Reactor System Research Articles

Simultaneous dehalogenation and oxidation of dichloroacetamide by Cu-modified CoFe-LDH in three-dimensional continuous flow aerated electrocatalytic reactor

Searching for catalysts and degradation systems for synchronous dehalogenation and oxidation of haloacetamides (HAcAms) is pressing. In this study, a novel three-dimensional continuous flow aerated electrocatalytic reactor (3D CFAER) system, which employed Cu-modified CoFe layered double hydroxides (CoFe-LDH) composite/activated carbon as a catalytic particle electrode for the degradation of dichloroacetamide (DCAcAm) was constructed. Under the experiment’s optimal operating parameters, the maximum degradation rate of DCAcAm reached 91.7 %. The superior performance for the degradation of DCAcAm was due to the enhanced electron transfer induced by the modification of Cu in CoFe-LDH. Moreover, Density Functional Theory (DFT) calculations indicated that Cu doping improved the ability of LDH to dissociate water, thereby enhancing its electrocatalytic performance. Scavenger experiments and Electron Paramagnetic Resonance (EPR) results revealed that •OH, O2•– and electrochemical direct dehalogenation were responsible for DCAcAm removal. Additionally, the electrocatalytic stability of the electrode was tested upon repeated use with DCAcAm degradation remaining as high as 81.7 % after five consecutive experiments. More importantly, in 3D CFAER, electrocatalytic treatment lasting 90 min reduced the TOC and COD of the actual chlorine disinfection wastewater by 64.1 % and 74.9 %, respectively. This study provides new theoretical basis and technical support for control of HAcAms.

Effective multi-biocatalyst system with reusable NADH for transformation of glycerol to value-added dihydroxyacetone

Glycerol-based biorefinery can be a highly profitable process by producing highly value-added products such as dihydroxyacetone via combined catalytic strategies. Here, two-enzyme system is adopted for the transformation of glycerol into highly valuable dihydroxyacetone as well as cofactor regeneration at the same time. Glycerol dehydrogenase (GDH) and alcohol dehydrogenase (ADH) are co-immobilized within magnetically separable and spherical mesocellular silica foam (Mag-S-MCF), to prepare NER-(GDH/ADH). In details, GDH and ADH are adsorbed into the mesopores of Mag-S-MCF, and further crosslinked within the mesopores of Mag-S-MCF. The resulting nanoscale enzyme reactors (NER) of crosslinked GDH and ADH molecules within the bottle-neck structured mesopores can effectively prevent larger sized crosslinked enzyme aggregates from being leached out of smaller mesopores, due to the bottle-neck mesopore structure of Mag-S-MCF, as well as stabilize the activity of GDH and ADH upon chemical crosslinking, effectively preventing the denaturation of enzyme molecules. More importantly, the proximity of GDH and ADH molecules within mesopores of NER improves the efficiency of cofactor-mediated dual-enzymatic reactions by relieving mass-transfer limitations and improving cofactor recycling in an effective way, expediting both glycerol oxidation and dihydroxyacetone generation at the same time. As a result, the DHA concentration of NER-(GDH/ADH) and the simple mixture of NER-GDH and NER-ADH were 410 μM and 336 μM, respectively. To the best of our knowledge, this report is the first demonstration of stabilized nanoscale multi-enzyme reactor system, equipped with efficient cofactor regeneration within confined mesopores, for efficient glycerol transformation to high-valued dihydroxyacetone.Graphical

Analysis of Dynamic Characteristics of Reconfigurable Modular Reactor Systems for Renewable Methanol Synthesis

Analysis of Dynamic Characteristics of Reconfigurable Modular Reactor Systems for Renewable Methanol Synthesis

Optimizing H2 production from biomass: A machine learning-enhanced model of supercritical water gasification dynamics

Supercritical water gasification (SCWG) is recognized as an efficient technology for biomass conversion, demonstrating substantial potential in the sustainable energy sector. This paper focuses on the H2 production by SCWG of biomass. The objective is to develop an accurate gasification kinetic model that can facilitate the optimization of industrial reactor designs. A series of SCWG experiments is conducted in a batch reactor system under temperature of 500–600 °C and residence time of 1–20 min. Based on the experimental results, a hybrid-driven model for SCWG reaction is established. Firstly, experimental data is utilized to delineate SCWG reaction mechanistic model and forecast gas yields with an acceptable error margin. Subsequently, a Wasserstein Generative Adversarial Network Gradient Boosting Regression Grid Search (WGAN-GBR-GRID) model is applied to acquire knowledge of the predictive errors from the mechanistic model and to develop a hybrid model. The hybrid-driven model significantly enhances the average relative prediction error from 15.56 % to 0.02 % when compared to the mechanistic model. This result underscores the potential of the hybrid model in optimizing SCWG technology and the Shapley Additive exPlanations (SHAP) values in feature analysis shows the possible shortcomings of mechanistic model, thereby providing a new perspective for SCWG reaction dynamics modeling.

Predictive modeling of membrane reactor efficiency using advanced artificial neural networks for green hydrogen production

The imperative to decarbonize the energy sector has prompted substantial advancements in clean electricity generation, with hydrogen emerging as a promising low-carbon energy carrier. While hydrogen synthesis from renewable sources is crucial, challenges persist, necessitating innovative approaches for efficient and sustainable production. This study leverages diverse artificial neural network (ANN) models to assess and predict system efficiency based on key operational variables in membrane reactor systems. The multilayered perceptron (MLP) and radial basis function (RBF) methodologies are employed, with the MLP models optimized across twelve training algorithms and eight activation functions, exploring up to three hidden layers with variable neuron counts. The MLP model, utilizing the Levenberg-Marquard training algorithm and Tangent-Sigmoid activation function, achieved a high correlation coefficient (R2) of 0.9975 for training and 0.9962 for testing, and a mean squared error (MSE) of 0.00425 for training and 0.23951 for testing, indicating precise and accurate efficiency predictions. The Log-Sigmoid activation function also performed well, with R² values of 0.9971 (training) and 0.9961 (testing), and MSE values of 0.004086 (training) and 0.17694 (testing). Optimization of the RBF network identified the best performance with a spread parameter of 1 and 35 neurons, although the MLP model demonstrated superior accuracy and reduced computational time. Statistical analysis, encompassing correlation coefficient, mean squared error, Root Mean Squared error, absolute average deviation, absolute average relative deviation, and runtime, confirms the network’s consistent and accurate estimation of system efficiency across various input variables. The study highlights that applying tansig and logsig activation functions, configured with neuron counts of 20, 17, 6 and 23, 20, 2 at the first, second and third hidden layers, respectively, offers enhanced accuracy and reliability. The MLP model’s high performance underscores its potential to identify optimal conditions for H2 generation based on system efficiency, thereby advancing membrane reactor technology for hydrogen production.

Thermosiphon Cooling System for a Methanation Reactor: An Experimental Assessment

Abstract Operating the cooling system of a methanation reactor using an open-loop two-phase thermosiphon with evaporating water as the cooling liquid is an effective way to ensure safe operation as it does not rely on a recirculating pump. The aim of the reactor design is to co-generate methane and steam, the latter to be used in a solid-oxide electrolyzer to produce H2 to be injected in the reactor. The passive operation was analyzed to ensure a similar level of stability in the steam production compared to the active operation (i.e., with a pump). A total of 98% of the measured steam produced in passive cooling were within ±9.82% of the individual means, comparing well to ±9.5% for the active cooling operation.

Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations

In this work, we introduce a novel method to develop whole system digital twins (DTs) for advanced nuclear reactors. This method treats a complex reactor system as a heterogeneous graph: with the system components as different types of graph nodes and their physical interconnections as edges. Based on the heterogeneous graph, a graph neural network combining graph convolution and temporal node attention is developed as the DT, facilitating a comprehensive understanding of the system’s dynamic behavior. By utilizing the System Analysis Module (SAM) code for simulating various operational transients, we develop a graph-based database that trains the DT. This DT is characterized by two primary functions: It can infer the entire system’s status using sparse node information, and it can predict the progress of transients based on current and historical system information. Our approach is validated through case studies on the Experimental Breeder Reactor II (EBR-II) system and a generic Fluoride-salt-cooled High-temperature Reactor (gFHR), demonstrating the DT’s accuracy in forecasting operational transients. The DT’s rapid computation capabilities enhance its potential for supporting advanced reactor operations, offering benefits in intelligent simulation, autonomous control, and anomaly detection, paving the way for improved safety analysis and intelligent component health management for advanced reactor systems and reducing their operations and maintenance cost.

Design a robust intelligent power controller for pressurized water reactor using particle swarm optimization algorithm

Abstract Proportional–Integral–Derivative (PID) controllers have been optimized and used to overcome many types of problems in nuclear reactor systems. The high performance of PID controllers depend on optimizing their gains. In this research, an optimized robust PID controller is proposed to control power perturbations in a pressurized water reactor (PWR). The optimization process of robust PID using particle swarm optimization (PSO) algorithm aims to adapt PID gains then after that, H-infinity controller is used. The results show a good performance when that suggested hybrid controller is applied to the nuclear power system since the suggested design makes the system robust due to applying H-infinity method, in addition to get the benefits of the optimized PID controller.

Removal of sulfamethoxazole in an algal-bacterial membrane aerated biofilm reactor: Microbial responses and antibiotic resistance genes

Antibiotics are frequently detected in wastewater, but often are poorly removed in conventional wastewater treatment processes. Combining microalgal and nitrifying bacterial processes may provide synergistic removal of antibiotics and ammonium. In this research, we studied the removal of the antibiotic sulfamethoxazole (SMX) in two different reactors: a conventional nitrifying bacterial membrane aerated biofilm reactor (bMABR) and algal-bacterial membrane aerated biofilm reactor (abMABR) systems. We investigated the synergistic removal of antibiotics and ammonium, antioxidant activity, microbial communities, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and their potential hosts. Our findings show that the abMABR maintained a high sulfamethoxazole (SMX) removal efficiency, with a minimum of 44.6 % and a maximum of 75.8 %, despite SMX inhibition, it maintained a consistent 25.0 % ammonium removal efficiency compared to the bMABR. Through a production of extracellular polymeric substances (EPS) with increased proteins/polysaccharides (PN/PS), the abMABR possibly allowed the microalgae-bacteria consortium to protect the bacteria from SMX inactivation. The activity of antioxidant enzymes caused by SMX was reduced by 62.1–98.5 % in the abMABR compared to the bMABR. Metagenomic analysis revealed that the relative abundance of Methylophilus, Pseudoxanthomonas, and Acidovorax in the abMABR exhibited a significant positive correlation with SMX exposure and reduced nitrate concentrations and SMX removal. Sulfonamide ARGs (sul1 and sul2) appeared to be primarily responsible for defense against SMX stress, and Hyphomicrobium and Nitrosomonas were the key carriers of ARGs. This study demonstrated that the abMABR system has great potential for removing SMX and reducing the environmental risks of ARGs.

Generating a system of group constants for neutron-physical calculations of fast reactors based on ROSFOND-2020.2 library files

The subject of constant support development is currently becoming increasingly important in connection with the national strategy of transition to a closed nuclear fuel cycle. At the same time, the importance of the tasks of refining calculation models and minimizing methodological, statistical, and constant errors is increasing. In this connection, the idea of creating a universal system of constants describing with equal accuracy both uranium loading and loading with mixed oxide uranium-plutonium fuel and the possibility to perform on its basis both precision Monte Carlo calculations (data format – ACE) and multigroup calculations (formats – ABBN and ANISN) was laid in the basis of this work. In this paper we analyze the freely available libraries of evaluated nuclear data in order to justify the choice of source files for the formation of a new system of group constants for neutron-physical calculations of fast reactor cores, describe the process of formation of a new library of reactor constants, and verify the obtained system on computational test models of BN-800 reactor and critical systems. The process of formation of the new system of group constants included selection of initial neutron data files, updating of data tables of basic neutron cross-sections, self-shielding factors and Doppler coefficients, as well as data on fission spectra for the main fuel nuclides. The methodological component of the error for test models of the BN-800 core was evaluated. Using the ABBN-RF22 system of group constants it was possible to estimate the correction in the 299 groups calculation, which amounted to 0.3%. Previously, when using the ABBN-93 library, there was no such possibility due to the lack of continuity between the files of evaluated neutron data and the group constants used.

Aspects of Reaction Engineering for Biodiesel Production

Biodiesel is a non-toxic, drop-in liquid transportation fuel that is amenable to continuous production from sustainable biomass resources using catalytic technologies. A diverse range of catalysts and reactor technologies have been experimentally investigated and computationally modelled, for producing biodiesel (fatty acid methyl esters) from oil feedstocks by their esterification or transesterification with short-chain alcohols. Solid-acid and base catalysts are attractive for biodiesel production from renewable oil feedstocks due to their ease of separation from the desired biodiesel and glycerol by-product, use of Earth’s abundant elements, and suitability in continuous processes. Here, we review the technical challenges and opportunities in designing catalytic reactor systems for biodiesel production.

Scaling design and similarity analysis of a floating nuclear power plant

In the process of developing floating reactor systems, their operation in the marine environment needs to be simulated to ensure the reliability of the safe design of nuclear reactors. Scaling test is a potential option for computer model validation by virtue of its low cost and flexibility. This study first gives the similarity law for dynamic tests of the reactor system in high-temperature environments by dimensional analysis. Then we focus on analyzing the jamming phenomenon that may occur during the similarity design process and provides a solution for realizing the contact state of the prototype in the scaled model. This study also analyzes the dynamic response of a floating reactor system under extreme operating conditions by combining numerical simulations and scaling tests. By comparing the response results predicted by the scaled model with the prototype response, it is further demonstrated that the feasibility of scaling test as an alternative to full-size test to provide a reference for realizing low-cost, accurate and safe design for reactor system.

A subchannel analysis code for advanced liquid metal fast reactor cores and study on heat transfer characteristics of core geometry parameters

The liquid metal fast reactor represents an important reactor type for the future development of nuclear energy. Accurately modeling and predicting the subchannel flow and heat transfer phenomenon in the rod bundles plays a key role in ensuring core safety. Consequently, a subchannel code suitable for the liquid metal fast reactor is analyzed based on the subchannel analysis code of the Pressurized Water Reactor (PWR). The modified code incorporates various types of liquid metals, such as lead, lead-bismuth eutectic (LBE), and sodium, along with their constitutive models, enhancing the applicability of the liquid metal reactor systems. This code has been verified and validated at several levels, including comparing the code simulation results with other similar subchannel codes results, high-dimensional Computational Fluid Dynamics (CFD) simulations, and experiment data. The sensitivity analysis of core geometric parameters and turbulent mixing coefficients is performed based on the modified version code. The influence of the core geometry, including the rod Pitch to Diameter ratio (P/D), Rod to Wall gap (RTW) and the wire wrap pitch (H) on the sensitivity of outlet temperature has been investigated. The results show that the new subchannel analysis code suitable for liquid metal cooled reactor shows reasonable agreement with the verified and validated results. The geometric parameters, such as P/D, RTW and H have noticeable effects on the outlet temperature difference of the subchannels. Additionally, the outlet temperature distribution in the subchannel is significantly affected by different turbulent mixing coefficients and the distribution of the turbulent mixing coefficient also influenced by the reactor core sizes. Overall, this study could support the rod bundles design and safety analysis in the liquid metal reactors.

Metagenomic analysis reveals abundance of mixotrophic, heterotrophic, and homoacetogenic bacteria in a hydrogen-based membrane biofilm reactor

Heterotrophic microorganisms are frequently observed in hydrogenotrophic denitrification systems and are presumed to contribute to their improved performance. However, their roles and metabolic pathways in the hydrogen-based membrane biofilm reactor (H2−MBfR) system remain unclear. The objective of this study was to elucidate the underlying mechanisms driving heterotrophic denitrification. For this purpose, metagenomic analysis was conducted on an H2−MBfR showing higher denitrification performance, focusing on the metabolic function of the microbial community. Functional genes related to H2 oxidation, organic carbon metabolism, and denitrification were the major targets of interest. This analysis revealed a substantial number of genes associated with the oxidation of organic carbon compounds in the biofilm, suggesting its potential for heterotrophic denitrification. Investigation of the genes of interest in metagenome-assembled genomes (MAGs) has demonstrated a predominance of mixotrophs or heterotrophs rather than obligate autotrophs. Notably, MAGs exhibiting the highest abundance of genes of interest were affiliated with Hydrogenophaga and Thauera, implying their significant role in denitrifying the H2−MBfR as mixotrophs utilizing both H2 and organic substrates. The identification of 11 MAGs, presumed to originate from homoacetogens suggested that acetate might contribute to the proliferation of heterotrophs. Based on these metagenomic findings, possible metabolic pathways were identified to explain heterotrophic denitrification within the H2−MBfR biofilms.

Modelling of a continuous sorption-enhanced methanation process in an adiabatic packed-bed reactor system

The present study investigates a sorption-enhanced methanation process and successive solid regeneration stages using a dual-function catalyst containing nickel as a catalyst and zeolite 13X for water removal. An adiabatic packed bed, modelled by a dynamical and heterogeneous model, has been considered, and a five-stage sequence describes the sorption-enhanced methanation and successive solid regeneration. First, methanation occurs with in-situ water removal; then, the catalyst drying using a pressure and temperature swing approach implemented by blowdown, purge, cooling, and pressurisation stages. In adiabatic operation, heat management is crucial; on the other hand, the heat produced can be efficiently used to dry the zeolite. Process intensification is pursued by addressing the effect of gas inlet temperature, pressure, and GHSV on system performance. Achieving an average purity of 99 % of the methane for pressures greater than 2 bar is possible for long-time operation, with productivity averaging 0.8 mol/(kgads min) at the highest gas hourly space velocity investigated.

Influence of space conjugate temperature varying non-uniform heat sink/source on hydromagnetic slip water-EG (50:50) nanofluid

Significant cooling is an essential requirement in the field of aeronautical and bio-medical engineering, nuclear reactor system, solar collectors, and in development of electronic chips etc. Involving rotating conical geometries. In view of this, flow and heat transfer over conical geometries subject to different constraints of motion are highly needed. Implementation of magnetic field subject to flow pattern controls the fluid motion thereby imparting better cooling. Consideration of nanofluid instead of regular fluid yields prominent cooling of the associated surface. Such relevance has motivated the authors to work on magnetohydrodynamics and heat transfer investigation of water-EG (50:50) mixture based Al2O3 and Fe3O4 past heated and rotating down-pointing upright cone subject to impact of space and temperature varying non-uniform heat source or sink. Numerical solution of dimensionless governing equations is accomplished by implementing Runge-Kutta method. The findings indicate that swirl and axial velocities peter out with rise in magnetic parameter while both exhibit opposite impact in response to slip parameter. Temperature profiles upgrade due to amplification of space and temperature dependent parameters. Skin friction and heat transportation upsurge with growth of solid volume fraction of nanoparticle.

Exploring the regulation mechanism of signaling molecules on algal-bacterial granular sludge through different N-acyl-homoserine lactones

As a recently emerging wastewater treatment technology, Algal-bacterial granular sludge (ABGS) process shows significant advantages. However, current research on the ABGS system is a lack of a clear and complete understanding of the potential mechanism of signal molecules on the growth of ABGS. This study comprehensively explores the variations in the ABGS under different N-acyl-homoserine lactone (AHL)conditions by constructing three sequencing batch reactor (SBR) systems. The results indicate that N-hexanoyl-L-homoserine lactone (C6-HSL) accelerates the granulation process in the early stages by promoting the loosely bound extracellular polymeric substances (LB-EPS) secretion and filamentous bacteria growth, thereby shortening required time for initial granule formation. On the other hand, N-(3-oxodecanoyl)-L-homoserine lactone (3-oxo-C12-HSL) expedites the granulation process by promoting the tightly bound extracellular polymeric substances (TB-EPS) and aromatic protein secretion, benefiting structural stability and nitrogen and phosphorus removal efficiency of mature ABGS.

The MOOSE fluid properties module

The Fluid Properties module within the Multiphysics Object-Oriented Simulation Environment (MOOSE) is used to compute fluid properties for numerous applications, ranging from nuclear reactor thermal hydraulics to geothermal energy. Those applications drove the development of the module to enable numerous different fluid equations of states, property lookups with primitive and conserved flow variable to cater to pressure and density-driven solvers, and an object-oriented design facilitating expansion and maintenance. Each fluid property is implemented in its own class but inherits capabilities such as automatic differentiation, automated out-of-bounds handling or variable conversion capabilities. This paper presents the module, its design, its user and developer interface, its content in terms of fluids and properties, and several of its applications showing its major role in the MOOSE simulation ecosystem. Program summaryProgram title: MOOSE Fluid Properties moduleCPC Library link to program files:https://doi.org/10.17632/cwzhsyp6pd.1Developer's repository link:https://github.com/idaholab/moose/tree/next/modules/fluid_propertiesLicensing provisions: LGPLProgramming language: C++, PythonNature of problem: The simulation of thermal hydraulics of advanced nuclear reactor systems, such as heat pipe micro-reactors or molten-salt cooled pebble bed reactors, requires a wide variety of discretizations of the fluid flow equations, from 1D thermal hydraulics to computational fluid dynamics at various levels of fidelity, with a wide variety of coolants. Applications are developed within the MOOSE C++ framework by Argonne and Idaho National Laboratories to simulate these reactors for research and design purposes. These applications (Sockeye, SAM, others) rely on MOOSE for the computation of fluid properties. The fluid properties module contains properties for most advanced nuclear reactor coolants, including an interface to the Molten Salt Thermodynamics Database (MSTDB) developed by Oak Ridge National Laboratory. Single phase, two phase, and gas mixtures fluid properties are computed by the module.Solution method: The fluid properties module includes numerous numerical methods to support the wide range of applications, notably forward automatic differentiation, conversion methods between pressure and density-driven variable sets, spline-based table lookups which are the current state of the art for the fast computation of fluid properties. The integration with MOOSE facilitates uncertainty quantification with regards to the fluid properties and optimization studies with regards to the fluid composition.

Silica solubility and molecular speciation in water vapor at 400–800 °C

Silica solubility and molecular speciation in hydrothermal water vapor have been determined through quartz solubility experiments at 400–800 °C and 50–270 bar using a novel U-tube flow-through reactor system and theoretical calculations. The results demonstrate that silica concentrations are low in water vapor (mSi,tot = 0.11–4.56 mmol/kg or xSi,tot = 8.21 × 10−5–1.98 × 10−6 mol/mol) increase with both temperature and pressure, which is attributed to the dissolution of quartz according to the reaction:SiO2(s) + (n + 2)H2O(g) ⇋ Si(OH)4·(H2O)n(g)Thermodynamic modeling and theoretical calculations employing density functional theory (B3LYP-D3), and MP2 ab initio calculations reveal the stable structures to be Si(OH)4(g), Si(OH)4·(H2O)2(g), Si(OH)4·(H2O)4(g) and Si(OH)4·(H2O)7(g) (n = 0, 2, 4, 7) under the temperature and pressure conditions of interest, with higher-order hydrated structures also present at the lowest temperatures and highest pressures. Various isomers of the gaseous silica species were identified, with the number of energetically favorable structures increasing with hydration level and the motifs shifting from silanol-water bonds to complex water-water networks. Over the temperature range of interest, the logarithm of the quartz equilibrium solubility constant (logKn) rises from −7.40 to −6.55 and −12.23 to −11.65 at 400 to 800 °C for the formation of Si(OH)4(g) and Si(OH)4·(H2O)2(g), respectively, and decreases from −16.20 to −19.15 and –22.61 to −28.74 for Si(OH)4·(H2O)4(g) and Si(OH)4·(H2O)7(g) at the same temperature range, respectively. Standard thermodynamic properties were derived based on the experimental results, revealing temperature-independent enthalpy (ΔHn,ro), entropy (ΔSn,ro) and heat capacity (ΔCp,n,ro) of reaction for each gaseous silica species. The enthalpy of the reaction is nearly constant, whereas the entropy and heat capacity decrease with increasing hydration, resulting in higher-level hydrated species becoming less important with increasing temperature. Our quartz solubility results are in good agreement with previous experimental data and thermodynamic equations, as well as the thermodynamic properties of Si(OH)4(g) at 25 °C and 1 bar.

Synergistic photocatalytic degradation of methylene blue using TiO2 composites with activated carbon and reduced graphene oxide: a kinetic and mechanistic study

This comprehensive study explored the removal of methylene blue (MB) from aqueous solutions as a model pollutant, utilizing solar-driven photocatalysis with nano-sized titanium dioxide (TiO2) and composites with activated carbon (AC) and reduced graphene oxide (RGO). This research introduces continuous solar reactor instead of conventional batch experiments investigating its design configuration. Utilizing response surface methodology (RSM), the study determined the optimal process conditions (MB concentration at 30 mg/L, pH 8.82, irradiation time 138 min), under which TiO2 achieved a 93.13% MB removal efficiency. The study further revealed that the integration of TiO2 with AC and RGO (5% wt.) significantly enhanced the MB photocatalytic degradation. The TiO2/AC composite achieved 98.3% MB degradation in 138 min of solar exposure, related to its large specific surface area of 146 m2/g and a pore volume of 0.439 cm3/g. Likewise, the TiO2/RGO composite demonstrated 97% removal with a surface area of 102 m2/g and a pore volume of 0.476 cm3/g, significantly better than nano-TiO2. Additionally, the research investigated the role of the solar reactor configuration on MB removal. Using 26 mm Pyrex tube diameter with 15 cm long on parabolic aluminum concentrator inclined at 30° optimally achieved the peak MB degradation efficiency. Recyclability tests shown a noticeable decrease in nano-TiO2 efficiency to 56.03% without regeneration; however, after regeneration following the third cycle, the efficiency significantly recovered to 70.07%. Thereby, this paper introduces an innovative, continuous, and well-designed solar reactor system for dye removal, employing nano-TiO2 and its composites with AC and RGO for improved photocatalytic efficiency under statistically optimized process conditions.