Chemical Reactor Research Articles

Non-invasive and non-intrusive diagnostic techniques for gas-solid fluidized beds – A review

Gas-solid fluidized-bed systems offer great advantages in terms of chemical reaction efficiency and temperature control where other chemical reactor designs fall short. For this reason, they have been widely employed in a range of industrial application where these properties are essential. Nonetheless, the knowledge of such systems and the corresponding design choices, in most cases, rely on a heuristic expertise gained over the years rather than on a deep physical understanding of the phenomena taking place in fluidized beds. This is a huge limiting factor when it comes to the design, the scale-up and the optimization of such complex units. Fortunately, a wide array of diagnostic techniques has enabled researchers to strive in this direction, and, among these, non-invasive and non-intrusive diagnostic techniques stand out thanks to their innate feature of not affecting the flow field, while also avoiding direct contact with the medium under study. This work offers an overview of the non-invasive and non-intrusive diagnostic techniques most commonly applied to fluidized-bed systems, highlighting their capabilities in terms of the quantities they can measure, as well as advantages and limitations of each of them. The latest developments and the likely future trends are also presented. Neither of these methodologies represents a best option on all fronts. The goal of this work is rather to highlight what each technique has to offer and what application are they better suited for.

Prediction of NOx emission from two-stage combustion of NH3–H2 mixtures under various conditions using artificial neural networks

This study aims to predict NOx emission from the combustion of ammonia (NH3) and hydrogen (H2) mixtures using Artificial Neural Network (ANN) models. Chemical Reactor Network (CRN) models were utilized to calculate the NOx emission during the Rich-Quench-Lean (RQL) two-stage combustion of NH3–H2 mixtures under various conditions, such as fuel pressures, inlet temperatures, primary air humidification fractions, total equivalent ratios and primary equivalent ratios. The simulation results served as a data set for training and validation of three different ANN models: Backpropagation (BP), Radial Basis Function (RBF), and Generalized Regression Neural Network (GRNN). The results show that all three ANN models can effectively replace the CRN model in accurately predicting NOx concentrations. In particular, the BP model, optimized with 37 hidden neurons, showcased superior performance, achieving a correlation coefficient (R) value of 0.99826 with the simulated results. It had the lowest Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) values of 61.3 and 96.1, respectively. In addition, it achieved the highest coefficient of determination (R2) and Model Efficiency (ME) values of 0.9950 and 0.9908 respectively, surpassing the RBF and GRNN models. These results suggest that the BP model has significant potential as an alternative to the CRN model for predicting NOx emissions from two-stage combustion of NH3–H2 mixtures, demonstrating both accuracy and efficiency.

Experimental and numerical study on emission characteristics of NH3/DME/air flames in a premixed burner

As a potential candidate for the use as a carbon-free fuel, ammonia (NH3) has an advantage over hydrogen in terms of storage costs but faced with two main issues, i.e., low burning speed and high NOx emission. In this study, dimethyl ether (DME) was used as a combustion promoter to improve the combustion characteristics of NH3, and the emission characteristics of NH3/DME/air premixed flames were investigated in a premixed burner. For the NO emissions, it was found that lean conditions and stoichiometric condition favored the formation of NO while rich conditions showed a negative impact on NO formation. Moreover, increasing of NH3 fraction from 50% to 90% at a volumetric ratio of fuel mixtures effectively decreased the NO emissions. Interestingly, the NO2 emission showed a similar trend to that of NO, but with only 1/10 of the relevant concentration, the underlying reason was ascribed to the similarity between NO and NO2 reaction pathways. In addition, the emission of CO and unburned NH3 increased sharply in fuel rich conditions due to the lack of oxygen. The simulations in the chemical reactor networks with a detailed mechanism were conducted to analyze the NO emission behaviors of the NH3/DME flames. Results showed that the two-element chemical reactor networks could capture the trend of NO emission accurately. Sensitivity analyses of NO concentration were conducted to identify and analyze the reactions responsible for NO formation. Results showed that the third body reaction CH3OCH3(+M)=CH3+CH3O(+M) has the greatest promotion effect on NO generation at the flame zone, while the reactions NH+NO=N2O+H and N+NO=N2+O become the major reactions of NO consumption at the post flame zone. DME has high reactivity, and a large number of active radicals produced by its oxidation could promote the generation reactions of NO and increase the production rate of NO. The NO reaction pathway analysis showed that the HNO pathway played a major role in NO formation in the main combustion zone.

Selective BTEX detection using laser absorption spectroscopy in the CH bending mode region

BTEX (benzene, toluene, ethylbenzene, and xylene) are simple aromatics that play a major role in soot formation in combustion systems. They are widely used as aromatic representatives in fuel surrogates. Measuring BTEX in chemical reactors can give insight into the soot formation mechanisms and help mitigate its production. The similar chemical structures of BTEX make their selective detection highly challenging. These species give rise to broad and similar absorption features across most of the electromagnetic spectrum. In this work, we report the development of a selective BTEX laser-based sensor in the long-wave mid-infrared (LW-MIR) spectral region. The sensor probes the rarely accessed CH bending modes of BTEX molecules and takes advantage of the strong, spectrally isolated absorption features of aromatics in this spectral region. The developed sensor is based on a custom-designed difference-frequency generation (DFG) laser source. Wavelength selection, and the development and evaluation of the performance of the custom-designed sensor are discussed. The sensor was found to perform excellently over the mole fraction range of 0 - 1,000 ppm of each of the BTEX species. Estimated detection limits of our developed sensor are 60, 15, 40, and 50 ppm for benzene, toluene, ethylbenzene, and m-xylene, respectively.

The Impact of Heating Rate on the Kinetics of the Nitriding Process for 52100 Steel.

The aim of this study was to determine the impact of the heating rate of steel balls made of AISI 52100 alloy steel on the kinetics and efficiency of the gas nitriding process when carried out using a chemical reactor with precise thermo-gravimetric measurements, which allowed for changes in sample mass during heating and nitriding to be monitored with an accuracy of 50 µg. In the chemical reactor, the examined alloy steel was subjected to a heating process at the selected nitriding temperature of 590 °C. Two heating variants were used: the first variant relied on heating to the nitriding temperature with different rates-1 °C per minute, 2 °C per minute, 5 °C per minute and 10 °C per minute, respectively-whereas the second variant relied on the fast-25 °C per minute-heating of treated specimens to a temperature of 475 °C, at which, the nitrogenous potential of the atmosphere promotes faster nitrogen diffusion deep into the nitrided substrate, followed by reheating up to the nitriding temperature at different rates: 1 °C per minute, 2 °C per minute, 5 °C per minute, and 10 °C per minute, respectively. To evaluate the impact of heating rate kinetics and effectiveness during nitriding on the obtained surface layer quality, we investigated the phase composition, microhardness distribution, and thickness of the obtained diffusion layers. It was found that heating to a temperature of 475 °C in the nitriding process does not significantly affect the average mass gain of a sample. Above this temperature, within the range of nitriding temperatures, the extension of time increases the sample's mass gain. Simultaneously, it was found that the use of a constant heating rate allows for thicker nitrided layers and a greater sample hardness to be obtained. Dual-stage heating, in turn, is more effective in the context of sample mass gain per time unit.

Experimental visualization of mass transfer from a slug bubble during co-current flow in a conventional channel

Process intensification during gas–liquid flows is of paramount importance to optimize the size of the chemical reactors. This paper results from an investigation of the mass transfer visualization in a millimetric tube by using the colorimetric technique. A slug bubble train has been established in a 3.8 mm diameter tube for different gas superficial velocities and a constant liquid superficial velocity resulting in the low capillary number range between 0.0004<Ca<0.0006. Color-inducing dye Resazurin solution interacts with the Oxygen bubble to induce the pink color in the solution which has been captured by a high-speed camera. The liquid slug entrapped between the bubbles has three distinct regions namely, the central stem which has a stagnation point ahead of the bubble, the wall lubrication layer, and an entrapped Taylor vortex between the central stem and wall lubrication layer. Flow visualization results have been correlated with the penetration theory-based mass transfer models.

Predicting the Flow Behavior and Residence Time Distribution in Chemical Reactors: A Simplified and Fast Approach Using Smoothed Particle Hydrodynamics

AbstractUnderstanding the flow dynamics of chemical species is important for characterizing, analyzing, and designing chemical reactors. Computational fluid dynamics (CFD) provides accurate flow patterns, but this approach can be computationally expensive for large or complex geometries. To overcome this limitation, a new Lagrangian‐based method is developed using smoothed particle hydrodynamics (SPH) to forecast the flow patterns and residence time distribution of two different fluids for various reactor geometries: (laminar, fractal, T‐mixer, Hartridge–Roughton (H‐R) mixer and packed bed with a gyroid internal packing) and compared the results with computational fluid dynamics (CFD) simulations. The SPH method is less accurate than the CFD analysis, but it obtained the approximate flow behavior much faster. Consequently, the SPH method has significant potential as a first screening technique to optimize reactor topologies and internal packing structures.

Optimisation of synthesis parameters for Co-Mo/MgO catalyst yield in MWCNTs production

This study examined the impact of synthesis parameter on Cobalt-Molybdenum supported with magnesium oxide (Co-Mo/MgO) catalyst yield in production of multiwall carbon nanotube (MWCNT). Wet impregnation was used to synthesis the Co-Mo/MgO bimetallic catalyst, while a catalytic chemical vapour deposition reactor (CCVD) was used for the synthesis of carbon nanotubes (CNTs). Factorial and central composite design techniques were used to optimise the catalyst and multi-wall carbon nanotubes (MWCNTs). Thermogravimetric analysis/ Differential thermal analysis (TGA/DTA), selected area (electron) diffraction (SAED), X-Ray diffraction analysis (XRD), and Brunauer–Emmett–Teller (BET) were used to characterise the catalyst and MWCNTs that were produced. The Co-Mo/MgO catalyst had an optimal yield of 93.22%, 247.30 m2/g of specific surface area at 120 °C drying temperature, 16 g of mass support, and a 10-hour drying time. The maximum catalyst yield of 40.62% was obtained at calcination temperature of 500 °C and a holding period of 2 hours. The catalyst with the highest degradation temperature of 398.21 °C was observed at 600 °C, when calcined for 4 hours. It was discovered that the surface area of Co-Mo/MgO catalyst from the BET analysis under ideal conditions varied depending on the holding time. The XRD and SAED revealed the growth of CNTs of concentric graphene pattern with the Co-Mo/MgO catalyst.

A simplified mechanism of hydrogen addition to methane combustion for the pollutant emission characteristics of a gas-fired boiler

The reaction mechanism of hydrogen-enriched methane (HEM) combustion is significant in the combustion process. In this study, four widely used reaction mechanisms for methane combustion are simplified to investigate the pollutant emission characteristics of a gas-fired boiler used for HEM combustion. The laminar burn velocity (LBV) and ignition delay time (IDT) of the four detailed and four simplified mechanisms are compared, and the simplified San Diego mechanism is identified as the optimal mechanism using relative error and population standard deviation analysis. The temperatures and key components of the simplified San Diego mechanism are also compared with those of the detailed San Diego mechanism under various XH2. Based on the simplified San Diego mechanism, a chemical reactor network model for gas-fired boilers is further established to investigate the pollutant emissions of HEM combustion, in which the hydrogen doping ratio XH2 ranged from 0 to 80% and the inlet air and fuel temperature Tin ranged from 300 K to 600 K. Results showed that at Tin = 300 K with XH2 ranging from 0 to 80%, the mole fraction of NO increase by 1.94 times because of the increase in peak flame temperature; moreover, the mole fractions of N2O, CO, and CO2 decrease by approximately 25%, 50%, and 52%, respectively. With XH2 ranging from 0 to 40% and Tin ≥ 500 K, the mole fraction of NO decreases because the reduction reaction of NO + H = N + OH is promoted, whereas when XH2 is further increased to 80%, the increased H promotes the increase in NO again. CO emissions decreased as XH2 increased from 0 to 80%, whereas they increased by approximately 1.3 times as Tin increased from 300 K to 600 K because of the CO2 decomposition. N2O emissions decreased by more than 25% as XH2 increased from 0 to 80%. Additionally, CO2 emissions decrease by 52% with an increase in XH2 and by only 5% with an increase in Tin, indicating that XH2 has a larger impact on CO2 emissions. The proposed optimal HEM combustion mechanism is conducive to improving the efficiency of numerical calculations.

High-quality MOCVD-grown heteroepitaxial gallium oxide growth on III-nitrides enabled by AlOx interlayer

We report high-quality Ga2O3 grown on an AlGaN/AlN/Sapphire in a single growth run in the same Metal Organic Chemical Vapor Deposition reactor with an AlOx interlayer at the Ga2O3/AlGaN interface. AlOx interlayer was found to enable the growth of single crystalline Ga2O3 on AlGaN in spite of the high lattice mismatch between the two material systems. The resulting nitride/oxide heterogenous heterostructures showed superior material qualities, which were characterized by structural, electrical, and optical characterization techniques. In particular, a significant enhancement of the electron mobility of the nitride/oxide heterogenous heterostructure is reported when compared to the individual electron mobilities of the Ga2O3 epilayer on the sapphire substrate and the AlGaN/AlN heterostructure on the sapphire substrate. This enhanced mobility marks a significant step in realizing the next generation of power electronic devices and transistors.

Effect of adsorption-catalytic deformation and partial deactivation on the determination of the absolute activity of a liquid phase hydrogenation catalyst

Objectives. To take into account the change in the number of active sites during the adsorptioncatalytic deformation and deactivation of a catalyst surface by means of a catalytic poison when calculating the turnover frequency (TOF) of a hydrogenation catalyst.Methods. The activity was determined by a static method, using a titanium reactor having a volume of 400 mL, an experimental temperature controlled using a liquid thermostat with an accuracy of 0.5 K, with a paddle stirrer rotation speed of 3600 rpm and system hydrogen pressure equal to atmospheric. The consumption of hydrogen used to reduce the model compound was taken into account via the volumetric method. The heats of hydrogen adsorption were determined using a reaction calorimeter with an operating mode close to that of a chemical reactor. After measuring the specific surface area using low temperature nitrogen adsorption, the results were processed using Brunauer–Emmett–Teller theory approximations. Deactivation was carried out by introducing dosed amounts of catalytic poison into the system in titration mode.Results. A kinetic experiment for the reduction of a multiple carbon bond in a sodium maleate molecule using aqueous solutions of sodium hydroxide with additions of monohydric aliphatic alcohols as solvents under conditions of partial deactivation of the catalyst was carried out. The obtained values of heats of hydrogen adsorption on skeletal nickel in the course of the experiment are given. The described approach is used to calculate TOF values taking into account changes in the number of active surface sites during the course of a catalytic reaction and upon the introduction of a deactivating agent. A refined equation for the correct calculation of TOF is proposed along with its mathematical justification. The results of TOF calculations under various assumptions for a number of catalytic systems are shown.Conclusions. When calculating absolute activity values, a change in the number of active sites has a significant effect on the obtained values. The physical meaning of a number of constants in the proposed equation relates the activity of the catalyst to the distribution of hydrogen on its surface in terms of heats of adsorption.

A practically implementable reinforcement learning‐based process controller design

AbstractThe present article enables reinforcement learning (RL)‐based controllers for process control applications. Existing instances of RL‐based solutions have significant challenges for online implementation since the training process of an RL agent (controller) presently requires practically impossible number of online interactions between the agent and the environment (process). To address this challenge, we propose an implementable model‐free RL method developed by leveraging industrially implemented model predictive control (MPC) calculations (often designed using a simple linear model identified via step tests). In the first step, MPC calculations are used to pretrain an RL agent that can mimic the MPC performance. Specifically, the MPC calculations are used to pretrain the actor, and the objective function is used to pretrain the critic(s). The pretrained RL agent is then employed within a model‐free RL framework to control the process in a way that initially imitates MPC behavior (thus not compromising process performance and safety), but also continuously learns and improve its performance over the nominal linear MPC. The effectiveness of the proposed approach is illustrated through simulations on a chemical reactor example.

Numerical treatment via the spectral collocation method for Casson–Williamson nanofluid flow due to a stretching sheet with slip conditions

The main goal of the research is to investigate the effects of temperature and concentration slip on the MHD Casson–Williamson nanofluid flow through a porous sheet, with a focus on viscous dissipation. This research has a novel approach, as it seeks to incorporate various factors that have not been previously studied in this context. Moreover, an inclined magnetic field from the outside is applied to the stretched surface. Besides this, it is considered that the viscosity of nanofluids depends on temperature while all other physical characteristics are taken to be constant. It is hypothesized that the expanding surface that stretched exponentially is what caused the flow motions of the nanofluid. There are several engineering applications for this type of study, which is based on MHD non-Newtonian nanofluid flow across a stretched surface with heat generation and viscous dissipation. They include solar energy storage, energy distribution, chemical reactors, and the manufacturing of polymers. To examine the heat transmission and mass transfer rates, tools like thermophoresis and Brownian motion were implemented. The flow problem is formally represented as a set of nonlinear PDEs that are then, through the use of dimensionless variables, converted into a set of ODEs. To numerically obtain the solution to the problem, the shifted Chebyshev polynomials of the third-kind approximation along with the spectral collocation technique are utilized. This process transforms the existing model into an algebraic equation system that was created as a restricted optimization problem, which is then optimized to obtain the solution and the unknown coefficients. For a variety of pertinent parameter values, the graphic and tabular representations of the concentration, temperature, velocities, rate of heat mass transfer, and shear stresses of nano-fluids at the surface of the sheet are shown. Finally, there is a remarkable amount of agreement between the earlier investigation and the comparison research that was conducted. The findings suggest that higher values of the magnetic parameter, Casson parameter, viscosity parameter, and suction parameter lead to a decrease in both velocity and boundary layer thickness. Furthermore, an increase in the viscosity parameter, Casson parameter, and magnetic parameter results in elevated values for both temperature and concentration.

Design the mechanical–chemical reactor for oily wastewater treatment

This study explains the mechanical design of a mixer with a focus on the fluid forces generated by the fluid continuum in the mixing reactor on the impellers. The research demonstrates that the forces are caused by transient asymmetries in fluid flow that act on the mixing impeller. The mixer shaft and gear reducer receive these dynamic loads from the impeller blades. A general equation for the fluid force behavior can be developed. The research also stresses on the significance of the mechanical interaction of the mixing process with the mixing vessel and impeller. Four parameters were measured; impeller speed for coagulation and flocculation, mixing time for coagulation, and flocculation. The experimental results in the final section will explain that impellers with four blades provide higher oil removal than impellers with two blades in oily wastewater treatment.

Improvement Axial Dispersion Calculation in Fibrous Garnished Fixed Beds Using the Neural Method

To determine accurately the physical modeling of flow through porous media and / or in chemical reactors, especially in the field of low Reynolds numbers, it is essential to compute the coefficient of axial dispersion. In prior studies, we employed the neural method to compute axial dispersion within fixed beds with parallelepiped and spherical packings. In the present study we apply the same method of calculation on heterogeneous fixed beds with large anisotropy using data from Poirier and Trinh on fibrous beds. Such an investigation could be however very useful while one has the desire to predict the mixing process to characterize the axial dispersion in fixed beds of anisotropic particles and when experimental measurements are not accessible and / or difficult to implement as for reactors and / or industrial complex porous media. To show also the robustness and applicability of this method, the calculation results obtained will be modeled using expressions similar to those proposed by Poirier and Trinh, so that we can compare our results with those obtained by these authors, under the same operating conditions. Furthermore, our study offers a comprehensive analysis encompassing all three examined fixed bed configurations, namely parallelepiped, spherical, and fibrous arrangements.

Switching Event-Triggered Adaptive Resilient Dynamic Surface Control for Stochastic Nonlinear CPSs With Unknown Deception Attacks.

This work concentrates on the adaptive resilient dynamic surface controller design problem for uncertain nonlinear lower triangular stochastic cyber-physical systems (CPSs) subject to unknown deception attacks based on a switching threshold event-triggered mechanism. The adverse effect of deception attacks on the stochastic CPSs is that the exact system state variables become unavailable. Furthermore, it should be emphasized that the coexistence of unknown nonlinearities, stochastic perturbations, and unknown sensor and actuator attacks makes it a very difficult and challenging event to implement the control design. To get the desired controller, radial basis function (RBF) neural networks (NNs) are introduced so that the design obstacle caused from the unknown nonlinearities can be easily solved. On this basis, in order to save resources and effectively transmit, the event-triggered control scheme based on a switching threshold strategy is further considered. In the backstepping design process, the dynamic surface control (DSC) technique is presented to deal with the issue of "explosion of complexity." By skillfully designing a new coordinate transformation and the attack compensators, the problem of unknown deception attacks is successfully handled. Under our proposed control scheme, all the closed-loop signals are bounded in probability and the stabilization errors converge to an adjustable neighborhood of the origin in probability. Finally, the simulation results on the double chemical reactor show the validity of the proposed design scheme.

Numerical solution of one inverse problem for a diffusion model of a chemical-technological process

A chemical-technological process taking place in a chemical reactor with a chemical reaction of the second order is considered. A one-dimensional one-parameter diffusion model of the hydrodynamic flow in the reactor is proposed for the mathematical description of this process. Within the framework of the proposed model, the inverse problem is posed to determine the concentration of the selected reagent in the incoming flow, ensuring the implementation of a predetermined hydrodynamic regime at the reactor outlet. A discrete analogue of the inverse problem is constructed and the resulting difference problem is presented as a variational problem with local regularization. A special representation is proposed for the numerical solution of the variational problem. As a result, an explicit formula is obtained for determining the approximate concentration of the selected reagent in the incoming stream. The effectiveness of the proposed method is illustrated by numerical calculations for model problems

A Challenge to Solve Complicated Nonlinear Differential Equations in the Engineering Fields and Basic Sciences by New Approach AKLM

In this manuscript, we claim that many complicated applied problems in nonlinear differential equations can be answered analytically.And as far as the researchers know, the application of analytical (not numerical) solution in the field of engineering and basic sciences is very important.These virgin methods can be successfully applied in various engineering fields such as mechanics (solid, fluid,heat and mass transfer), electronics, petroleum industry, designing chemical reactors, and also in applied sciences, economics and so on. It is worth noting that these methods are convergent at any form of differential equations, including any number of initial and boundary conditions. During the solution procedure, it is not required to convert or simplify the exponential, trigonometric and logarithmic terms, which enables the user to obtain a highly precise solution This method can be very valuable in solving engineering and basic science problems, and even economics, as a result, we present this method in this article for academic researchers.

Prediction of NOx emissions and pathways in premixed ammonia-hydrogen-air combustion using CFD-CRN methodology

Ammonia-hydrogen blends have gained significance as they are carbon-free energy-dense fuels. However, NOx emissions have been a significant concern. In this study, the emissions from the premixed combustion of 70/30VOL.% NH3/H2 blend is studied using the computational fluid dynamics (CFD)- chemical reactor network (CRN) approach. The velocity, temperature, and species field are first obtained using CFD, based on which, a network consisting of perfectly stirred reactors (PSR) and plug flow reactor (PFR) is constructed. Three mechanisms have been implemented in the CRN to predict the NO and N2O emissions. It is shown that the trend of NOx is correctly predicted by the CRN over a wide range of equivalence ratios (φ) of 0.65–1.2 as compared to the authors’ recently published experimental data. It is demonstrated that a single CRN (based on the CFD for a specific φ) can be run to cover the range of φ = 0.65 to 1.2 b y scaling the temperature input to each reactor of the CRN. To contrast the NO pathways at different φ, quantitative reaction pathway diagrams (QRPD) are constructed, and dominant production and consumption pathways of NO for lean and rich combustion are established. The shifts in reaction pathways with φ are noted and found to be governed by OH, O, and H radicals. Next, the effect of stoichiometry on these radicals is established. Finally, the experimental trend of high NO close to stoichiometric combustion and high N2O in very lean combustion along with their respective pathways are explained.

Downsizing Sustainable Aviation Fuel Production with Additive Manufacturing—An Experimental Study on a 3D printed Reactor for Fischer-Tropsch Synthesis

Sustainable aviation fuels (SAF) are needed in large quantities to reduce the negative impact of flying on the climate. So-called power-to-liquid (PtL) plants can produce SAF from renewable electricity, water, and carbon dioxide. Reactors for these processes that are suitable for flexible operation are difficult to manufacture. Metal 3D printing, also known as additive manufacturing (AM), enables the fabrication of process equipment, such as chemical reactors, with highly optimized functions. In this publication, we present an AM reactor design and conduct experiments for Fischer-Tropsch synthesis (FTS) under challenging conditions. The design includes heating, cooling, and sensing, among others, and can be easily fabricated without welding. We confirm that our reactor has excellent temperature control and high productivity of FTS products up to 800 kgC5+ mcat−3 h−1 (mass flow rate of hydrocarbons, liquid or solid at ambient conditions, per catalyst volume). The typical space-time yield for conventional multi-tubular Fischer-Tropsch reactors is ~100 kgC5+ mcat−3 h−1. The increased productivity is achieved by designing reactor structures in which the channels for catalyst and cooling/heating fluid are in the millimeter range. With the effective control of heat release, we observe neither the formation of hot spots nor catalyst deactivation.