Chemical Reactor Research Articles

Identification of the coefficient in the diffusion model of hydrodynamic flow in a chemical reactor

This article analyzes in detail the actual problem of the spread of disinformation through various media resources and their impact on society. The main aspects of information consumption by Ukrainian society, in particular on the Internet, are highlighted, and the potential target audience is determined. Based on the analysis, a new intelligent system based on Natural Language Processing technology is proposed, which provides users with a comprehensive overview of the activity of each media resource. Available analogues with their advantages and limitations are examined in detail, emphasizing the significant advantages of the proposed intelligent system for increasing information literacy and countering disinformation. Refs.: 19 titles.

Aerodynamically Levitated Droplets as Small-Scale Chemical Reactors and Liquid Microprinters.

A thin liquid film spread over the inner surface of a rapidly rotating vial creates an aerodynamic cushion on which one or multiple droplets of various liquids can levitate stably for days or even weeks. These levitating droplets can serve as wall-less ("airware") chemical reactors that can be merged without touching-by remote impulses-to initiate reactions or sequences of reactions at scales down to hundreds of nanomoles. Moreover, under external electric fields, the droplets can act as the world's smallest chemical printers, shedding regular trains of pL or even fL microdrops. In one modality, the levitating droplets operate as completely wireless aliquoting/titrating systems delivering pg quantities of reagents into the liquid in the rotating vial; in another modality, they print microdroplet arrays onto target surfaces. The "airware", levitated reactors are inexpensive to set up, remarkably stable to external disturbances and, for printing applications, require operating voltages much lower than in electrospray, electrowetting, or ink jet systems.

ANN‐driven insights into heat and mass transfer dynamics in chemical reactive fluids across variable‐thickness surfaces

AbstractThis study investigates the heat and mass transfer dynamics in exothermic, chemically reactive fluids over variable‐thickness surfaces using advanced numerical methods and artificial neural networks (ANN). The importance of understanding these processes lies in their significant industrial applications, such as in chemical reactors and heat exchangers. We transformed nonlinear partial differential equations into ordinary differential equations and used the bvp4c numerical method to generate a comprehensive data set. The ANN model, trained with the Levenberg–Marquardt algorithm, was evaluated for its accuracy in simulating complex fluid dynamics and thermosolutal transport phenomena. Our results revealed that increasing the second‐grade fluid parameter enhanced skin friction by 20.38%, heat transfer rate by 1.16%, and mass transfer rate by 4.06%. The ANN model demonstrated high predictive precision with a validation mean squared error of . These findings highlight the effectiveness of the ANN methodology in providing precise simulations of fluid dynamics, which is crucial for optimizing industrial processes.

(Invited) Low Cost in Situ Electrosynthesis and Cycling of Quinone Negolytes in a Commercial Flow Battery Stack

Aqueous organic redox flow batteries (RFBs) potentially offer greatly lower capital cost relative to vanadium RFBs or even lithium-ion batteries, as they use no critical materials and are instead derived from very inexpensive precursors. To date, the success of organic RFBs as a whole has been hampered by two factors. The first is the high cost of scaling up a new chemistry, as every synthetic step adds cost and complexity and creates waste that must be disposed of. The second is fast degradation of the reactants and has been largely mitigated through various strategies that have recently been reported. The recent results mean that low-cost compounds that may intrinsically have a fast degradation rate, now merit consideration since their fade rate can be lowered significantly.We report the development of an in situ electrosynthesis process, from the lab scale to the ton scale, that creates the organic RFB negolyte from the starting reactants using commercial RFB stacks that have been repurposed as chemical reactors. The yield and purity are even higher than the equivalent chemical process and no further purification or downstream processing is required; the entire process is self-contained and produces zero waste which greatly simplifies scaleup, permitting, and implementation. Moreover, the as-produced material can be immediately cycled as a drop-in replacement for vanadium in RFBs with minimal modification of existing vanadium RFB designs.This unique in situ strategy enables rapid scaling of a new chemistry in a way that supports local manufacture, which is of strategic importance to many governments. Further cost reductions are envisioned if it can be implemented at the customer site -- inside a completed flow battery system -- rather than at a centralized facility.When combined with previous results on reversing the degradation of quinone RFB reactants, the electrosynthetic pathway to producing organic RFB negolytes is the final missing piece of the puzzle in the commercialization of an affordable, practical, and viable organic RFB chemistry.

A dual scale spatio‐temporal control for complex distributed parameter systems

AbstractIt is very difficult to control the distributed parameter system (DPS) for consistent spatial performance. In this paper, a dual scale spatio‐temporal control is designed for the DPS to achieve a consistent performance across the entire workspace under unknown exogenous disturbances. First, the generalized “spatial observer” should be designed under spectral decomposition/synthesis, to act as the nominal model of the DPS, through which the spatial mismatch between the model and the process could be estimated. Then a distributed disturbance compensator can be constructed to suppress all the undesirable spatial disturbance through the inner loop, and the compensated system will become closer to the nominal model and easier to control. Third, a dual controller will be designed in the outer loop for the final consistent spatial performance. Since the spatial performance is mainly affected by the dominant dynamics on the slow scale, a convex optimization algorithm can be effectively established in terms of nonlinear matrix inequalities for the dual controller. In this way, the nonlinear optimization problem is solved by converting it into the problem of a linear matrix inequalities with constraints. Besides, the spatio‐temporal state variable of the controlled plant is demonstrated to converge in Hilbert space. The feasibility and effectiveness of the proposed control method are verified by temperature control of a catalytic rod, a benchmark in chemical reactors.

Collaborative modelling of gas-solid reacting flow in a fuel reactor equipped with process controllers in chemical looping combustion/conversion

Chemical reactors usually feature complex internal reacting flows, and they are usually equipped with process controllers to stabilise their operations, especially for highly dynamic reactors including chemical looping combustion/conversion (CLC). However, their dynamic internal states are not well understood due to the lack of reliable research tools. In this work, for the first time, an innovative numerical collaborative model is developed to describe the reacting flow details and simulate the response to a process controller. The collaborative model is applied to a fuel reactor (FR) in a CLC to demonstrate its effectiveness. The detailed internal flow patterns in the FR are obtained and described by the three-phase reacting flow CFD model, and the circulating rate of oxygen carrier (OC) is controlled and optimised by the fuzzy logic controller (FLC). The controller is designed to operate at varying control time intervals, 1 s, 2 s, and 5 s, to study the optimal frequency for data sampling and feedback. The efficiency of the controller to the FR is tested in terms of OC circulation, gas components and the general performance of the reactor. The results show that the stability of OC circulating rate and performance are effectively improved by the process controller; among the three control intervals, the 2 s interval shows the highest feasibility and capability of maintaining stable OC circulation and CO2 yield in the FR. Quantitatively, compared to the base case without a controller, the range of OC circulating rates has been narrowed from [0.014, 0.534] to [0.018, 0.385] in control case A, [0.075, 0.342] in control case B, and [0.004, 0.530] in control case C. Meanwhile, the CO2 yield increased from 86.93 % in the base case to 87.98 % in control case A, 88.16 % in control case B, but decreased to 85.4 % in control case C due to poor controlling performance. The combustion efficiency increased from 84.20 % in the base case to 84.87 % in control case A, 86.22 % in control case B, and 85.88 % in control case C. Among all control cases, control case B presents the narrowest data range and highest efficiency, indicating optimal control performance in improving OC circulation stability. The deviation of OC circulating rate values decreases from 0.123 to 0.058, and the CO2 yield increases from 86.93 % to 88.16 % in control case B with a 2 s interval. This work provides a new cost-effective tool for real-time simulating and controlling the reacting flow system including CLC for clean combustion and solid wastes conversion.

Computational analysis of nanoparticles and waste discharge concentration past a rotating sphere with Lorentz forces

Abstract As industries rely more and more on magnetohydrodynamic (MHD) systems for different uses in power, production, and management of the environment, it becomes essential to optimize these operations. The study seeks to improve the effectiveness and productivity of cooling structures, chemical reaction reactors, and contaminant control methods by investigating these intricate interconnections. Because of this, the work scrutinizes the endothermic/exothermic (EN/EX) chemical processes, convective boundary conditions, and pollutant concentration impacts on MHD nanofluid circulation around a rotating sphere. The governing equations based on the above assumptions are reduced into a system of ordinary differential equations and solved numerically with Runge–Kutta Fehlberg’s fourth- and fifth- order schemes. The obtained numerical outcomes from the numerical scheme are presented with the aid of graphs, and the results show that the rate of mass transfer decreases with an increase in the external pollutant local source and solid volume percentage. For changes in the values of the activation energy parameter and solid fraction, the rate of thermal dispersion drops for the EN case and upsurges for the EX case. The concentration profile shows increment with the addition of the external pollutant source variation parameter and local pollutant external source parameter. The outcomes of the present work can be helpful in cooling equipment, developing advanced methods for controlling pollution, environmental management, MHD generators, and various industrial contexts.

Machine learning-assisted discovery of flow reactor designs

Additive manufacturing has enabled the fabrication of advanced reactor geometries, permitting larger, more complex design spaces. Identifying promising configurations within such spaces presents a significant challenge for current approaches. Furthermore, existing parameterizations of reactor geometries are low dimensional with expensive optimization, limiting more complex solutions. To address this challenge, we have established a machine learning-assisted approach for the design of new chemical reactors, combining the application of high-dimensional parameterizations, computational fluid dynamics and multi-fidelity Bayesian optimization. We associate the development of mixing-enhancing vortical flow structures in coiled reactors with performance and used our approach to identify the key characteristics of optimal designs. By appealing to the principles of fluid dynamics, we rationalized the selection of design features that lead to experimental plug flow performance improvements of ~60% compared with conventional designs. Our results demonstrate that coupling advanced manufacturing techniques with ‘augmented intelligence’ approaches can give rise to reactor designs with enhanced performance.

Comparative study of hybrid, tri-hybrid and tetra-hybrid nanoparticles in MHD unsteady flow with chemical reaction, activation energy, Soret-Dufour effect and sensitivity analysis over Non-Darcy porous stretching cylinder

Present study investigates influence of Soret-Dufour effects on MHD unsteady flow of a tetra-hybrid nanofluid (Al2O3, Cu, SiO2 and TiO2 with base fluid water) within non-Darcy porous stretching cylinder. Additionally, chemical reaction, activation energy, and heat generation are considered. This research contributes to the understanding of how these nanofluids can optimize heat and mass transfer process in applications such as advanced cooling systems, solar collectors, biomedical devices, and chemical reactors. Tetra-hybrid nanofluids are selected as per novel aspects for their exceptional ability to adapt their properties for diverse applications, including advanced thermal management systems and scenarios requiring high thermal and electrical conductivity. The comparison between hybrid, tri-hybrid, and tetra-hybrid nanofluids serves to evaluate how increasing complexity and diversity in nanoparticle combinations impact thermal and flow characteristics. The prevailing PDE's undergo transformation into nonlinear ODE's through the utilization of similarity variables and numerically solved using fifth order Runge-Kutta Fehlberg method with shooting method. It is established that rising unsteady parameter values result in increasing velocity profile and rising shape factor parameter result in higher heat transfer. Specifically, the Nusselt number increases by 24 % in the tri-hybrid and 11 % in the tetra-hybrid with a higher Soret number, whereas the Sherwood number decreases by 38 % in the tri-hybrid and 26 % in the tetra-hybrid nanofluid. Employing sensitivity analysis, this study also aims to investigate impact of output responses such as local Nusselt number and local Sherwood number on input parameter Dufour number, Soret number and chemical reaction parameter for tri-hybrid and tetra-hybrid nanofluid. It is found out that Dufour number in tetra-hybrid nanofluid has the more significant impact on the Nusselt number, whereas the Soret number predominantly affects the Nusselt number in tri-hybrid nanofluid. These findings underscore the potential of tetra-hybrid nanofluid in enhancing the performance of various industrial and environmental processes.

Investigation of a new method for direct chemistry integration in Conditional Source-term Estimation

This paper examines a new Conditional Source-term Estimation (CSE) implementation in which an integral inversion is performed for species mass fractions without any chemistry tabulation. To tackle the numerical stiffness due to chemistry, a constant-pressure chemical reactor is considered in conditional space. The objective of this work is to investigate this new method in CSE by comparing its numerical performance (accuracy of predictions and computational efficiency) with previous CSE implementations using tabulated chemistry. For the first time, the constraints for mass and mixture fraction conservation in conditional space are included in the inversion process. The investigation is performed in a Reynolds Averaged Navier-Stokes (RANS) framework using a well-documented turbulent flame with detailed measurements in conditional and physical spaces for many reacting scalars. A chemical mechanism including 16 species and 35 reactions is incorporated. CSE predictions of conditional and Favre averaged temperature and different species mass fractions are analysed. CSE with full chemistry performs as well as CSE with tabulated chemistry, if not slightly better. Numerical errors are discussed. The new CSE implementation is made possible by the proposed numerical treatment of stiffness due to chemistry and first-order Tikhonov regularisation technique with additional physical constraints. The new approach is found to be more CPU intensive than CSE with a pre-tabulation technique, but as a preliminary analysis, the computational cost of CSE with direct integration of a chemical mechanism appears to be much smaller than the run time associated with CMC for a similar set-up. Further investigation is required to refine this initial conclusion. These results open new opportunities towards CSE simulations that involve fuel blends and more complex operating conditions for example with spray and multi-stream inlets with non-uniform compositions for which accurate chemistry tabulations are difficult to generate.

Coordination engineering for iron-based hexacyanoferrate as a high-stability cathode for sodium-ion batteries

Iron-based hexacyanoferrate (Fe-HCF) are promising cathode materials for sodium-ion batteries (SIBs) due to their unique open-channel structure that facilitates fast ion transport and framework stability. However, practical implementation of SIBs has been hindered by low initial Coulombic efficiency (ICE), poor rate performance, and short lifespan. Herein, we report a coordination engineering to synthesize sodium-rich Fe-HCF as cathodes for SIBs through a uniquely designed 10-kg-scale chemical reactor. Our study systematically investigated the relationship between coordination surroundings and the electrochemical behavior. Building on this understanding, the cathode delivered a reversible capacity of 99.3 mAh g-1 at 5 C (1 C = 100 mA g-1), exceptional rate capability (51 mAh g-1 even at 100 C), long lifespan (over 15,000 times at 50 C), and a high ICE of 92.7%. A full cell comprising the Fe-HCF cathode and hard carbon (HC) anode exhibited an impressive cyclic stability with a high-capacity retention rate of 98.3% over 1,000 cycles. Meanwhile, this material can be readily scaled to the practical levels of yield. The findings underscore the potential of Fe-HCF as cathodes for SIBs and highlight the significance of controlling nucleation and morphology through coordination engineering for a sustainable energy storage system.

Influence of high-temperature thermal annealing on paramagnetic point defects in silicon-rich silicon nitride films formed in a single-wafer-type low-pressure chemical vapor deposition reactor

The influence of high-temperature thermal annealing on silicon dangling bonds called K centers in Si-rich silicon nitride films grown in a single-wafer-type low-pressure chemical vapor deposition reactor with the SiH2Cl2-NH3 system at 750 °C has been investigated by combining thermal desorption spectroscopy (TDS), Fourier transform infrared spectroscopy-attenuated total reflection, spectroscopic ellipsometry, and electron spin resonance. In the TDS analysis, H2 desorption from the nitride films was detected above about 600 °C. It is found that thermal annealing at 750 and 900 °C caused a slight decrease in the K center density and a change in the g value of K centers, which are considered to be caused by changes in the atomic structure of the nitride films. On the other hand, thermal annealing at 1050 °C resulted in a substantial decrease in the K center density and the generation of paramagnetic defects with unprecedented characteristics. The findings in this study are expected to provide important guidelines for the design of manufacturing processes of nonvolatile memories.

Observer-Based High Order Sliding Mode Control of a Continuous Chemical Reactor

Observer-Based High Order Sliding Mode Control of a Continuous Chemical Reactor

Thermal Performance Assessment of a Novel Hybrid Reactor for Solar Thermochemical Processes

Solar thermochemical conversion processes offer a promising pathway for converting sunlight into clean, sustainable, and carbon-neutral fuels. A solar chemical reactor is one of the most essential components that utilizes concentrated solar energy to drive chemical reactions. In this study, a novel hybrid solar reactor is designed, fabricated, and tested to assess its thermal performance for the purpose of studying the solar thermochemical conversion processes in Thailand for the first time. It was performed under different heating modes regarding solar heat and/or electrical heat, with the aim to support day-and-night operation and variations in solar radiation conditions. The reactor was experimentally tested under on-sun, off-sun, and hybrid conditions using air as a heat transfer fluid. As a result, with one kWth solar thermal power input absorbed, the solar reactor achieved high temperatures exceeding 500 °C from the hybrid system while the reactor absorption efficiency was found to be 4%. The reactor demonstrated the possibility and reliability of performing solar thermochemical conversion processes under day-and-night and unstable solar radiation conditions.

Event-triggered impulsive tracking control for uncertain strict-feedback nonlinear systems via the neural-network-based backstepping technique

This paper studies the problem of event-triggered impulsive tracking control (ETITC) for uncertain strict-feedback nonlinear systems (USFNSs). In contrast to existing impulsive control schemes, this paper incorporates the neural-network (NN)-based backstepping technique into impulsive control design, such that stronger nonlinearities and uncertainties are allowed to be included in the concerned systems. The proposed state-feedback ETITC scheme guarantees that all the signals of the closed-loop system are bounded and the tracking error ultimately converges to an adjustable bounded region, while also avoiding the Zeno behavior. In addition, by constructing a NN-based observer, this paper further develops an output-feedback ETITC scheme to extend its investigation to the scenario where full states are not available for impulsive control design. Finally, an illustrative example involving a chemical reactor system is presented to demonstrate the effectiveness of our control schemes.

Day/Night Power Generator Station: A New Power Generation Approach for Lunar and Martian Space Exploration

In the not-too-distant future, humans will return to the Moon and step foot for the first time on Mars. Eventually, humanity will colonize these celestial bodies, where living and working will be commonplace. Energy is fundamental to all life. The energy that people use to sustain themselves on Earth, and in particular on these other worlds, is the integrated, safe production of electrical power, day and night. This paper proposes a radically new solution to this problem: Solar Tracking by day and a Solar Rechargeable Calcium Oxide Chemical Thermoelectric Reactor by night. Called the “Robotic End Effector for Lunar and Martian Geological Exploration of Space” (REEGES) Day/Night Power Generator Station, this form of thermoelectric power generation is mathematically modeled, simulation is performed, and a concept model design is demonstrated in this paper. The results of the presented simulation show the maximum total system output capability is 9.89 V, 6.66 A, and 65.9 W, with an operating time of up to 12 h, through a scalable design. This research provides instructions to the Space Research Community on a complete and novel development methodology for creating fully customized, configurable, safe, and reliable solar/thermoelectric day/night power generators, specifically meant for use on the Moon and Mars, using the Proportional-Integral-Derivative++ (PID++) Humanoid Motion Control Algorithm for its operation on a computationally lightweight microcontroller.

Irreversible and reversible chemical reaction impacts on convective Maxwell fluid flow over a porous media with activation energy

The Maxwell model of fluid flow in a rotating frame over a porous media is investigated in this paper. Binary chemical reactions and fluid movement under activation energy are both covered in this study. The impact of mass and heat transmission along the boundary layer is investigated in an equilibrium process. Using the method of similarity transformation, the controlling partial differential equations are changed into ordinary differential equations. The results are confirmed using the bvp4c Matlab built-in programme, and the altered equations are resolved utilizing a 4th order Runge Kutta based shooting method. Reversible and irreversible processes, activation energy, chemical reactions, Deborah numbers, and rotation parameters are some of the parameters for which the results are offered in tables and graphs. The prior objective of this study is to examine the impact of activation energy and chemical reactions on Maxwell fluid flow in an equilibrium setting. The concentration boundary layer for reversible flows is significantly finer than that of irreversible flows with the influence of activation energy, chemical reaction, and rotation factors. A reduced boundary layer thickness can improve the rates of heat and mass transmission in tremendous applications, such as exchangers of heat and chemical reactors. In this chemical process, sulphuric acid is utilized as a catalyst along with Maxwell fluid which affects the boundary layer reaction rate and selectivity. This is crucial for efficient catalytic process design. Controlling reaction rates using fluid elasticity and reaction kinetics is useful in operations that need accurate product production.

Exploring pNIPAM lyogels: Experimental study on swelling equilibria in various organic solvents and mixtures, supported by COSMO-RS analysis

Stimuli-responsive lyogels are considered to be smart materials due to their capability of undergoing significant macroscopic changes in response to external triggers. Due to their versatile and unique properties, smart lyogels exhibit great potential in various applications such as drug delivery or actuation processes. While Poly-N-isopropylacrylamide (pNIPAM) is widely known as a thermo-responsive material, it also shows significant solvent-responsive swelling behavior. For the systems tested, polar solvents induce strong swelling due to hydrogen bonding with the amide group, nonpolar solvents lead to significant shrinkage of the lyogels. The aim of this study is to investigate and to model this behavior for future application in chemical or biochemical reactors. As a current area of research, incorporating smart lyogel technology into (bio-)chemical reactors facilitates the development of smart reactor systems. Applying thermodynamic modelling with the gE model COSMO-RS on the monomer or oligomers of pNIPAM, the correlation between solvent-polymer interactions and the degree of swelling can be observed. pNIPAM derivatives exhibit low infinite dilution activity coefficients (IDACs) in polar solvents with large degrees of swelling, while displaying an increase of IDACs in nonpolar solvents. Hydrogen bonds dominate the swelling behavior of lyogels not only in pure solvents but also in mixtures of solvents with varying polarity. Even in mixtures containing high amounts of nonpolar solvents, large degrees of swelling were observed due to the uptake of the polar solvent in the lyogel matrix. This effect can be observed in binary solvent mixtures but also in representative mixtures along an esterification reaction with varying carboxylic chain length of alcohol and carboxylic acids.

Sinusoidal control strategy applied to continuous stirred‐tank reactors: Asymptotic and exponential convergence

AbstractThe main goal of this proposal is to present a class of nonlinear controllers for regulation and set point changes in continuous chemical reactors. The proposed control law has in its mathematical structure a proportional term of the regulation error to provide closed‐loop stability and a sinusoidal term, which can compensate for the nonlinearities of the plant. The closed‐loop stability of the plant is demonstrated via Lyapunov analysis, which reveals an asymptotic convergence of the control output to the required set points. Furthermore, the analysis of the regulation error's dynamic under the considered assumptions leads us to conclude that exponential stability is also reached. The controller is implemented via numerical experiments in two examples to generalize the applicability of the proposed approach by considering continuous stirred‐tank reactors models. The first case considers autocatalytic chemical oscillatory reactions that induce chaotic behaviour. For the second case, a process of acetone, butanol, and ethanol (ABE) fermentation through Clostridium acetobutylicum is considered. The proposed strategy shows an adequate performance because it can reach the required set point without long time settings and overshoot. A comparison with a smooth sliding‐mode and a standard proportional‐integral (PI) controller indicates the advantages of the proposed control approach.

Quantized control for interconnected PDE systems via mobile measurement and control strategies

This paper deals with the Rϵ-stabilization for interconnected partial differential equation systems (IPDESs) by mobile measurement and control strategies. First, compared to the static measurement and control strategies, the mobile ones are employed to improve the dynamic response of the closed-loop system, while reducing the number of sensors and actuators effectively. Moreover, considering the constrained transmission channel bandwidth, the hysteresis quantizer with an adjustable parameter is introduced to save the communication resources in the network, while can balance the quantization effect and the control performance by adjusting the parameter. Further, the output quantization controller is designed to ensure that the closed-loop system is Rϵ-stable, which converges to a given interval in finite time. Finally, a simulation example of chemical non-isothermal tubular reactors is provided to illustrate the validity of the presented design method.