Machine learning for optimizing Reactive Red 120 biosorption onto cross-linked gelatin/alginate-TTAB-montmorillonite composite

Explainable Machine Learning and Mechanistic Interpretation of Congo Red Removal by CTABr-Modified Bio-Apatite-Based Adsorbent

Waste-derived adsorbents represent a promising strategy for sustainable wastewater treatment; however, adsorption processes are frequently governed by complex nonlinear interactions that remain difficult to interpret using conventional approaches. The present study developed an integrated experimental and explainable m...

Machine learning aided RSM approach to parameter optimization for Rhodamine B removal using sawdust

Machine learning–assisted sustainable removal of cationic dyes using Butea monosperm a leaf powder as an eco-friendly biosorbent

Peanut Husk as an Efficient Biosorbent for Methylene Blue Removal from Wastewater: Kinetic, Isotherm, and Exploratory Artificial Neural Network Analysis

This study explores the adsorption performance of clean peanut husk (CPH) as a sustainable and low-cost biosorbent for removing methylene blue (MB) from aqueous solutions. Batch experiments investigated the effects of dye concentration, biosorbent dosage, pH, particle size, and temperature. FT-IR analysis confirmed the...

Citric acid-modified loquat seed waste as biosorbent for methylene blue: kinetics, isotherm, thermodynamics, and machine learning-based prediction of adsorption performance

Graphical abstract showing citric-acid modification of loquat seed powder and its application as a biosorbent for methylene blue removal. The material achieved a maximum adsorption capacity of 47.53 mg/g within 9 min, followed by the Freundlich and pseudo-second-order models, which were accurately predicted by a rand...

Hybrid Isotherm–Machine Learning Modeling of CO₂ Adsorption in Modulator-Tuned MIL-101(Cr)