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Hydrogenation of CO 2 to hydrocarbons in fixed-bed and annular reactors (AR) can be limited via problems associated with high water production as the main by-product. Selective in-situ water removal using a hydrophilic membrane can be a promising solution for enhancing reactor performance. To this aim, a one-dimensional heterogeneous model comprising mass and heat transfers in the shell and tube of a membrane reactor (MR) is proposed. Firstly, the performance of different rector configurations exhibiting similar cross sectional areas and volumes are compared. Afterwards, influential factors affecting the MR performance such as shell/tube temperature, sweep ratio (θ) and pressure ratio (φ) are investigated thoroughly. Results show that increasing initial tube/shell temperature has positive effect on total hydrocarbons yield. However, sharp and sudden temperature elevation (hot spot) due to large extent of water removal, may have detrimental effects on catalyst performance. Moreover, it is observed that increasing θ and φ alter products distribution due to the equilibrium displacement and results in the lack of H 2 for further reactions. In addition, kinetic parameters corresponding to the inhibiting effect of water are indicated to have significant roles in hydrocarbons distribution. Therefore, water removal impose various changes, which cannot be considered independently in analyzing the MR performance. Image 1 • Modeling of CO 2 hydrogenation in membrane reactor is presented. • Effect of in-situ water removal on the reactor performance is analyzed. • Hydrocarbons distribution and reactor temperature are assessed in AR and MR. • Effect of sweep ratio and sweep pressure on products yield are studied. [ABSTRACT FROM AUTHOR]

Abstract Global warming, climate change, fossil fuel depletion and steep hikes in the price of environmentally friendly hydrocarbons motivate researchers to investigate CO 2 hydrogenation for hydrocarbons production. However, due to the reaction complexities and varieties of produced species, the process mechanism and subsequently estimation of the kinetic parameters have been controversial yet. Therefore, estimating the kinetic parameters using Artificial Bee Colony (ABC) and Differential Evolution (DE) optimization algorithms based on Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism is proposed as a possible remedy to fulfil the requirements. To this end, a one-dimensional heterogeneous model comprising detailed reaction rates of reverse water gas shift (RWGS), Fisher-Tropsch (FT) reactions and direct hydrogenation (DH) of CO 2 is developed. It is observed that ABC exhibiting 6.3% error in predicting total hydrocarbons selectivity is superior to DE algorithm with 32.9% error. Therefore, the model employed the estimated kinetic parameters obtained via ABC algorithm, is exploited for products distribution analysis. Results reveal that maximum 73.21% hydrocarbons (C 1 C 4) selectivity can be achieved at 573 K and 1 MPa with 0.85% error compared to the experimental value of 72.59%. Accordingly, the proposed model can be exploited as a powerful tool for evaluating and predicting the performance of CO 2 hydrogenation to hydrocarbons process. Graphical abstract Image 1 Highlights • Studying kinetic parameters of CO 2 hydrogenation has remained controversial. • One-dimensional heterogeneous model including detailed reaction rates is developed. • Kinetic parameters are estimated via ABC and DE algorithms using experimental data. • Components distribution along reactor length are presented based on ABC algorithm. • Performance of the theoretical reactor is compared with available experimental data. [ABSTRACT FROM AUTHOR]

• Modeling of CO 2 hydrogenation to hydrocarbons in a three-side reactor is developed. • Tr, Ts, Tt, θ and φ are considered as main effects in determining product yields. • Statistical analysis is performed to study the effects of variables on the yields. • Optimized operating conditions are determined to maximize olefin yields. Direct CO 2 hydrogenation to hydrocarbons is a promising method of reducing CO 2 emissions along with producing value-added products. However, reactor design and performance have remained a challenging issue because of low olefin efficiency and high water production as a by-product. Accordingly, a one-dimensional non-isothermal mathematical model is proposed to predict the membrane reactor performance and statistical analysis is used to assess the effects of important variables such as temperatures of reactor (Tr:A), shell (Ts:B) and tube (Tt:C) as well as sweep ratio (θ:D) and pressure ratio (φ:E) and their interactions on the products yields. In addition, the optimized operating conditions are also obtained to achieve maximum olefin yields. Results reveal that interacting effects comprising AB (TrTs), AC (TrTt), AE (Trφ), BC (TsTt), CE (Ttφ), CD (Ttθ) and DE (θφ) play important roles on the product yields. It is concluded that higher temperatures at low sweep and pressure ratios can maximize the yields of olefins, while simultaneously the yields of paraffins are minimized. In this regard, optimized values for Tr, Ts, Tt, θ and φ are determined as 325 °C, 306.96 °C, 325 °C, 1 and 1, respectively. [ABSTRACT FROM AUTHOR]

The development of an efficient reactor for hydrocarbons (C 2 –C 4) production through hydrogenation of CO 2 , requires a deep understanding of the operating conditions effects. Subsequently, a model is proposed to analyze the reaction rates and investigate the sensitivity of hydrocarbons yield and products distribution to the variations of temperature, pressure and space velocity (SV). Besides, Thiele modulus and effectiveness factor are calculated for all of the reactions considered in the model. Results reveal that simultaneous occurrence of both endothermic reverse water gas shift (RWGS) and exothermic Fischer-Tropsch (FT) reactions, may be the main reason of temperature and rate fluctuations at the fixed-bed reactor inlet. In addition, increasing temperature and pressure, and decreasing SV can shift the process to produce more light olefins. Finally, sensitivity analysis demonstrates that reactor behavior is independent of the changes in pressure and SV at high temperature, which is an indication of high temperature dependency of this process. These findings can be effectively employed to achieve a better insight about appropriate operating conditions of hydrocarbons production via hydrogenation of CO 2. Image 1 • Effectiveness factor and Thiele modulus for all reactions are calculated. • Sensitivity analysis are performed via the mathematical modeling of reactor. • Variations of reaction rates and reactor temperature are analyzed. • Effect of temperature, pressure and space velocity on products are studied. [ABSTRACT FROM AUTHOR]

• Modeling of CO 2 hydrogenation to hydrocarbons in CR, AFSR and RFSR are accomplished. • Kinetic parameters are estimated via heuristic DA optimization algorithm. • Performance of the theoretical CR is compared with available experimental data. • Effect of reactor configuration is investigated in terms of conversion and selectivity. Climate change and global warming, as well as growing global demand for hydrocarbons in industrial sectors, make great incentives to investigate the utilization of CO 2 for hydrocarbons production. Therefore, finding an in-depth understanding of the CO 2 hydrogenation reactors along with simulating reactor responses to different operating conditions are of paramount importance. However, the reaction mechanisms for CO 2 hydrogenation and their corresponding kinetic parameters have been disputable yet. In this regard, considering the previously proposed Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism, which considered CO 2 hydrogenation as a combination of reverse water gas shift (RWGS) and Fischer-Tropsch (FT) reactions, and using a one-dimensional pseudo-homogeneous non-isothermal model, kinetic parameters of the rate expressions are estimated via fitting experimental and modelling data through a novel swarm intelligence optimization technique called dragonfly algorithm (DA). The predicted reactants conversion using DA algorithm are closer to the experimental data (with about 4% error) comparing to those obtained by the artificial bee colony (ABC) algorithm, and are in significant agreement with available literature data. The proposed model is used to assess the effect of reactor configuration on the performance and temperature fluctuations. Results show that axial flow spherical reactor (AFSR) and radial flow spherical reactor (RFSR) exhibiting the same surface area with that of the cylindrical reactor (CR), i.e., AFSR-2 and RFSR-2-i are the most efficient exhibiting hydrocarbons selectivity of 40.330% and 40.286% at CO 2 conversion of 53.763% and 53.891%. In addition, it is revealed that the location of the jacket has an essential role in controlling the reactor temperature. [ABSTRACT FROM AUTHOR]