Two-phase Reactor Research Articles

Population Balance Equations for Reactive Separation in Polymer Upcycling.

Many polymer upcycling efforts aim to convert plastic waste into high-value liquid hydrocarbons. However, the subsequent cleavage of middle distillates to light gases can be problematic. The reactor often contains a vapor phase (light gases and middle distillates) and a liquid phase (molten polymers and waxes with a suspended or dissolved catalyst). Because the catalyst resides in the liquid phase, middle distillates that partition into the vapor phase are protected against further cleavage into light gases. In this paper, we consider a simple reactive separation strategy, in which a gas outflow removes the volatile products as they form. We combine vapor-liquid equilibrium models and population balance equations (PBEs) to describe polymer upcycling in a two-phase semibatch reactor. The results suggest that the temperature, headspace volume, and flow rate of the reactor can be used to tune selectivity toward the middle distillates, in addition to the molecular mechanism of catalysis. We anticipate that two-phase reactor models will be important in many polymer upcycling processes and that reactive separation strategies will provide ways to boost the yield of the desired products in these cases.

VOF study of mesoscale bubble flow dynamics in the side-blown gas–liquid two-phase reactor

Understanding the flow and mixing characteristics of mesoscale bubbles within side-blown gas–liquid two-phase systems is paramount for the design and optimization of associated industrial processes. This study elucidates the gas–liquid side-blown two-phase reactor, employing the volume of fluid method coupled with the realizable k-ε turbulence model. Following the model validation through experimental measurements, the mesoscale bubble dynamics, flow characteristics, and multiscale coupling mechanisms inherent to side-blown gas–liquid reactor are explored. The key insights can be obtained: (1) the upward trajectory of bubbles originating from side-injection gas can be categorically divided into four phases with different bubble behaviors. (2) A reduction in the ratio of inertial forces to buoyancy forces during bubble ascent induces a decrease in the bubble shape factor. This transition manifests as a shift from vertical to flattened bubble shapes within the transition and plume regions. (3) Bubbles undergo transitions between states characterized by high buoyancy and low surface tension, accompanied by varying levels of viscous forces during their ascent. These dynamic states render bubbles susceptible to breakup. Under conditions of a constant nozzle diameter, the maximum bubble size within the reactor is inherently restricted. (4) Drawing upon the correlation between bubble Weber and Reynolds numbers, a predictive formula for determining the characteristic velocity of bubbles within side-blown reactors is proposed:uc=σ1-0.456(ρlLC)0.456512μl11.36Overall, this work offers meaningful insights into the fundamental mechanisms governing bubble cluster dynamics within side-blown gas–liquid reactors.

Numerical Analysis of Gas Hold-Up of Two-Phase Ebullated Bed Reactor

Due to the significant increase in heavy feedstocks being transported to refineries and the hydrocracking process, the significance of adopting an ebullated bed reactor has been reemphasized in recent years. The predictive modelling of gas hold-up in an ebullated two-phase reactor was performed using 10 machine learning methods based on support vector machine (SVM) and Gaussian process regression (GPR) in this study. In an ebullated bed reactor, the impacts of three features, namely liquid velocity, gas velocity, and recycling ratio, on the gas hold-up were examined. The liquid velocity has the most impact on the predicted gas hold-up, according to the feature significance analysis. The rotational-quadratic, squared-exponential, Matern 5/2, and exponential kernel functions integrated with the GPR models and the linear, quadratic, cubic, fine, medium, and coarse kernel functions integrated with the SVM model performed well during training and testing, with the exception of the fine SVM model, whose R2 is very low. According to the R2 > 0.9 and low RMSE and MAE values, the rotational-quadratic, squared-exponential, and Matern 5/2 GPR models performed the best.

Investigating the impact of modeling assumptions and closure models on the steady-state prediction of solar-driven methane steam reforming in a porous reactor

In this work, the effect of different modeling assumptions and closure models — frequently considered in the literature of solar thermochemical reactors and closely-related areas — is investigated. The application of different modeling assumptions and closure models may strongly affect the results accuracy and compromise a meaningful comparison across literature works. The following is herein investigated: (i) the role of upstream and downstream fluid regions to the two-phase reactor region; (ii) relevance of species and gas-phase thermal diffusion mechanisms; (iii) reaction heat accounted for in gas- or solid-phase energy balance equations; (iv) local thermal equilibrium (LTE) vs. local thermal non-equilibrium (LTNE) models; (v) model dimension (one-dimensional vs. two-dimensional axisymmetric models); (vi) local volumetric convection heat transfer correlations; and (vii) effective solid thermal conductivity correlations. The relevance of this work extends well beyond the current application (methane steam reforming in a volumetric solar reactor), since similar models and assumptions have also been widely applied for predicting the performance of volumetric solar absorbers and dry reforming solar reactors. The results show that an upstream fluid region should be considered while applying inlet first-type boundary conditions and diffusion transport in the corresponding governing equations to ensure full-conservation and simultaneously to account for developing profiles upstream the reactor inlet section. For the operating conditions considered, species diffusion and gas-phase heat conduction are particularly relevant at the reactor centerline but with a negligible integral effect. A significant difference in the reactor performance is observed while accounting for the reaction heat from surface reactions in the solid- or gas-phase energy balances — for the lowest inlet gas velocity herein considered, the thermochemical efficiency (methane conversion) is approximately equal to 70.8% (76.3%) and 77.3% (84.7%) assigning the reaction heat to the gas- and solid-phase energy balances, respectively. LTE model results are strikingly different from the results obtained with the LTNE model considering the reaction heat accounted for in the gas-phase energy balance but not significantly different from the results computed with the LTNE model with the reaction heat assigned to the solid-phase energy balance. One-dimensional reactor modeling provided with an average concentrated solar heat flux value results in a similar average performance as that given by a two-dimensional model but fails to predict the high temperatures observed at reactor centerline — for the lowest inlet gas velocity, the difference between the maximum solid temperatures predicted by one- and two-dimensional models is about 340K.

Design, Construction, and Concept Validation of a Laboratory-Scale Two-phase Reactor to Valorize Whiskey Distillery By-products.

The by-products generated from the whiskey distillation process consist of organic liquids with a high chemical oxygen demand (COD) and residues with a high solid content. Low-carbon strategies that repurpose and valorize such by-products are now imperative to reduce the carbon footprint of the food and beverage industries. The operation of a two-phase anaerobic digester to produce volatile fatty acids (VFAs) and biogas may enable distilleries to transition toward a low-carbon bioeconomy. An example of such a system is a leach bed reactor connected to an expanded granular sludge bed (LBR-EGSB) which was designed, commissioned, and conceptually validated in this paper. Several design improvements progress the LBR-EGSB beyond previous reactor designs. An external gas-liquid-solid separator in the EGSB was used to capture any residual gases produced by the effluent and may reduce the amount of methane slippage and biomass washout. The implementation of a siphon-actuated leachate cup is a low-cost alternative that is less prone to actuation malfunction as compared to electrically actuated solenoid valves in previous reactor designs. Furthermore, replacing fresh water with distillery's liquid by-products as leachate promotes a circular repurpose and reuse philosophy. The system proved to be effective in generating VFAs (10.3 g VFAs L-1Leachate), in EGSB COD removal (96%), and in producing methane-rich biogas (75%vol), which is higher than the values achieved by traditional anaerobic digestion systems. The LBR-EGSB could ultimately provide more by-product valorization and decarbonization opportunities than traditional anaerobic digestion systems for a whiskey distillery.

Kinetic modeling of methanol-to-olefins process over SAPO-34 catalysts in a dual fluidized bed reactor–regenerator

Based on a lumped methanol-to-olefins (MTO) reaction kinetic model over SAPO-34 catalyst particles, a one-dimensional two-phase model was developed for bubbling fluidized bed reactor and catalyst regenerator. Comparison of the model predictions with literature experimental data showed good agreement over wide ranges of operating conditions both on a bench-scale unsteady-state bubbling fluidized bed reactor as well as pilot and demo-scale steady-state dual fluidized bed reactor–regenerator. The two-phase reactor model was also applied for catalyst coke content combustion with diluted air to design the regenerator of the dual fluidized bed reactor. Finally, the heat duty required for cooling circulating catalyst particles is obtained from overall energy balances. This integrated reactor–regenerator simulation allows for seamless analysis of MTO process. The trade-off between the complexity and applicability of the model makes it a useful choice for conceptual process designs, scale-up, integration with simulation software, optimization, process control and economic analyses.

Enhanced performance of anaerobic two-phase reactor treating coal gasification wastewater with the assistance of zero valent iron under co-digestion conditions

Coal gasification wastewater (CGW) is a typical industrial wastewater that is difficult to degrade as it contains a large number of refractory and toxic pollutants, such as high concentrations of phenols.The aim of this study is to investigate an anaerobic two-phase reactor treating synthetic CGW under co-digestion conditions. The optimum dosages of co-substrate (glucose = 1000 mg/L), zero valent iron (ZVI) (2 g/L), and hydrolysis acidification time (12 h) were explored by batch tests. The results indicated that the concentration of total phenols declined from 636 mg/L to 376 mg/L when the cumulative methane production increased to 145 mL. In the long-term operation of the anaerobic two-phase reactor, 1,000 mg/L glucose was added to the influent, and 2 g/L ZVI was added in the methanogenic phase, respectively. HRTs in acidogenic and methanogenic phases were kept at 12 h and 48 h, respectively. The average acetate and TVFAs concentrations remained at approximately 852 mg/L and 1042 mg/L, respectively. The result showed that the concentrations of influent and effluent COD were approximately 3,191 mg/L and 412 mg/L, respectively, while those of influent and effluent total phenols were approximately 655 mg/L and 23 mg/L, respectively. The removal efficiencies of total COD and total phenols were over 86% and 96%, respectively. In addition, the total methane production rose to 250 mL/d. Microbial community structure analysis demonstrated that the acidogenic phase contained most types of microbial species and the most complex community diversity in the anaerobic system and that direct interspecies electron transfer (DIET) might occur between the potential electroactive bacteria Chloroflexi and the archaea Methanobacteriales and Methanosaeta, respectively.

Co-metabolism based adaptation of anaerobes to phenolic saline wastewater in a two-phase reactor enables efficient treatment and bioenergy recovery

Anaerobic biological treatment of saline phenolic wastewater has some limitations such as slow adaptation, low biodegradability, and salinity-derived washout of biomass, though this technology has some benefits in terms of bioenergy recovery, simplicity in operation, and economic rationality. Therefore, we propose a packed-bed circular baffled reactor (PB-CBR) along with a co-metabolism strategy for phenol adaptation at salinity level of 10 g-NaCl/L. Phenol and glucose were gradually increased and decreased to 0.9 and 1.0 g/L, respectively. Stable and efficient performance was achieved with > 99.9% phenol removal, ∼98% overall biodegradability, and ∼ 0.3 L CH4/gCOD. A sudden increase in phenol to 2 g/L was then examined, where phenol removal dropped to ∼ 19% after 30 d; after another 30 d, the removal was negligible even when phenol was decreased to 1.7 g/L. The compartment-wise analysis of PB-CBR showed that phases-separation, along all compartments, maintained the overall efficiency, particularly when facing salinity or phenol shocks; otherwise, earlier compartments achieve ∼ 95% of efficiency. The microbial community analysis showed that Corynebacteriaceae, Syntrophaceae, Kosmotogaceae, and Synergistaceae were key players in phenol-degradation. Using readily biodegradable co-substrate enhanced the biodiversity. Eventually, and according to a cost-benefit analysis, the present work offers a promising opportunity to treat phenol-based saline effluents in an efficient, sustainable, and affordable way.

Assessment of energy efficiency and performance in a two-phase anaerobic process for organic matter removal.

Energy efficiency (EE) depends mainly on the lower heating values (LHVs) of hydrogen and methane selected from the thermodynamics tables under ideal conditions. However, for practical applications, the heating value should be calculated by considering some environmental factors under real conditions. Accordingly, this study compared EE using the ideal LHV with the EE using the real LHV in a two-phase anaerobic digestion reactor treating synthetic wastewater. Additionally, the process performance and the stability were studied. The results showed that the EE value calculated using LHVideal was, on average, 35% higher than that evaluated using LHVreal; these differences are relevant to the estimation of real energy and also for practical applications. At the same time, the index buffer intermediate alkalinity/partial alkalinity was shown to be more accurate than the pH value to analyze the stability of the process. With regards to chemical oxygen demand, the removal efficiency in the methanogenic phase decreased drastically when utilizing 100% of the acidogenic phase. Future considerations for the optimization of each phase are highlighted.

Prediction of gas velocity in two-phase flow using developed fuzzy logic system with differential evolution algorithm

In this investigation, differential evolution (DE) algorithm with the fuzzy inference system (FIS) are combined and the DE algorithm is employed in FIS training process. Considered data in this study were extracted from simulation of a 2D two-phase reactor in which gas was sparged from bottom of reactor, and the injected gas velocities were between 0.05 to 0.11 m/s. After doing a couple of training by making some changes in DE parameters and FIS parameters, the greatest percentage of FIS capacity was achieved. By applying the optimized model, the gas phase velocity in x direction inside the reactor was predicted when the injected gas velocity was 0.08 m/s.

Effective Bioremediation of Zinc(II) with Fusarium sp. in Batch and Continuous Studies

Designing desirable approach for batch and continuous methods of activity for profoundly effective removal of zinc(II) is of practical importance, given the steady, cost-effective, environmentally friendly attribute. This article offers an answer for foster a continuous stirred tank bioreactor (CSTR) containing single- and two-phase reactors for the viable continuous removal of zinc(II) from aqueous solution by making use of Fusarium sp. collected from soil under growing conditions. The different development stages Fusarium sp. were tried, including initial metal concentration, pH and growth rate in batch bioreactors. The maximum removal of zinc(II) in the batch studies indicated 63.9 mg/g, at controlled pH: 5.0; and at initial 500 mg/L zinc(II) concentration, which is almost of comparable quantity to the most extreme removal of zinc(II) (52.8 mg/g) obtained in the continuous mode of operation. A continuous flow system operated in staged manner was found to be the ideal strategy for obtaining almost complete removal at lower concentration focus up to 100 mg/L in a single stage bioreactor and a multistage reactor at higher zinc(II) concentrations.

Predicting Air Superficial Velocity of Two-Phase Reactors Using ANFIS and CFD.

In predicting the turbulence property of gas (bubble) flow in the domain of continuous fluid and liquid, the integration of machine learning and computational fluid dynamics (CFD) methods reduces the overall computational time. This combination enables us to see the effective input parameters in the engineering process and the impact of operating conditions on final outputs, such as gas hold-up, heat and mass transfer, and the flow regime (uniform bubble distribution or nonuniform bubble properties). This paper uses the combination of machine learning and single-size calculation of the Eulerian method to estimate the gas flow distribution in the continuous liquid fluid. To present the machine-learning method besides the Eulerian method, an adaptive neuro-fuzzy inference system (ANFIS) is used to train the CFD finding and then estimate the flow based on the machine-learning method. The gas velocity and turbulent eddy dissipation rate are trained throughout the bubble column reactor (BCR) for each CFD node, and the artificial BCR is predicted by the ANFIS method. This smart reactor can represent the artificial CFD of the BCR, resulting in the reduction of expensive numerical simulations. The results showed that the number of inputs could significantly change this method’s accuracy, representing the intelligence of method in the learning data set. Additionally, the membership function specifications can impact the accuracy, particularly, when the process is trained with different inputs. The turbulent eddy dissipation rate can also be predicted by the ANFIS method with a similar model pattern for air superficial gas velocity.

Evolution and Interaction Characteristics of Liquid Flow and Bubbles in a Jet Bubbling Column

The jet bubbling column is a new type of gas–liquid two-phase reactor with excellent mixing ability. The evolution and interaction characteristics of liquid flow and bubbles in a jet bubbling colum...

Simulation of direct chlorination of ethylene in a two-phase reactor by coupling equilibrium, kinetic and population balance models

Abstract The purpose of presented research is the mathematical simulation and sensitivity analysis of ethylene dichloride synthesis (EDC) through direct chlorination of ethylene in a bubble column reactor at steady state condition. In the first step, the reactor is heterogeneously simulated based on the energy and mass balance equations by coupling the mass and energy, kinetic, equilibrium, and population balance models. In the considered process, the gaseous ethylene and chlorine are dispersed and dissolved in the liquid medium and converted to EDC at the presence of a homogeneous catalyst. The population balance model is applied to calculate the heat and mass transfer area along the reactor. To investigate the accuracy of established model, the results of simulation are compared with the plant data. It is confirmed that temperature, pressure, rate of mass transfer, breakage, and coalescence phenomena change the bubble diameter and distribution in the chlorination reactor. In the second step, the effects of operating pressure and temperature on the EDC production rate are investigated by the developed model. In the third step, considering EDC production rate as the cost function the optimal operating temperature of reactor is developed at steady state condition. Based on the obtained results, the optimal operating temperature is 357 K and EDC production at the optimal condition is 23.79 mol s−1.

Impact of process temperature and organic loading rate on cellulolytic / hydrolytic biofilm microbiomes during biomethanation of ryegrass silage revealed by genome-centered metagenomics and metatranscriptomics

BackgroundAnaerobic digestion (AD) of protein-rich grass silage was performed in experimental two-stage two-phase biogas reactor systems at low vs. increased organic loading rates (OLRs) under mesophilic (37 °C) and thermophilic (55 °C) temperatures. To follow the adaptive response of the biomass-attached cellulolytic/hydrolytic biofilms at increasing ammonium/ammonia contents, genome-centered metagenomics and transcriptional profiling based on metagenome assembled genomes (MAGs) were conducted.ResultsIn total, 78 bacterial and archaeal MAGs representing the most abundant members of the communities, and featuring defined quality criteria were selected and characterized in detail. Determination of MAG abundances under the tested conditions by mapping of the obtained metagenome sequence reads to the MAGs revealed that MAG abundance profiles were mainly shaped by the temperature but also by the OLR. However, the OLR effect was more pronounced for the mesophilic systems as compared to the thermophilic ones. In contrast, metatranscriptome mapping to MAGs subsequently normalized to MAG abundances showed that under thermophilic conditions, MAGs respond to increased OLRs by shifting their transcriptional activities mainly without adjusting their proliferation rates. This is a clear difference compared to the behavior of the microbiome under mesophilic conditions. Here, the response to increased OLRs involved adjusting of proliferation rates and corresponding transcriptional activities. The analysis led to the identification of MAGs positively responding to increased OLRs. The most outstanding MAGs in this regard, obviously well adapted to higher OLRs and/or associated conditions, were assigned to the order Clostridiales (Acetivibrio sp.) for the mesophilic biofilm and the orders Bacteroidales (Prevotella sp. and an unknown species), Lachnospirales (Herbinix sp. and Kineothrix sp.) and Clostridiales (Clostridium sp.) for the thermophilic biofilm. Genome-based metabolic reconstruction and transcriptional profiling revealed that positively responding MAGs mainly are involved in hydrolysis of grass silage, acidogenesis and / or acetogenesis.ConclusionsAn integrated -omics approach enabled the identification of new AD biofilm keystone species featuring outstanding performance under stress conditions such as increased OLRs. Genome-based knowledge on the metabolic potential and transcriptional activity of responsive microbiome members will contribute to the development of improved microbiological AD management strategies for biomethanation of renewable biomass.

Optimization of a Fenton-based gas–liquid two-phase reactor for NOx removal

The objective of this work is the computational fluid dynamics (CFD)-based optimization of a gas–liquid two-phase NOx removal absorption vessel. One of the main effectors on the efficiency in a gas–fluid system is the construction of the inlet gas distributor. The optimal solution should provide homogeneous gas distribution in the vessel leading to better operation. Twenty-four different geometries with 8 nozzle number (1, 3, 5, 4, 9, 29, 37, and 61), and 3 inlet areas were drawn: 1.2e-4 m2 (100%) and 0% and 150% of the original area was simulated in a CFD environment. The geometries were evaluated based on the analysis of the gas volume fractions, well-mixed areas, particle trajectories, and outlet concentrations. The application of case 8 (with 29 inlet nozzles in non-uniform construction) and case 4 (with 61 uniform diameter nozzles) also exceeds the operation of the reference case and can be used for the improvement of existing construction. Based on the different evaluation criterion case 4 was chosen as the best solution, which provides at least 10% removal efficiency increase. With the homogeneous gas distribution, the phase contact within the vessel can be intensified, which will lead to more efficient NOx removal.

Enzymatic epoxidation of cyclohexene by peroxidase immobilization on a textile and an adapted reactor design

A textile-based reaction system for new peroxidase reactions in non-native media was implemented. The epoxidation of cyclohexene by the commercial peroxidase MaxiBright® was realized with the textile-immobilized enzyme in an adapted liquid-liquid two-phase reactor. A commercially available polyester felt was used as low-price carrier and functionalized with polyvinyl amine. The covalent immobilization with glutardialdehyde lead to an enzyme loading of 0.10 genzyme/gtextile. The textile-based peroxidase shows a high activity retention in the presence of organic media. This catalyst is shown to enable the epoxidation of cyclohexene in various solvents as well as under neat conditions. A model reactor was produced by 3D printing which places the textile catalyst at the interphase between the liquid reaction phase and the product extracting solvent.

Simulation of a Bubble-Column Reactor by Three-Dimensional CFD: Multidimension- and Function-Adaptive Network-Based Fuzzy Inference System

Recently, novel approaches have been developed for simulating bubbly flow as well as distributed and constant phase evolution by means of a two-phase reactor. Among these approaches, the Eulerian–Eulerian method and soft computing approaches can be mentioned. Since complex numerical methods (for example, multidimensional Eulerian–Eulerian method) require several runs for fluid conditions optimization, a method which can decrease these runs can be very useful and practical. This method is provided by joining computational fluid dynamic (CFD) to the adaptive neuro-fuzzy inference system (ANFIS). In this technique, valuable information is provided for a careful analysis of fluid conditions. Also, it can facilitate a vast amount of data categorization in synthetic neural network nodes, which eliminates the need for a complex nonstructured CFD mesh. Moreover, a neural geometry can be provided, in which no limitation of mesh numbers in the fluid domain would exist. The key CFD parameters in the scale-up of the reactorstaken into consideration in the current research are gas and liquid circulations. These factors are applied as output factors for prediction tool in various dimensions in the ANFIS method. The results obtained in this study show appropriate conformity concerning ANFIS and CFD results depending on multiple dimensions. In this study, the grouping of CFD and multifunction the ANFIS method delivers the nondiscrete domain in different dimensions and presents an intelligent instrument for the local prediction of multiphase flow. The result shows that three inputs, which represent the dimension of the reactor, and learning stage of the ANFIS method provide a better understanding of flow characteristics in the two-phase reactor, while the two-dimensional ANFIS method even with multistructured functions cannot predict well the multiphase flow in the reactor.

Solid carbon production and recovery from high temperature methane pyrolysis in bubble columns containing molten metals and molten salts

We study methane pyrolysis in a bubble column reactor consisting of a layer of molten NiBi alloy, and a molten salt layer floating on the metal layer. The molten metal is a pyrolysis catalyst; the molten salt layer is added for removing contaminants from the carbon product. Methane is introduced at the bottom of the reactor and the rising bubbles contain reactant and product gases together with metal vapor and flakes of solid carbon. When the bubbles rise through the molten salt layer the metal vapor condenses producing dense liquid metal droplets, which sink to the metal phase; the low-density carbon rises to the top of the salt layer. The carbon generated from the single-phase molten NiBi reactor has a different structure from that produced in the two-phase NiBi/salt reactor. The amount of metal in the carbon product is less than 5 wt %, in the two-phase reactor, compared to 83 wt % in the NiBi single-phase reactor. After subsequent purification steps one obtains solid carbon with less than 2 wt % salt contamination and no detectable metal contamination.

Electric field assisted multicomponent reaction in a microfluidic reactor for superior conversion and yield.

We explore the improvements in yield and conversion of a chemical reaction inside a two-phase microfluidic reactor when subjected to an externally applied alternating current (AC) electric field. A computational fluid dynamic (CFD) framework has been developed to incorporate the descriptions of the two-phase flow, multicomponent transport and reaction, and the Maxwell's stresses generated at oil-water interface owing to the presence of the externally applied electric field. The CFD model ensures that the reactants are flown into a microchannel together with the oil and water phases before the reaction takes place at the interface and products diffuse back to the bulk phases. The study unveils that the variation in the intensity of the AC field helps in converting a two-phase stratified flow into an oil-in-water microemulsion composed of oil slugs, plugs, or droplets. Importantly, the results also suggest that harnessing the vortices inside or outside these flow patterns helps in the improvement in mass transfer across the interface, which can be employed to improve the yield and conversion of a reaction. We have shown an example case of a pseudo-first order reaction for which the variation in frequency and intensity of AC field is found to form higher surface-to-volume-ratio flow patterns having a higher throughput. The convective recirculation in and around these miniaturized flow morphologies increase the rate of mass transfer, mixing of reactant and products, conversion of reactant, and yield of products. The results reported can be of significance in the design and development of future advanced-flow rector technologies.