Integrating artificial neural networks and response surface methodology for predictive modeling and mechanistic insights into the detoxification of hazardous MB and CV dyes using Saccharum officinarum L. biomass

The presence of dye pollutants in industrial wastewater poses significant environmental and health risks, necessitating effective treatment methods. The optimal adsorption treatment of methylene blue (MB) and crystal violet (CV) dye-simulated wastewater utilising Saccharum officinarum L presents a key challenge in the selection of appropriate modelling approaches. While RSM and ANN models are frequently used, there is a noticeable knowledge gap when it comes to evaluating their relative strengths and weaknesses in this context. The study compared the predictive abilities of response surface methodology (RSM) and artificial neural network (ANN) for the adsorption treatment of MB and CV dye-simulated wastewater using Saccharum officinarum L. The process experimental variables were modelled and predicted using a three-layer artificial neural network trained using the Levenberg-Marquard backpropagation algorithm and 30 central composite designs (CCD). The adsorption study used a specific mechanism, which led to noteworthy maximum removals of 98.3% and 98.2% for dyes (MB and CV), respectively. The RSM model achieved an impressive R2 of 0.9417, while the ANN model achieved 0.9236 in MB. Adsorption is commonly used to remove colour from many different materials. Saccharum officinarum L., a byproduct of sugarcane processing, has shown potential as an efficient and ecological adsorbent in this environment. The purpose of this study is to evaluate sugarcane bagasse's potential as an adsorbent for the removal of dyes MB and CV from industrial wastewater, providing a long-term strategy for reducing dye pollution. Due to its beneficial economic and environmental characteristics, the Saccharum officinarum L. adsorbent has prompted research into sustainable resources with low pollutant indices.

Synthesis of ion-imprinted polymer-decorated SBA-15 as a selective and efficient system for the removal and extraction of Cu(ii) with focus on optimization by response surface methodology

Ion-imprinted polymer-decorated SBA-15 (SBA-15-IIP) for the adsorption of copper was synthesized and characterized using different techniques, including FT-IR, XRD, TG/DTA, SEM, BET, and TEM.

Study of decolorisation of binary dye mixture by response surface methodology

Decolorisation of a complex mixture of two different classes of textile dyes Direct Red 81 (DR81) and Rhodamine B (RHB), simulating one of the most important condition in real textile effluent was investigated onto deoiled Argemone Mexicana seeds (A. Mexicana). The adsorption behaviour of DR81 and RHB dyes was simultaneously analyzed in the mixture using derivative spectrophotometric method. Central composite design (CCD) was employed for designing the experiments for this complex binary mixture where significance of important parameters and possible interactions were analyzed by response surface methodology (RSM). Maximum adsorption of DR81 and RHB by A. Mexicana was obtained at 53 °C after 63.33 min with 0.1 g of adsorbent and 8 × 10^-6 M DR81, 12 × 10^-6 M RHB with composite desirability of 0.99. The predicted values for percentage removal of dyes from the mixture were in good agreement with the experimental values with R² > 96% for both the dyes. CCD superimposed RSM confirmed that presence of different dyes in a solution created a competition for the adsorbent sites and hence interaction of dyes was one of the most important factor to be studied to simulate the real effluent. The adsorbent showed remarkable adsorption capacities for both the dyes in the mixture.

Screening and optimization of highly effective ultrasound-assisted simultaneous adsorption of cationic dyes onto Mn-doped Fe3O4-nanoparticle-loaded activated carbon

The ultrasound-assisted simultaneous adsorption of brilliant green (BG) and malachite green (MG) onto Mn-doped Fe₃O₄ nanoparticle-loaded activated carbon (Mn-Fe₃O₄-NP-AC) as a novel adsorbent was investigated and analyzed using first derivative spectrophotometry. The adsorbent was characterized using FT-IR, FE-SEM, EDX and XRD. Plackett-Burman design was applied to reduce the total number of experiments and to optimize the ultrasound-assisted simultaneous adsorption procedure, where pH, adsorbent mass and sonication time (among six tested variables) were identified as the most significant factors. The effects of significant variables were further evaluated by a central composite design under response surface methodology. The significance of independent variables and their interactions was investigated by means of the analysis of variance (ANOVA) within 95% confidence level together with Pareto chart. Using this statistical tool, the optimized ultrasound-assisted simultaneous removal of basic dyes was obtained at 7.0, 0.02g, 3min for pH, adsorbent mass, and ultrasonication time, respectively. The maximum values of BG and MG uptake under these experimental conditions were found to be 99.50 and 99.00%, respectively. The adsorption process was found to be followed by the Langmuir isotherm and pseudo-second order model using equilibrium and kinetic studies, respectively. According to Langmuir isotherm model, the maximum adsorption capacities of the adsorbent were obtained to be 101.215 and 87.566mgg^-1 for MG and BG, respectively. The value of apparent energy of adsorption obtained from non-linear Dubinin-Radushkevich model (4.348 and 4.337kJmol^-1 for MG and BG, respectively) suggested the physical adsorption of the dyes. The studies on the well regenerability of the adsorbent in addition to its high adsorption capacity make it promising for such adsorption applications.

Application of ZnO nanorods loaded on activated carbon for ultrasonic assisted dyes removal: Experimental design and derivative spectrophotometry method

A method based on application of ZnO nanorods loaded on activated carbon (ZnO-NRs-AC) for adsorption of Bromocresol Green (BCG) and Eosin Y (EY) accelerated by ultrasound was described. The present material was synthesized under ultrasound assisted wet-chemical method and subsequently was characterized by FE-SEM, TEM, BET and XRD analysis. The extent of contribution of conventional variables like pH (2.0-10.0), BCG concentration (4-20mgL(-1)), EY concentration (3-23mgL(-1)), adsorbent dosage (0.01-0.03g), sonication time (1-5min) and centrifuge time (2-6min) as main and interaction part were investigated by central composite design under response surface methodology. Analysis of variance (ANOVA) was adapted to experimental data and guide the best operational conditions mass by set at 6.0, 9mgL(-1), 10mgL(-1), 0.02g, 4 and 4min for pH, BCG concentration, EY concentration, adsorbent dosage, sonication and centrifuge time, respectively. At these specified conditions dye adsorption efficiency was higher than 99.5%. The suitability and well prediction of optimum point was tested by conducting five experiments and respective results revel that RSD% was lower than 3% and high quality of fitting was confirmed by t-test. The experimental data were best fitted in Langmuir isotherm equation and the removal followed pseudo second order kinetics. The experimentally obtained maximum adsorption capacities were estimated as 57.80 and 61.73mgg(-1) of ZnO-NRs-AC for BCG and EY respectively from binary dye solutions. The mechanism of removal was explained by boundary layer diffusion via intraparticle diffusion.

Statistical experimental design, least squares-support vector machine (LS-SVM) and artificial neural network (ANN) methods for modeling the facilitated adsorption of methylene blue dye

This study is based on the usage of a composite of zinc sulfide nanoparticles with activated carbon (ZnS-NPs-AC) for the adsorption of methylene blue (MB) from aqueous solutions.

Simultaneous extraction and preconcentration of some metal ions using eucalyptus-wood based activated carbon modified with silver hydroxide nanoparticles and a chelating agent: optimization by an experimental design

In the present work, the solid phase extraction (SPE) of Cr(iii), Cu(ii), Pb(ii), Ni(ii), Cd(ii), and Co(ii) metal ions was carried out using a new adsorbent, activated carbon modified with silver hydroxide nanoparticles and a chelating agent.

Ternary dye adsorption onto MnO2 nanoparticle-loaded activated carbon: derivative spectrophotometry and modeling

MnO₂ nanoparticle-loaded activated carbon (MnO₂-NP-AC) as an efficient, environmental friendly and cost-effective adsorbent was synthesized and characterized using different techniques such as FE-SEM, EDX, XRD, BET and FTIR.

Enhanced simultaneous removal of malachite green and safranin O by ZnO nanorod-loaded activated carbon: modeling, optimization and adsorption isotherms

Highly improved, safe, green and rapid adsorption by loading trace amounts of ZnO nanorods on AC with high uptake capacity.

Random forest model for the ultrasonic-assisted removal of chrysoidine G by copper sulfide nanoparticles loaded on activated carbon; response surface methodology approach

Copper sulfide nanoparticle-loaded activated carbon (CuS-NP-AC) was prepared and used as an adsorbent for the accelerated removal of chrysoidine G (CG) assisted by ultrasound.

Preparation and characterization of MWCNTs functionalized by N-(3-nitrobenzylidene)-N′-trimethoxysilylpropyl-ethane-1,2-diamine for the removal of aluminum(iii) ions via complexation with eriochrome cyanine R: spectrophotometric detection and optimization

A novel adsorbent was fabricated by covalently anchoring N-(3-nitro-benzylidene)-N′-trimethoxysilylpropyl-ethane-1,2-diamine onto multiwalled carbon nanotubes (NBATSPED-MWCNTs).

Simultaneous removal of methylene blue and Pb2+ ions using ruthenium nanoparticle-loaded activated carbon: response surface methodology

Ruthenium nanoparticles were synthesized in a green approach with high yield in the presence of ultrasound and then the product was loaded on activated carbon.