In this study, a CFD mathematical model has been developed for catalytic fast pyrolysis (CFP) of biomass. The multi-phase fluid flow, and the inter-phase momentum and energy transfer processes were modelled with Eulerian multi-phase formulas. The biomass catalyst fast pyrolysis reactions were described by using a two-stage, semi-global model. Specified secondary tar catalytic cracking process, which considers both intrinsic reaction rates and mass transfer process are embedded to the developed model by user-defined function (UDF). The developed model has then been employed to investigate the effects of structural properties of catalyst, such as specific internal area, average size of active sites, pore diameter, and tortuosity, on products yields and composition. The influences of adsorption capability of tar molecule on catalyst surface and external film mass transfer were also analyzed. The developed model can be employed for further research and engineering designs of the catalyst pyrolysis of carbonaceous materials.

The mass transfer between a rising bubble and the surrounding liquid is mainly determined by an extremely thin layer of dissolved gas forming at the liquid side of the gas-liquid interface. Resolving this concentration boundary layer in numerical simulations is computationally expensive. Subgrid-scale models mitigate the resolution requirements enormously and allow approximating the mass transfer in industrially relevant flow conditions with high accuracy. However, the development and validation of such models is difficult as only integral mass transfer data for steady-state conditions are available. Therefore, it is difficult to assess the validity of the sub-grid models in transient conditions. In this contribution, we compare the local and global mass transfer of an improved subgrid-scale model for rising bubbles (Re = 72-569 and Sc = 10^2-10^4) to a single-phase simulation approach, which maps the two-phase flow field to a highly-resolved mesh comprising only the liquid phase.

We review theories of polyelectrolyte (PE) coacervation, which is the spontaneous association of oppositely charged units of PEs and phase separation into a polymer-dense phase in aqueous solution. The simplest theories can be divided into “physics-based” and “chemistry-based” approaches. In the former, polyelectrolytes are treated as charged, long-chain, molecules, defined by charge level, chain length, and chain flexibility, but otherwise lacking chemical identity, with electrostatic interactions driving coacervation. The “chemistry-based” approaches focus on the local interactions between the species for which chemical identity is critical, and describe coacervation as the result of competitive local binding interactions of monomers and salts. In this article, we show how these approaches complement each other by presenting recent approaches that take both physical and chemical effects into account. Finally, we suggest future directions towards producing theories that are made quantitatively predictive by accounting for both long range electrostatic and local chemically specific interactions.

Toluene diisocyanate (TDI) is an important chemical intermediate prepared by phosgenation reaction between toluene diamine and phosgene with two steps name cold and thermal phosgenation respectively. In this paper, the reactive distillation model for the thermal phosgenation reaction based the kinetics equations was established for an industrial installation, and the effects of the different parameters on the process performance were studied firstly; then based on the analysis results, a thermal coupling process between the towers of reactive distillation and phosgene purification was presented and investigated; finally, the optimal operation scheme was simulated and the results showed that the proposed process can save the heat and cold energy with 7.29% and 32.78%, respectively, and reduce the total annual cost about 17.11%. The result of the paper can be used to guide the operation configuration or the revampment of the TDI production equipment.

The degree of rate control quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, e.g. with finite differences. Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this work, we demonstrate the use of automatic differentiation in the evaluation of the degree of rate control. Automatic differentiation libraries are increasingly available through modern machine learning frameworks. Compared to the finite differences, automatic differentiation provides solutions with higher accuracy with lower computational cost. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis (DELSA), to assess the importance of kinetic parameters over an uncertain space. This method also benefits from automatic differentiation to obtain high-quality results efficiently.

The work reported in this investigation involves the determination of the hydrodynamic properties of the Trickle Bed Reactor which has been loaded in various ways to mark the effect of the loading methodologies employed to pack the catalyst pellets. The bed structure of a packed three-phase reactor is critical to study as it provides the essential contact between the phases and provides the catalytic sites where the reaction takes place. Depending on the structural properties of the bed such as local void structure, liquid distribution, two-phase pressure drop, and holdup of fluids gets affected. The study aims to envelop the catalyst bed characteristics such as the local void structure, the length of the catalyst bed, flow characteristics such as liquid and gas flow rate, and liquid distributor at the top of the catalyst bed to gauge and quantify their effect on the hydrodynamics of a trickle bed reactor.

The dynamic pH response resulting from acid-base transport of interfacial reactions greatly influences the kinetic performance and process mechanism, but its theoretical foundation is lacked. Herein, a generalized acid-base transport model is established owing to the success in deriving buffer transport equations and is experimentally through the relationships of buffer transport limiting current versus solution pH and buffer concentration (CB). The relationships bring forth the parameter determination methods of buffers with the superiority of facile survey of practical parameter values. Based on model calculations, the dynamic pH response is drawn as a j‒pH diagram to show the buffer transport law in the full pH range, highlighting the rate-limiting effect. The buffer operation principles are graphically presented as CB‒ΔpH diagrams to aid economic buffer applications. This study has laid the foundation for quantification and regulation of dynamic pH response and is of wide interest to the chemistry encompassing interfacial processes.

The droplet size distribution in liquid-liquid dispersions is a complex convolution of impeller speed, impeller type, fluid properties, and flow conditions. In this work, we present three a priori modeling approaches for predicting the droplet diameter distributions as a function of system operating conditions. In the first approach, called the two-fluid approach, we use high-resolution solutions to the Navier-Stokes equations to directly model the flow of each phase and the corresponding droplet breakup/coalescence events. In the second approach, based on an Eulerian-Lagrangian model, we describe the dispersed fluid as individual spheres undergoing ongoing breakup and coalescence events per user-defined interaction kernels. In the third approach, called the Eulerian-Parcel model, we model a sub-set of the droplets in the Eulerian-Lagrangian model to estimate the overall behavior of the entire droplet population. We discuss output from each model within the context of predictions from first principles turbulence theory and measured data.

This work aims to study the gas phase hydrodynamics in a stirred tank with a surface-aerated long-short blades agitator by the Eulerian‒Eulerian approach coupled with population balance model. Predicted local gas holdup and bubble size distribution agree well with those measured by a conductivity probe technique. The predictions demonstrate that the pressure depression in the center is the main driving force for gas suction and the downward flow carries the bubbles down to redistribute in the whole tank. The gas phase has higher gas holdup with large bubble size in the upper part and lower gas holdup but with small bubble size in the lower part of the tank. The predicted gas-liquid mass transfer coefficients agree well with our previous experimental results and just depends on the power consumption per unit volume when the aspect ratio of the liquid height to the tank diameter varies from 1.1 to 2.0.

The binary fluidization of Geldart-D type non-spherical wood particles and spherical LDPE particles was investigated in a laboratory-scale bed. The experiment was performed for varying static bed height, wood particles count, as well as superficial gas velocity. The LDPE velocity field were quantified using Particle Image Velocimetry (PIV). The wood particles orientation and velocity are measured using Particle Tracking Velocimetry (PTV). A machine learning pixel-wise classification model was trained and applied to acquire wood and LDPE particle masks for PIV and PTV processing, respectively. The results show significant differences in the fluidization behavior between LDPE only case and binary fluidization case. The effects of wood particles on the slugging frequency, mean, and variation of bed height, and characteristics of the particle velocities/orientations were quantified and compared. This comprehensive experimental dataset serves as a benchmark for validating numerical models.

Homogeneous hydrogen transfer reactions of methacrolein (MAL) and isopropanol (IPA) to methallyl alcohol (MAA) were investigated in batch reactor (Conv.89%, Select 93.1%) and tubular reactor (Conv.88.1%, Select 95%) using aluminum isopropoxide (Al(OPri)3) as catalyst. Kinetic experiments on hydrogen transfer reactions and reaction order were investigated in batch reactor and tubular reactor. Response surface methodology (RAM) was applied to optimize the optimum reaction conditions of hydrogen transfer reaction. Purification process of MAA from product mixture after hydrogen transfer reaction was simulated with Aspen Plus software, theoretical stages, reflux ratio and feed stage of distillation tower were optimized. Density Functional Theory (DFT) was used to investigate viable reaction pathway and to probe the catalytic mechanism between reactants and catalyst, including dehydrogenation, coupling and hydrogenation reaction. Microscopic mechanisms of hydrogen transfer reaction from MAA to MAL were acquired in detail and could be easily extended to other series of hydrogen transfer reaction.

This paper describes a machine learning guided framework for screening the potential toxicity impact of amine chemistries used in the synthesis of hybrid organic-inorganic perovskites. Using a combination of a probabilistic molecular fingerprint technique that encodes bond connectivity (MinHash) coupled to non-linear data dimensionality reduction methods (UMAP), we develop an “Amine Atlas’. We show how the Amine Atlas can be used to rapidly screen the relative toxicity levels of amine molecules used in the synthesis of 2D and 3D perovskites and help identify safer alternatives. Our work also serves as a framework for rapidly identifying molecular similarity guided, structure-function relationships for safer materials chemistries that also incorporate sustainability/ toxicity concerns.

A three-dimensional, non-isothermal and multiphase model of high temperature proton exchange membrane fuel cells is built to investigate water and phosphoric acid transportation, in which a spherical agglomerate model considering catalyst layer structure and liquid phase fraction is applied to determine the electrochemical kinetics in the cathode catalyst layer. Experimental polarization curve, water proportion in the anode outlet gas and phosphoric acid distribution are selected for validation. It is found that the simulated results can represent the experimental data with reasonable accuracy. Based on the model, the effects of current density and stoichiometry on the variable distributions are analyzed. The results show that water in anode is mainly from cathode by concentration diffusion of liquid water. A higher current density leads to a greater electro-migration of phosphoric acid from cathode to anode and a higher liquid phase fraction in anode,while a lower phosphoric acid concentration in the fuel cells.

Multifluid model (MFM) simulations have been carried out on liquid-solid fluidized beds (LSFB) consisting of binary and higher-order polydisperse particle mixtures. The role of particle-particle interactions was found to be as crucial as the drag force under laminar and homogenous LSFB flow regimes. The commonly used particle-particle closure models are designed for turbulent and heterogeneous gas-solid flow regimes and thus exhibit limited to no success when implemented for LSFB operating under laminar and homogenous conditions. A need is perceived to carry out Direct Numerical Simulations of liquid-solid flows and extract data from them to develop rational closure terms to account for the physics of LSFB. Finally, a recommendation flow regime map signifying the performance of the MFM has been proposed. This map will act as a potential guideline to identify whether or not the bed expansion characteristics of a given polydisperse LSFB can be correctly simulated using MFM closures tested.

The force exerted on particles is of great significance to the flow and reaction characteristics of particles in gasifier. In this study, the unbalanced thrust, especially its magnitude, of a single char particle induced by chemical reactions during combustion process is investigated numerically, based on the random distribution of active sites. It is revealed that the nonuniform distribution of active sites directly leads to the nonuniform release of gaseous products, which accounts for the net induced thrust of particles. The effects of active site ratio, ambient gas temperature and particle diameter on the induced thrust of reaction particle were investigated. The results show that the induced thrust on particles could be equal to the magnitude of particle gravity. The induced thrust decreases with the increase of active area and particle diameter. And it is enhanced with the increase of ambient temperature.

High heat duty is an urgent challenge for industrial applications of amine-based CO2 capture. In this work, we report a novel, stable, efficient, and inexpensive Ni-HZSM-5 catalyst to reduce the heat duty. The density functional theory (DFT) calculations successfully explain the catalytic performance. The catalytic activity associates with the combined properties of MSA × B/L × Ni2+. The 7.85-Ni-HZ catalyst presents an excellent catalytic activity for the CO2 desorption: it increases the amount of desorbed CO2 up to 36%, reduces the heat duty by 27.07% compared with the blank run, and possesses high stability during five cyclic tests. A possible catalytic mechanism for the Ni-HZSM-5 catalysts through assisting carbamate breakdown and promoting CO2 desorption is proposed based on experimental results and theoretical calculations. Therefore, the results present that the 7.85-Ni-HZ catalyst significantly accelerates the protons transfer in CO2 desorption and can potentially apply in industrial CO2 capture.

A high-throughput (105.5 g/h) passive four-stage asymmetric oscillating feedback microreactor using chaotic mixing mechanism was developed to prepare aggregated BaSO4 particles of high primary nanoparticle size uniformity. Three-dimensional unsteady simulations showed that chaotic mixing could be induced by three unique secondary flows (i.e., vortex, recirculation, and oscillation), and the fluid oscillation mechanism was examined in detail. Simulations and Villermaux-Dushman experiments indicate that almost complete mixing down to molecular level can be achieved and the prepared BaSO4 nanoparticles were with narrow primary particle size distribution (PSD) having geometric standard deviation, σg, less than 1.43 when the total volumetric flow rate Qtotal was larger than 10 mL/min. By selecting Qtotal and reactant concentrations, average primary particle size can be controlled from 23 to 109 nm as determined by microscopy. An average size of 26 nm with narrow primary PSD (σg = 1.22) could be achieved at Qtotal of 160 mL/min.

This paper presents a novel energy flow redistribution methodology to achieve optimal operation of heat exchanger networks (HENs). The proposed method aims to manipulate the propagation path of a disturbance through the network to reduce its impact on utility consumption. Specifically, an optimization problem is formulated to generate new duty targets for heat exchangers of the network when a disturbance is encountered. Subsequently, a feedback control system is designed to track these targets by manipulating bypasses around the process heat exchangers. The effectiveness of the proposed framework is illustrated with the help of three benchmark examples. The proposed approach can handle disturbances in inlet as well as target temperature, inlet flow and heat transfer coefficient of individual heat exchangers.