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The mesoporous carbon-supported metal catalysts are important materials in heterogeneous catalysis. From the standpoint of process intensification, the current synthesis methods still suffer from several issues, such as the excessive use of toxic solvents, the time-consuming self-assembly process, and the difficulty of continuous production. Herein, we report a solvent-free and continuous route to synthesize mesoporous carbon-supported metal catalysts. Interestingly, the use of cyclic extrusion could promote the mixing, coordination, and assembly of catalyst precursors (tannin-metal salts-additives) by shearing and squeeze force. The as-made mesoporous carbon-supported nickel showed high surface areas (up to 512m2g-1), narrow pore size distribution (~10 nm), and good performance in the selective hydrogenation of nitrobenzene to aniline (Conv.>99%; Sel.>99%). In addition, the fluid property of catalyst precursors and the geometry of the twin-screw extrusion channel were studied, and the essence of this cyclic extrusion process is also discussed.

Deterministic structure representation of polymers plays a crucial role in developing models for polymer property prediction and polymer design by data-centric approaches. Currently, unique structure representations of polymers, especially the polymers with heteroatomic backbones, are unavailable. In this contribution, we propose a so-called ring repeating unit (RRU) method that can uniquely represent polymers with a broad range of structure diversity. To prove the rationality of RRU-based structure representation for generating feature descriptors, a quantitative structure property relationship (QSPR) model for glass transition temperature (Tg) was established for 1321 polyimides with good accuracy (R2 = 0.8793). Comprehensive model validations including external, internal, and Y-random validations were performed, providing Tg prediction result with an average absolute error (AAE) of 19.38 ℃. It is believed that the as-developed RRU method allows for dealing with any macromolecular structure and targeted property, enabling for reliable polymer property prediction and high-performance polymer design by data-driven approaches.

The effect of fluid turbulence models on the coarse-grid simulation for the mesoscale gas-solid flow system is not as clear as that for gas-liquid/single flows. In this study, the effect of different turbulence models on predictions of riser-only, turbulent and bubbling flow hydrodynamics is quantified. Then the selected turbulence models are examined by coarse-grid simulations in a full-loop circulating fluidized bed (CFB) with a proposed hybrid drag model which integrates two SGMs and Hulin-Gidaspow model. Results show that the standard k-epsilon and k-omega models fail to capture a correct fluidization pattern in riser. Meanwhile, the RNG and realizable k-epsilon models and SST k-omega model enable satisfactory predictions which are highly comparable to discrete model predictions and experiments over different flow regimes. However, the realizable k-epsilon model produces more pronounced flow fluctuations causing computational instability. Using superior turbulence closures, full-loop simulations with the proposed hybrid model can predict desirable hydrodynamics.

The adipic acid is an important intermediate in the production of nylon, polyurethane and polyester resins. The industrial approach for preparing adipic acid is through the liquid catalytic oxidation of KA oil with nitric acid. In this work, a comprehensive model is developed for this reaction based on the kinetic study conducted in a continuous flow tubular reactor. The kinetic model fits well with the experimental results across the experimental conditions, and the average relative error between the calculated and experimental values is 5.7%. Results show that there was an induction period at the early stage of reaction. Moreover, it is found that at temperature range of 328–358 K, the formation rate of adipic acid strongly dependents on the temperature and nitric acid concentration. The developed model is used to predict the yield of adipic acid at 359–368 K. The work in this study could provide much knowledge for industrial tubular reactor design.

One of the challenges for modelling of polymerization kinetics is the detailed description of the molecular build-up of both linear and non-linear chains, specifically those with many grafts and crosslinks. Such grafted/crosslinked (co)polymers are relevant as emulsifiers, surface-modifying agents, coating materials, and compatibilizers. In the present work, we put forward a coupled matrix-based Monte Carlo (CMMC) concept to be successful in this respect, avoiding computational stiffness. The CMMC concept is illustrated for single phase grafting of polybutadiene (PB) with styrene (St) at 343 K by limiting the St conversion to 30%. Considering literature kinetic parameters, a benchmark for average characteristics as obtainable by deterministic method of moments simulations is first presented to then gradually extend the level of modelling output addressing (i) conventional grafting performance indicators (e.g. the grafting yield and mass ratio); (ii) univariate chain length distributions for all macrospecies types (polystyrene, PB, PB with only T grafts, PB with at least one H graft, etc.); (iii) bivariate St–butadiene distributions showing a compositional drift, due to the kinetic tendency to attack longer chains if they are sufficiently present and the competition between grafting and crosslinking; (iv) the explicit molecular build-up of individual molecules predicting the positioning of the St–Bd and St–St connectivity points and the chain formation history. It is demonstrated that the CMMC tool allows the simulation of the contribution and structure of molecules that are hard to access purely experimentally, so that in the long run, novel structure–property relationships are within reach. It is also showcased that consideration of elementary reactions is highly recommended and that even at 343 K, thermal self-initiation with St and related chain transfer reactions matter for a full appreciation of molecular variations. The current work also opens the pathway to identifying pragmatic equations for the experimentalist and online control benefiting from a detailed CMMC solution under any desired conditions.

The quantification of dispersity is an indispensable part of characterizing polymers. In this work, general dispersity equations for “living” polymers obtained by nitroxide-mediated polymerization ...

In this work, the effect of non-drag forces (lift force, turbulent dispersion force, wall lubrication force and virtual mass force) and bubble induced turbulence (BIT) on the CFD-PBM simulation of ...

The kinetics of the ultraviolet light-induced solution atom transfer radical polymerization (ATRP) of methyl acrylate using titanium oxide (TiO2) was investigated through experiments and modeling b...

For designing and operating fluidized bed reactors, bed expansion ratio is one of the most important parameters. In this research, a bubbling fluidized bed is simulated using three-dimensional Eulerian-Eulerian method that is incorporated with kinetic theory of granular flow (KTGF) to calculate the pressure drop, gas volume fraction (GVF) and bed expansion ratio. Grid optimization is firstly conducted to achieve suitable solution for further simulations. Subsequently, different numerically derived drag models are employed to investigate the effect of these models on gas-solid flow dynamics. Afterwards, the fluidized bed is simulated at different gas superficial velocities employing two different drag models respectively. Simulation results have been comprehensively validated against experimental data. Finally, an expression for bed expansion ratio has been formulated and compared with the empirical correlation. The proposed correlation holds reasonably well with various experimental values. This work provides a scalable way to aid in designing and operating process reactors.

In this work, a three-dimensional coarse-grid two-fluid model (TFM) simulation by varying granular properties like granular viscosity, frictional viscosity, and solids pressure has been performed. Simulated predictions were subsequently compared with experimental results in the case of Geldart A or B particles. Laminar flow behavior is also studied and coarse-grid simulation predictions were less realistic for laminar flow. This flow regime which although consumes less computational resources falls short for large-scale riser scale up. Flow regime in our simulation was fast fluidization and simulation predicts with minimum error near riser inlet. More specifically, granular viscosity, frictional viscosity and solids pressure for Type A particles predict with minimum error especially near riser inlet at a lower height. For Type B particles, these three solid properties correspond closely with experimental results near inlet at a lower height whereas, at a higher height, turbulence increases and simulation results deviate from experimental studies.

This work aims at comparing surface tension models in VOF (Volume of Fluid) modeling and investigating the effects of gas distributor and gas velocity. Hydrodynamics of a continuous chain of bubbles inside a bubble column reactor was simulated. The grid independence study was first conducted and a grid size of 1.0 mm was adopted in order to minimize the computing time without compromising the accuracy of the results. The predictions were validated by comparing the experimental studies reported in the literature. It was found that all surface tension models can describe the bubble rise and bubble plume in a column with slight deviations.

Particle-resolved (PR) high-fidelity simulations, e.g., direct numerical simulation (DNS), have emerged as a powerful tool to precisely capture the full details of complex fluid-particle heat and mass transfer behaviors. The captured information can be used to constitute closures for unresolved conservation equations. However, such simulations are commonly performed under a specific variety of operating conditions. To broaden the range of closure model applicability, this fundamental study develops an enhanced correlation for the gas-particle transport rate in terms of Nusselt (Sherwood) number via collecting data points (e = [0.35, 1], Rep = [0, 550]) from open sources. The collected data are predicted with a mean relative error of 9.3%. The extended correlation is then systematically validated by comparison with experimental data and PR-DNS results. Finally, the correlation is applied to integrate with a macroscopic computational fluid dynamics (CFD) reactor model. Validation results reveal an enhanced improvement in mass and heat transfer predictions. Moreover, the overall thermal and reactive behaviors computed from the coupled reactor model achieve reasonably good accordance with PR-DNS predictions over various process conditions. The developed correlation is hopeful to improve the accuracy of coarse-grained simulation of interphase heat and mass transfer accompanied by heterogeneously catalyzed chemical reaction.