The present study investigated the kinetics, equilibrium and thermodynamics of chromium (Cr) ion biosorption from Cr(VI) aqueous solutions by Cupressus lusitanica bark (CLB). CLB total Cr biosorption capacity strongly depended on operating variables such as initial Cr(VI) concentration and contact time: as these variables rose, total Cr biosorption capacity increased significantly. Total Cr biosorption rate also increased with rising solution temperature. The pseudo-second-order model described the total Cr biosorption kinetic data best. Langmuir´s model fitted the experimental equilibrium biosorption data of total Cr best and predicted a maximum total Cr biosorption capacity of 305.4 mg g^-1. Total Cr biosorption by CLB is an endothermic and non-spontaneous process as indicated by the thermodynamic parameters. Results from the present kinetic, equilibrium and thermodynamic studies suggest that CLB biosorbs Cr ions from Cr(VI) aqueous solutions predominantly by a chemical sorption phenomenon. Low cost, availability, renewable nature, and effective total Cr biosorption make CLB a highly attractive and efficient method to remediate Cr(VI)-contaminated water and wastewater.

The adsorption performance of a Cu-TiO₂composite for removing acid blue 80 (AB80) dye from aqueous solutions was investigated in terms of kinetics, equilibrium, and thermodynamics. The effect of operating variables, such as solution pH, initial dye concentration, contact time, and temperature, on AB80 adsorption was studied in batch experiments. AB80 adsorption increased with increasing contact time, initial dye concentration, and temperature and with decreasing solution pH. Modeling of adsorption kinetics showed good agreement of experimental data with the pseudo-second-order kinetics model. The experimental equilibrium data for AB80 adsorption were evaluated for compliance with different two-parameter, three-parameter, and four-parameter isotherm models. The Langmuir isotherm model best described the AB80 adsorption equilibrium data. The thermodynamic data revealed that the AB80 adsorption process was endothermic and nonspontaneous. Kinetics, equilibrium, and thermodynamic results indicate that Cu-TiO₂adsorbs AB80 by a chemical sorption reaction.

Hexavalent chromium [Cr(VI)] is a high-priority environmental pollutant because of its toxicity and potential to contaminate water sources. Biosorption, using low-cost biomaterials, is an emerging technology for removing pollutants from water. In this study, Long Short-Term Memory (LSTM) and bidirectional LSTM (Bi-LSTM) neural networks were used to model and predict the kinetics of the removal capacity of Cr(VI) and total chromium [Cr(T)] using Cupressus lusitanica bark (CLB) particles. The models were developed using 34 experimental kinetics datasets under various temperature, pH, particle size, and initial Cr(VI) concentration conditions. Data preprocessing via interpolation was implemented to augment the sparse time-series data. Early stopping regularization prevented overfitting, and dropout techniques enhanced model robustness. The Bi-LSTM models demonstrated a superior performance compared to the LSTM models. The inherent complexities of the process and data limitations resulted in a heavy-tailed and left-skewed residual distribution, indicating occasional deviations in the predictions of capacities obtained under extreme conditions. K-fold cross-validation demonstrated the stability of Bi-LSTM models 38 and 43, while response surfaces and validation with unseen datasets assessed their predictive accuracy and generalization capabilities. Shapley additive explanations analysis (SHAP) identified the initial Cr(VI) concentration and time as the most influential input features for the models. This study highlights the capabilities of deep recurrent neural networks in comprehending and predicting complex pollutant removal kinetic phenomena for environmental applications.