Chemical Engineering Science最新文献

Chemical looping gasification (CLG) for combined hydrogen production and carbon capture represents a significant pathway for the clean, low-carbon utilization of traditional fossil fuels. Currently, a significant knowledge gap remains concerning the interplay between reactor configuration optimization and the complex gas–solid interactions in the CLG systems. This study integrates reactive computational fluid dynamics-discrete element method (CFD-DEM) simulations with a coarse-grained model (CGM) to analyze 3D coal-based CLG systems. The spatiotemporal distributions of gas–solid flow dynamics and thermochemical characteristics are revealed. It is found that increasing the gasifier height enhances fuel conversion and hydrogen production but compromises CO₂ absorption. Smaller reactor diameters induce excessively rapid gas–solid flows, leading to incomplete fuel conversion and reduced hydrogen yield, while larger diameters cause uneven flows, significantly deteriorating hydrogen production and carbon absorption efficiency. Based on the simulation findings, the optimal height-to-diameter ratio for the gasifier in a CLG system is approximately 28.8, optimizing H₂ production while maintaining efficient CO₂ absorption. Moreover, the superficial gas velocity has a multifaceted influence on the hydrogen production and carbon reduction performance in the CLG process, necessitating a comprehensive consideration of its effects on fuel reaction time, gas–solid interactions, and other factors.

In the Fischer–Tropsch synthesis (FTS) reaction, the intricate reaction conditions are prone to induce phase transitions in iron carbides, which markedly affect catalytic performance. Manipulating and stabilizing the active phase is paramount for ensuring the catalyst efficiency. In this study, we regulated the Fe-Zn interaction to investigate the influence of iron carbides and the characteristics of surface carbon species. The strong interaction significantly enhanced the adsorption and dissociation of CO on the catalyst surface, thereby facilitating the formation of carbon-rich Fe_2(.2)C. Consequently, the FeZn-s catalyst exhibited the highest iron time yield (FTY) of 959 μmol_CO·g_Fe^-1·s^-1. But meanwhile, the stronger Fe-Zn interaction also accelerated the carbon deposition rate and elevated the graphitization degree of the surface carbon, expediting the catalyst deactivation. These results provide an insight into the modulation and stabilization of iron carbides by adjusting the interaction between the Fe and supports, which inspires the further development of Fe-based catalysts for FTS applications.

Transport diffusion of the quaternary mixture cyclohexane + toluene + acetone + methanol and most of its binary and ternary subsystems at ambient conditions of temperature and pressure is studied by molecular dynamics simulation. Liquid-liquid phase separation of cyclohexane + methanol extends into the according ternary and quaternary mixtures, rendering them highly non-ideal. Maxwell-Stefan diffusion and intradiffusion coefficients are predicted with the Green-Kubo formalism, while the thermodynamic factor is sampled with Kirkwood-Buff integration. From these data, the Fick diffusion coefficient is determined and thoroughly compared with experimental literature values. Given that the simulation results for all binaries, one of the ternaries and the quaternary mixture are successfully validated, it can be assumed that the results for the three remaining ternary mixtures, for which no experimental data exist, are sound, too. These three ternaries exhibit non-idealities that entail Maxwell-Stefan diffusion coefficient maxima that are accompanied by Fick diffusion coefficient minima due to the thermodynamic factor. Particularly the very different nature of cyclohexane and methanol molecules, where the latter strongly self-associate, leads to anomalies. The predictive models by Li et al. (2001) and Allie-Ebrahim et al. (2018) for binary and ternary mixtures, respectively, are found to yield good results for predicting the Fick diffusion coefficient of these challenging systems.

The transport of mRNA plays an indispensable role in vaccine drug delivery and emerging therapies. The attachment of lipid nanoparticle encapsulating mRNA (mRNA-LNP) to biological and engineering surfaces is determined by their intermolecular and surface interactions. In this work, the interactions between mRNA-LNP and surfaces with various functional groups were investigated using atomic force microscopy. The results show that mRNA chains are coiled in LNPs, and the surface charges of mRNA are screened by the surrounding lipid molecules. Approach force curves demonstrate that the steric repulsion varies with functional groups. Force mapping reveals that the intermolecular interactions, i.e., hydrogen bonding and electrostatic interaction, contribute to the adhesion. The –OH group is suggested as the most probable binding site for mRNA-LNP attachment. This work provides new insights into mRNA transport mechanisms at biological and engineering surfaces, with useful implications for designing novel nanocarriers and developing functional surfaces for biological applications.

Gas-liquid capillary flow finds widespread applications in reaction engineering, owing to its ability to facilitate precise control and efficient mixing. Incorporating compact and regular design with Coiled Flow Inverter (CFI) enhances process efficiency due to improved mixing as well as heat and mass transfer leading to a narrow residence time distribution. The impact of Dean and Taylor flow phenomena on mixing and dispersion within these systems underscores their significance, but is still not yet fully understood. Direct numerical simulation based on finite element method enables full 3D resolution of the flow field and detailed examination of laminar flow profiles, providing valuable insights into flow dynamics. Notably, the deflection of flow velocity from the center axis contributes is followed by tracking of particle with defined starting positions, aiding in flow visualization and dispersion characterization. In this CFD study, the helical flow with the influence of the centrifugal force and pitch (Dean flow) as well as the capillary two-phase flow (Taylor bubble) is described and characterized by particle dispersion and related histograms. Future prospects in this field include advancements in imaging techniques to capture intricate flow patterns, as well as refined particle tracking methods to better understand complex flow behavior.

The thermal decomposition of PFOA was studied in an α-alumina reactor between 400 and 1000 °C under two separate conditions: 1) in a bath gas of air and water vapor (H₂O_(g)) and 2) in a bath gas of helium, nitrous oxide (N₂O) and H₂O_(g). PFOA decomposition studies undertaken under these conditions, both experimental and modeling analysis, provided insightful information on the conditions leading to the formation of products of incomplete destruction (PIDs).

The combination of O₂ from air or O from N₂O decomposition, combined with H₂O_(g), resulted in complete mineralization of PFOA at temperatures above 950 °C into HF and CO₂. An elementary mass balance of F and C atoms concluded that, at 1000 °C, 105 ± 10 % of F atoms present in PFOA are converted into HF, while 100 ± 5 % of C atoms into CO₂. Both H₂O_(g) and oxygen together are necessary for complete mineralization.

Due to the unreliability of the mechanical seal of the mechanical stirring reactor in traditional carbonyl synthesis reactions, a gas–liquid jet bubbling reactor has been developed that is a new type of hydraulic stirring. A cold model device was constructed to address the complex flow field characteristics of a gas–liquid jet bubbling reactor, and a gas–liquid phase testing method was established to obtain the gas–liquid phase flow parameters in the cold model device. A mathematical model of a cold model device was established based on computational fluid dynamics. The reliability and accuracy of the calculation model were verified by combining experimental data of the cold model device, and the gas–liquid two-phase flow characteristics of an industrial grade reactor were obtained. The multiscale characteristics of gas–liquid two-phase signals in industrial reactors and the multiscale gas–liquid two-phase interactions were analyzed by combining wavelet analysis, power spectrum analysis, and fractal analysis. Based on the multiscale gas–liquid interaction mechanism model of gas–liquid interaction, the liquid phase interaction in d1-d6 inside the reactor was increased. The gas–liquid mass transfer process was enhanced, and the liquid level fluctuation and temperature difference of industrial grade reactors were significantly reduced.

A simple polycondensation process M_i + M_j ⇄ M_i+j + Z, proceeding in dispersion of nano-scale droplets was described by analytical solutions and differential equations giving insight into equilibrium and kinetics of the process. Stochastic and deterministic simulations show that the statistical nature of polycondensation, both irreversible and reversible one, affects the way the macromolecules of different lengths are formed and distributed among droplets. The droplet distributions in respect to the number of reacting chains and the chain length distributions depend, for the given conversion, on the polycondensation equilibrium constant K_cond and the initial conditions: monomer concentration and the number of its molecules in a droplet. The apparent equilibrium constants of condensation ${\overline{K}}_{\mathrm{ij}}=\left({\overline{\left[{\text{M}}_{i+j}\right]}}_e{\overline{\left[\text{Z}\right]}}_e\right)/\left({\overline{\left[{\text{M}}_i\right]}}_e{\overline{\left[{\text{M}}_j\right]}}_e\right)$ depend on oligomer/polymer sizes as well as on the initial number of monomer molecules in a droplet. This apparent violation of the law of mass action was explained by stochasticity of involved processes. Moreover, when the polycondensation byproduct Z is being removed reversibly from the system, ${\overline{K}}_{\mathrm{ij}}$ depends also on average equilibrium concentration ${\overline{\left[\text{Z}\right]}}_e$. The indicated effects are observed not only for ideally dispersed systems (all droplets contain initially the same number of monomer molecules), but also when the initial numbers of monomer molecules conform the Poisson distribution. However, the chain length distribution as well as kinetics and ${\overline{K}}_{\mathrm{ij}}$ differ here from those observed for systems with uniform distribution.

Catalytic cracking by noble metals is an effective strategy to enhance the cooling capacity of endothermic hydrocarbon fuels (EHFs), but microscopic reaction mechanisms of noble catalysts assisted fuel cracking remain to be elucidated. The reactive molecular dynamics simulation (ReaxFF MD) was employed in this work to investigate the catalytic mechanisms of Pt and Pd in the cracking of a surrogate EHF, i.e. n-dodecane. The results demonstrate that both Pt and Pd catalysts can significantly reduce the apparent activation energies for overall pyrolysis, while Pd demonstrating 72 % superior reduction performance due to the higher absorption with reactants. Specially, excessively high temperatures may lead to catalyst deactivation. With metal catalyst included, the gas-phase product yield and the proportion of hydrogen dominate production increases, which can be ascribed to additional dehydrogenation reactions during the initial cracking of n-dodecane by Pt and Pd, resulting in more H₂ and C₂H₄ formation.

The long-term objective of tandem reaction is to investigate ‘intelligent’ tandem reaction systems akin to living cells. Here we’ve prepared an ‘intelligent’ droplet microreactor for the tandem reaction using droplet microfluidic technology constructing a photoresponsive microfluidic tandem reaction system. The method leverages a three-phase emulsion’s ‘two membranes and three phases’ structure to segregate incompatible reagents, and introduces a stimulating surfactant to control the structure of this emulsion structure for intelligent reaction sequence control, enabling efficient, orderly tandem reaction within the same system. Validating this concept, we applied the droplet microreactor to the condensation-reduction cascade reaction, as envisioned, incompatible condensation and reduction reactions, were coordinated by cycling the UV light on /off for a smooth cascade reaction. Compared to batch reaction, the droplet microreactor showed sixfold catalytic efficiency enhancement and > 99 % reaction selectivity. Our work offers novel insights into realizing intelligent cascade reactions.