Optimal Reactor Design Research Articles

Optimization of shunt reactor design using evolutionary algorithms: PSO and DE

Optimization of shunt reactor design using evolutionary algorithms: PSO and DE

Co‐Pyrolytic Recycling of Bakelite and Polymethyl Methacrylate: Kinetic, Synergistic, and Thermodynamic Analysis

AbstractBakelite, a thermosetting plastic, has limited feasibility for thermal recycling processes such as pyrolysis, unlike thermoplastics, due to its inherent tendency to get charred upon heating and difficulty in being converted into valuable fuel and chemical compounds. In this study, the co‐pyrolysis of bakelite and poly methyl methacrylate is explored to improve the thermal degradation and thus recycling feasibility of bakelite by pyrolysis. The kinetics and thermodynamics of the co‐pyrolysis of blended samples are analyzed using different kinetics models. The thermal degradation experiments of the sample are conducted from ambient to 1000 °C at five various heating rates of 5, 10, 20, 30, and 50 °C/min in an inert N2 gas environment. The results showed that adding poly methyl methacrylate to bakelite changes the pyrolytic degradation temperature and weight loss trend. The kinetic analysis reveals that the thermal degradation at 220–345 °C follows an F2.5 order‐based model with an average activation energy of 181 kJ/mol, while the degradation at 345–475 °C follows an F2 order‐based model with an average activation energy of 318 kJ/mol. The enthalpy changes and free energy change associated with thermal degradation exhibit a positive trend while that of entropy change shows a negative trend. With blending the free energy change and entropy change decreased while enthalpy change increased. During batch pyrolysis at 450 °C, the PMMA‐Bakelite blend generates oil (49.17 %), wax (12.36 %), residue (15.36 %), and gas (23.11 %). According to FTIR and GC‐MS analyses, the pyrolytic oil produced by the co‐pyrolysis of the blended sample at 450 °C comprises 32.23 % saturated hydrocarbons (C9–40), 20.97 % unsaturated hydrocarbons (C6–24), and 46.80 % oxygenated material (C5–19). These findings can assist in the optimization of pyrolysis reactor design for the recycling of thermosetting plastics.

Strategic integration of metamaterials properties and topology optimization of gyroid metal hydride reactor for high-density hydrogen storage

Metal hydride (MH) is considered to be one of the potential materials for storing hydrogen. It has a substantial limitation to wide use in the mobility sector, which is its low gravimetric hydrogen storage density. A novel canister design utilizing the optimization of gyroid structure for MH-based hydrogen storage is proposed to enhance reactor strength and capacity, increasing the favor of using it outside stationary applications. Topology optimization (TO) of the reactor increases the capacity by 49 % while maintaining the capability of this reactor to sustain 5000 N of bending case. On top of that, changing the metamaterial properties of the gyroid results in a larger chamber size for storing a larger amount of MH by the maximum amount of 30 %. However, increasing the chamber size comes with a cost of a lower charging rate and a considerable area of non-reacted hydride at the same charging time compared to the non-modified structure. By evaluating the MH bed that consists of lanthanum nickel (LaNi5), the topologically optimized reactor design is varied with different chamber offsets of 0, 2, and 4 mm. The results show that using a 2 mm offset in this study case can increase hydrogen storage capacity by 22 % while maintaining the same charging time of less than 4500 s. The combination of both proposed methods can increase the overall MH bed chamber by 66.22 % compared to previous initial research that acts as proof of concept.

An Optimal Radiation Shield Design of a Small Modular Nuclear Power Reactor by Genetic Algorithm

One of the critical concerns in developing small modular nuclear reactors (SMRs) is employing efficient radiation shielding consistent with the design and implementation requirements. Besides observing the radiation shielding requirements, the design process entails developing compact, lightweight shielding as well as ensuring the safety of the staff and radiation-sensitive equipment around the reactor under different operating conditions. Conventional methods of radiation shielding design are based on experiments conducted. Therefore, the resultant design involves trial and error, rarely achieving an optimal, effective, and efficient design. In this study, a multi-objective method based on the genetic algorithm coupled with the MNCP calculation code has been used to enhance the radiation shielding system of a SMR. Using this method, the thickness of different shielding layers has been optimized to minimize the total dose (neutrons and gamma) at the output, the weight, and the overall volume of the shielding. To assess and compare the method used to an implemented conventional method, a sample design of the MRX nuclear power reactor is considered. Using the optimization technique, the radiation shielding of the reactor has been redesigned and compared with the original design. This paper discusses the existing deficiencies in the initial design of the primary shield of the reactor as a design implemented based on conventional methods. Similar to the original design, the main materials considered for radiation shielding in consecutive layers were water and steel, and the final layer contained lead. The thickness of the different layers and their arrangements have been optimized to assess the upgraded method. The calculations indicate that the overall thickness of the proposed shielding is suggested as 93.8 cm compared to 140 cm to obtain the total dose of neutrons and gammas, which is suggested as less than 10 µSv/h. The results imply a 38.56% reduction in volume and a 17.24% reduction in weight of the radiation shielding compared to the reference reactor design.

A comparative study of metal-sulphide/ZnO for visible-light-induced photocatalysis and the six-flux photon absorption model of an external lamp photoreactor

This study compares the photocatalytic performance of three metal-sulphide/ZnO nanocomposites (Ag2S/ZnO, FeS/ZnO and NiS/ZnO) for degrading tetracycline (TC) under visible light irradiation. The nanocomposites were synthesized using a novel one-pot solid-phase combustion method, analysed by various characterization techniques (XRD, SEM, TEM, BET, FTIR, PL, and UV–vis DRS). Photocatalytic tests revealed significantly higher efficiencies for Ag2S/ZnO (87.50 %), FeS/ZnO (80.53 %) and NiS/ZnO (77.27 %) nanocomposites exhibit much higher photocatalytic efficiency than pure ZnO (42.63 %). The improved performance is attributed to the reduced bandgap energy and suppressed electron-hole (e-/h+) recombination facilitated. This can also be attributed to the photocatalytic inhibition test which confirmed the holes (h+) as the main inhibitor and identified the superoxides (O2•−) radical as the main active specie responsible for the degradation. Additionally, this study innovatively applies the Six Flux radiation absorption-scattering models (SFM) to an external lamp photocatalytic reactor. This approach allows precise determination of reactor parameters and intrinsic reaction kinetics for TC degradation, independent of the radiation field. The TC degradation rate, calculated at 5.6 × 104EinL−1S−1 for every point in the reaction space, shows a half-order dependence on the local volumetric rate of photon absorption (LVRPA) of 142.3 W/m3, at a photon flux of 115.42 W/m2. These findings elucidate the mechanisms behind enhanced visible-light photocatalysis and demonstrate the innovative application of photon absorption and light-scattering models to optimize reactor design and efficiency. This work offers valuable insights for developing advanced photocatalytic systems with improved performance and practical applicability.

A comprehensive review of flue gas bio-mitigation: chemolithotrophic interactions with flue gas in bio-reactors as a sustainable possibility for technological advancements.

Flue gas mitigation technologies aim to reduce the environmental impact of flue gas emissions, particularly from industrial processes and power plants. One approach to mitigate flue gas emissions involves bio-mitigation, which utilizes microorganisms to convert harmful gases into less harmful or inert substances. The review thus explores the bio-mitigation efficiency of chemolithotrophic interactions with flue gas and their potential application in bio-reactors. Chemolithotrophs are microorganisms that can derive energy from inorganic compounds, such as carbon dioxide (CO2), nitrogen oxides (NOx), and sulfur dioxide (SO2), present in the flue gas. These microorganisms utilize specialized enzymatic pathways to oxidize these compounds and produce energy. By harnessing the metabolic capabilities of chemolithotrophs, flue gas emissions can be transformed into value-added products. Bio-reactors provide controlled environments for the growth and activity of chemolithotrophic microorganisms. Depending on the specific application, these can be designed as suspended or immobilized reactor systems. The choice of bio-reactor configuration depends on process efficiency, scalability, and ease of operation. Factors influencing the bio-mitigation efficiency of chemolithotrophic interactions include the concentration and composition of the flue gas, operating conditions (such as temperature, pH, and nutrient availability), and reactor design. Chemolithotrophic interactions with flue gas in bio-reactors offer a potentially efficient approach to mitigating flue gas emissions. Continued research and development in this field are necessary to optimize reactor design, microbial consortia, and operating conditions. Advances in understanding the metabolism and physiology of chemolithotrophic microorganisms will contribute to developing robust and scalable bio-mitigation technologies for flue gas emissions.

Optimization of Active Chlorine Production in a Filter-Press Type Electrochemical Reactor through Continuum Modelling and Response Surface Methodology

This study proposes a methodology to optimize the design of an electrochemical flow-by reactor to increase the active chlorine production. The performances of various reactor configurations were evaluated using Computational Fluid Dynamics, starting from the dimensions of the well-known FM01-LC reactor channel (B = 4 cm, L = 16 cm, and S = 1 cm), increasing or decreasing each component by 25%. These conditions were calculated using a Box-Behnken design of experiments, screening out the above dimensions as parameters in addition to the volumetric flow, which was operated at two different rates: 1 and 5 l min−1. A surface response methodology (RSM) was utilized to optimize the response variables, and determine the best design parameters. The combined computational study herein proposed suggests that the optimization of the flow electrochemical reactor design is a compromise between the flow uniform distribution, and mass transfer. It is found that the optimization method used is adequate at the experimental level, since the optimized channel (0.01 M) presents better performance than the conventional FM01-LC channel (0.002 M), after 60 min of experimental electrolysis. It is expected the current analysis will contribute to the development of new filter-press-type electrochemical reactors optimizing chlorine production for numerous applications.

A numerical compass for experiment design in chemical kinetics and molecular property estimation

Kinetic process models are widely applied in science and engineering, including atmospheric, physiological and technical chemistry, reactor design, or process optimization. These models rely on numerous kinetic parameters such as reaction rate, diffusion or partitioning coefficients. Determining these properties by experiments can be challenging, especially for multiphase systems, and researchers often face the task of intuitively selecting experimental conditions to obtain insightful results. We developed a numerical compass (NC) method that integrates computational models, global optimization, ensemble methods, and machine learning to identify experimental conditions with the greatest potential to constrain model parameters. The approach is based on the quantification of model output variance in an ensemble of solutions that agree with experimental data. The utility of the NC method is demonstrated for the parameters of a multi-layer model describing the heterogeneous ozonolysis of oleic acid aerosols. We show how neural network surrogate models of the multiphase chemical reaction system can be used to accelerate the application of the NC for a comprehensive mapping and analysis of experimental conditions. The NC can also be applied for uncertainty quantification of quantitative structure–activity relationship (QSAR) models. We show that the uncertainty calculated for molecules that are used to extend training data correlates with the reduction of QSAR model error. The code is openly available as the Julia package KineticCompass.Graphical

Multiphysics and multi-scale design and analysis of nuclear thermal propulsion pellet bed reactor based on spherical cermet fuel element

Due to the advantages of high thrust and high specific impulse, nuclear thermal propulsion (NTP) is a preferred near-term rocket engine technology for future Mars missions. This article introduces the reactor design based on spherical cermet fuel element, with the aim of studying the feasibility of applying this new fuel in NTP system. First, design requirements are determined based on the unique features of NTP. In terms of neutronics, the effect of rocket launch accidents and fuel loss caused by high-temperature hydrogen are considered. Thermal hydraulics refer to the requirements of NASA's Mars Design Reference Architecture 5.0 (DRA 5.0) for impulse, thrust, and thrust to weight ratio. Second, based on the requirements above, the optimal reactor configuration parameters are obtained with the goal of maximizing the thrust to weight ratio: reactor radius 51.1 cm, height 106 cm, aspect ratio 1.04, reflector 13 cm, and reactor mass 3940 kg. Finally, the performances of the optimal reactor design are analyzed. The neutron spectrum shows a characteristic of fast neutron spectrum, and fuel loss analysis shows that the core can withstand a fuel mass loss of about 4 wt%. In addition, the core axial and radial power distribution are calculated, with an overall power peak factor of 1.26. The thermal hydraulic calculation provides a range of core operating conditions that satisfy the design requirements of DRA 5.0 and temperature, with power of 620 ∼ 950 MW and flow rate of 16 ∼ 24 kg/s. Compared with the ANL200/2000 reactor using prismatic cermet, it has the advantage of higher specific impulse. The main disadvantage is the large pressure drop, which prevents it from being applied to the scenarios of high power and high thrust. Therefore, for NTP reactor using spherical cermet elements, it should be applied to low to medium power scenarios.

Towards Semi-Solid Organic Redox Flow Batteries: Material Screening, Electrochemical Performance, and Reactor Design Optimization

As our society transitions to cleaner sources of energy, the need for stationary electricity storage becomes increasingly important. In this context, redox flow batteries (RFBs) have emerged as a promising solution to provide electricity storage at full scale, due to their high scalability and flexibility. However, despite the growing research interest, there is still a urgent need of novel batteries, which are able to operate at high energy densities while relying on sustainable, abundant, and cost-effective electrolytes.In this work we report the development of novel semi-solid RFBs based on cost-effective and environmentally friendly organic materials. We have systematically screened different classes of organic molecules, to identify suitable redox couples that can operate under stable conditions (i.e., >5,000 cycles) in a wide pH range. Therefore, we have experimentally investigated the most promising redox couples in a 10-cm2 electrochemical cell, to understand the behavior of the systems under different carbon and active molecule loadings. Finally, we have simulated the performance of the battery under dynamic and steady-state conditions, aiming to quantify the influence of fluid dynamics and rheological properties of the carbon slurry on the electrochemical performance. Based on our simulations results, we have identified new reactor designs for the RFB, aiming to optimize both fluid dynamics and electrochemical performance of the battery. Such designs represent an important first step towards future upscaling strategies.

Advancements in CO2 methanation: A comprehensive review of catalysis, reactor design and process optimization

Renewable electricity, production/storage and distribution of green hydrogen and carbon dioxide emission reduction are just three of the practices needed for a net zero-emission world. The increasing amount of renewable energy produced requires the development of versatile technologies capable to store the excess renewable electricity produced. Hydrogen production through electrolysis, despite not being still economically viable, can be considered a mature technology. Different strategies to convert H2 into more volumetric dense fuel are under development through Power-to-Chemicals (PtC) process. Among these, CO2 methanation offers the advantage of a wide infrastructure available for the distribution and use of methane as chemical and fuel for both heat and power generation. The latter approach is also called Power-to-Gas (PtG) process. These technologies in the last year have been the focus of research, both public and private. In particular, direct methanation of biogas obtained from anaerobic digestors represents a challenge and an interesting opportunity due to the possibility to avoid the CO2 separation step at the moment needed for biogas purification to biomethane. Since CO2 separation is an additional cost, this route can be the key for economic sustainability of the process. In this review we focus on the main aspects involved in the design of a methanation plant, with a particular focus on the biogas methanation, starting from the reaction thermodynamics and kinetics. Afterwards, light is shed on the most interesting catalysts reported in the literature, with a focus on Ni-based catalysts and considering the support role in the reaction. Different kinetic approaches currently available and promising reactor types, including different simulation models, which are becoming increasingly fundamental in the reactor design and scale-up phase, are reported. Finally, the last chapter contains the most interesting and industrially relevant ongoing projects on direct biogas methanation.

Integrated kinetics-computational fluid dynamic-optimization for catalytic hydrogenation of CO2 to formic acid

As enormous research findings indicate, carbon dioxide (CO2) can be converted to important products such as formic acid using catalytic hydrogenation of CO2 technologies. In this work a three-dimensional computational fluid dynamic (CFD) reactor model for the catalytic hydrogenation of CO2 to formic acid in the presence of triethylamine and water was developed, and the nature of the flow and reaction occurring inside the reactor was demonstrated. A kinetic model which estimates kinetic rate expressions was also developed and validated using experimental data. The kinetic parameters from the kinetic model were used as reaction source terms for the CFD reactor model development. Sensitivity analyses were performed on the design variables by integrating the kinetic parameters from the developed kinetic model. The Bayesian optimization algorithm was used to optimize the catalytic CO2 hydrogenation reactor. The optimal design was acquired, and the CO2 conversion increased by 32.6% compared to the initial base case. An optimized reactor design was proposed for the catalytic hydrogenation of CO2 to formic acid within a catalytic trickle-bed reactor based on the integration of reaction kinetic modeling and CFD analysis. The integrated kinetic-CFD-optimization framework proposed in this work was effectively applied to the catalytic CO2 hydrogenation reactor and the results reported on this work could give important design and operational insight to the further development of catalytic CO2 hydrogenation reactors for CO2 to formic acid conversion in carbon capture and utilization applications.

The appearance of standing wave structures in the reaction medium during the diffusion development of the chain reaction process

Relevance. Understanding the dynamic behavior of radicals in reactors undergoing gas-phase oxidation of organic substances is crucial for optimizing reactor design and safety across industries. Purpose. This study aims to elucidate the emergence of standing wave structures influenced by feedback mechanisms in reactors with cylindrical and spherical symmetry, using mathematical principles governing the propagation of oscillations and shock waves in diffusion-driven chain reactions. Methodology. Materials and methods for the research included a computer simulation using MATHCAD 2001i, and comparative analysis of experimental data obtained from reactor experiments. The computational modeling revealed vivid formations of standing wave structures in reactors influenced by feedback mechanisms. Results. The impact of reverse connections in reactors with cylindrical and spherical symmetry significantly contributed to the formation of various standing wave structures of radical concentrations within the reaction zone. It was found that these structures were largely imperceptible visually and could only be observed when the reaction was accompanied by intense light emission. These visual representations served as compelling evidence of the intricate interplay between reaction kinetics and feedback effects. The study emphasized the importance of understanding and predicting the root causes of instabilities, ultimately enhancing the reliability and safety of reactors across various industries. The results demonstrated a correlation between specific feedback mechanisms and the spatial distribution of standing wave structures. Conclusions. The derived computational patterns, as presented in this paper, provide compelling evidence supporting the feasibility of standing wave structure formation within reactors when influenced by feedback mechanisms. The study unveiled the potential for fine-tuning reactor parameters to influence the formation and stability of these structures. The findings represented a significant stride towards a more comprehensive understanding of dynamic regimes in reactors, with implications for reactor design, operation, and safety protocols. The insights garnered from uncovering standing wave structures influenced by feedback mechanisms offered valuable opportunities to optimize reactor design and operational safety, leading to more efficient and sustainable processes

Research on optimization scheme for boiling heat transfer models of mini-channels casing-pipes once-through steam generator

The mini-channels casing-pipes once-through steam generator(MCOTSG) is used for a certain type of small modular reactor. The boiling heat transfer model is crucial to the accuracy of simulating the heat transfer process on the secondary loop of MCOTSG. In this paper, the heat transfer tubes of MCOTSG are taken as the research object. The thermal–hydraulic model of primary and secondary loops is established based on the RELAP5 program. Then the different nucleate boiling heat transfer models are calibrated and analyzed based on the experimental results of the steady state under low flow rate conditions. On this basis, the secondary loop heat transfer characteristics and the overall operating characteristics of OTSG under the transient state of feedwater flow rate reduction are simulated. The results of the steady state and transient state analysis show that the revised model that the Bertsch correlation is used to correct the Chen correlation performs the best in terms of computational stability and computational accuracy. The results of the study can provide a basis for the safety analysis and optimal design of MCOTSG and small modular reactor under low flow rate conditions.

High value-added syngas production by supercritical water gasification of biomass: Optimal reactor design

Supercritical water gasification (SCWG) emerges as a highly encouraging technique for the efficient generation of syngas from biomass feedstock. The performance of the SCWG reactor plays a pivotal role in determining the overall success of the process. This study employs a mathematical modeling and optimization method to design an optimal tubular-type reactor for the SCWG of biomass. First, the reactor is divided into cells, and mathematical models are established to describe the reactions within each cell, as well as the mass balances between cells. Afterwards, the optimal reactor design problem is formulated as a non-linear optimization problem, which involves integration of all the individual models along the reactor length. The objective is to maximize the high heating value (HHV) of gaseous products and simultaneously satisfying multiple constraints. Once the problem is solved, the optimal decision variables (i.e., reactor axial fluid temperature profiles, diameter and length) are obtained. Here, two reactor design scenarios are investigated to showcase the adaptability of this optimization method. The obtained outcomes indicate that non-isothermal reactors with a zigzag-shaped temperature profiles are more advantageous than traditional isothermal ones for high value-added syngas production. Specifically, optimal non-isothermal reactors can achieve a remarkable increase of 50.08% (i.e., 26.94 vs 17.95 MJ/kg glycerol) in the HHV of gaseous products compared to isothermal reactors. These findings provide valuable insights on designing efficient SCWG reactors for industrial high value-added syngas production.

Three-Dimensional-Printed Vortex Tube Reactor for Continuous Flow Synthesis of Polyglycolic Acid Nanoparticles with High Productivity.

Polyglycolic acid (PGA) nanoparticles show promise in biomedical applications due to their exceptional biocompatibility and biodegradability. These nanoparticles can be readily modified, facilitating targeted drug delivery and promoting specific interactions with diseased tissues or cells, including imaging agents and theranostic approaches. Their potential to advance precision medicine and personalized treatments is evident. However, conventional methods such as emulsification solvent evaporation via batch synthesis or tubular reactors via flow chemistry have limitations in terms of nanoparticle properties, productivity, and scalability. To overcome these limitations, this study focuses on the design and development of a 3D-printed vortex tube reactor for the continuous synthesis of PGA nanoparticles using flow chemistry. Computer-aided design (CAD) and the design of experiments (DoE) optimize the reactor design, and computational fluid dynamics simulations (CFD) evaluate the mixing index (MI) and Reynolds (Re) expression. The optimized reactor design was fabricated using fused deposition modeling (FDM) with polypropylene (PP) as the polymer. Dispersion experiments validate the optimization process and investigate the impact of input flow parameters. PGA nanoparticles were synthesized and characterized for size and polydispersity index (PDI). The results demonstrate the feasibility of using a 3D-printed vortex tube reactor for the continuous synthesis of PGA nanoparticles through flow chemistry and highlight the importance of reactor design in nanoparticle production. The CFD results of the optimized reactor design showed homogeneous mixing across a wide range of flow rates with increasing Reynolds expression. The residence time distribution (RTD) results confirmed that increasing the flow rate in the 3D-printed vortex tube reactor system reduced the dispersion variance in the tracer. Both experiments demonstrated improved mixing efficiency and productivity compared to traditional tubular reactors. The study also revealed that the total flow rate had a significant impact on the size and polydispersity index of the formulated PGA nanoparticle, with the optimal total flow rate at 104.46 mL/min, leading to smaller nanoparticles and a lower polydispersity index. Additionally, increasing the aqueous-to-organic volumetric ratio had a significant effect on the reduced particle size of the PGA nanoparticles. Overall, this study provides insights into the use of 3D-printed vortex tube reactors for the continuous synthesis of PGA nanoparticles and underscores the importance of reactor design and flow parameters in PGA nanoparticle formulation.

Photobioreactor Design for Polyhydroxyalkanoate Production Using Anoxygenic Photoheterotrophs: A Review

This review paper provides an overview of various types of photobioreactors (PBRs) that could be used for the production of polyhydroxyalkanoates (PHAs) using anoxygenic photoheterotrophs, with a focus on the design and operation of these systems. The paper highlights the potential of different PBRs based on reactor geometry and growth mode, and also examines the advantages and disadvantages of each PBR type and summarizes their suitability for PNSB-PHA production. The optimization of reactor design and operation is crucial for maximizing PNSB growth and PHA productivity. The self-immobilization of bacteria in granular sludge is a promising technology for wastewater treatment and the production of PHAs, while grooved-surface PBRs and porous-substrate PBRs have limitations due to difficult biomass harvesting in the former and the presence of aerobic conditions incongruent with PNSB culturing in the latter. Limitations exist with all solutions for maximizing rapid growth and maintaining high biomass concentrations due to the requirements of phototrophic growth.

Optimization of aluminum hydrolysis reactions and reactor design for continuous hydrogen production using aluminum wire feeding

The depletion of fossil fuels and the issues caused by CO2 emissions are driving changes in global energy approaches. In this context, hydrogen emerges as a new and clean energy carrier for the near future. In this study, a system that can produce hydrogen with a constant flow rate for on-demand applications is developed. Hydrolysis reactions of aluminum are utilized for hydrogen generation. Aluminum in the form of wire is used and the feeding issues have been solved. The parameters of the hydrolysis such as the solution temperature (25–80 °C), catalyzer concentration (1–4 M NaOH), aluminum quantity and aluminum wire diameter (0.6–1 mm) were optimized by adopting the response method (RSM) and using laboratory scale experiments. Aluminum hydrolysis reactions and aluminum transformations during the reactions are investigated by performing surface analyzes of the wire. Using the optimized data, the continuous hydrolysis reactor and the aluminum feeding mechanism are designed. The aluminum wire feeding system is computer controlled using a microcontroller-based code. Hydrogen production rates up to 350 ml min−1 have been accomplished. A fuel-cell in the range of 5–30 W is fed by the hydrogen generated by the hydrolysis reactor system and the stability of the hydrogen generation rate and hence of the electricity generation is proven. One of the original aspects of this study is the development of a process that continuously produces hydrogen using commercially available aluminum.

Controlled One-Step Synthesis of MOF-on-MOF Cocatalysts for Two-Channel Electrocatalytic Conversion of CO2 to Formic Acid.

The synthesis of efficient and highly selective catalysts and rational reactor design play decisive roles in the industrial application of the electrocatalytic carbon dioxide reduction reaction (CO2 RR). In this study, a dual-metal-organic framework (MOF) copper-based catalytic electrode is designed and prepared in one step by in situ synthesis on a foamed copper substrate. The MOF-on-MOF structure can effectively inhibit the generation of H2 and CO, and further enhance the selectivity of HCOOH. Furthermore, by using cheap and durable poly(tetrafluoroethylene) (PTFE) instead of an expensive and fragile GDE, the optimized reactor design improves the stability and durability of the gas channel and the replaceability of the electrode. The structure-optimized reactor has a maximum Faradaic efficiency of 89.2% in neutral medium, and an average current density of 26.1mAcm-2 in the flow cell, which has comparable performance to a GDE and can continue to operate stably. The use of PTFE improves the service life of the gas mass transfer channel, and the independent catalytic electrode can provide good catalytic efficiency. These results provide new insights into the reaction mechanism of structurally recombined double MOFs and PTFE-optimized CO2 RR reactor designs, providing technical support for the practical industrial application of the CO2 RR.

Assessment of State-of-the-art multiphase CFD modeling for subcooled flow boiling in reactor applications

Multiphase Computational Fluid Dynamics (M-CFD) has the potential to provide high fidelity simulation of complex boiling phenomena in Light Water Reactors (LWRs), thereby accelerating the development cycle and reducing the need for expensive large-scale experiments. M-CFD relies on two-phase closure models to consistently represent the relevant physical phenomena in flow boiling. However, the still incomplete understanding of the ability of these closures to accurately capture the underlying physics, limits the adoption of M-CFD in reactor development and design optimization. Due to the interaction of complex physical phenomena present in subcooled flow boiling, local measurements are necessary to assess the performance of existing closures. Furthermore, because previous validation was performed mostly on low pressure data, measurements at high pressure are needed to understand the performance of multiphase closures at PWR conditions. In this work, benchmarking was conducted using measured radial profiles of void fraction from subcooled flow boiling experiments of R12 refrigerant that reproduced density ratios and scaled flow conditions corresponding to PWR operation, called the DEBORA experiments. This work leverages recent advancements in momentum closures to perform a systematic assessment of the wall boiling representation by evaluating heat flux partitioning formulations and the associated closure relations. The influence and sensitivity of bulk boiling and condensation models were also evaluated. Using separate effect assessments and recent advancements in experimental understanding, this work presents a closure representation that demonstrates consistent predictions and is applicable to prototypical PWR conditions, while identifying areas for future improvement.