capture, utilization, and sequestration by considering H₂ production and storage. The case study showed including negative emissions technologies and CO₂ capture and processing with renewable energy allows achieving net zero emissions power.