Abstract:
The increasing use of synthetic dyes in various industries results in significant environmental pollution, particularly concerning wastewater effluent that is often resistant to conventional biological treatment methods. Biosorption utilizing agricultural waste materials, such as rice husk, presents a promising, sustainable, and cost-effective alternative for dye removal from aqueous solutions. However, the inherent heterogeneity and complex structure of natural adsorbents lead to highly nonlinear adsorption behavior that is challenging for traditional kinetic and isotherm models based on simplified assumptions to accurately predict.
Reference this Research Paper (copy & paste below code):
Yu-Ting Huang, Ming-Cheng Shih
(2025); Artificial Neural Network Modeling for Methylene Blue Adsorption onto Rice Husk: Performance Evaluation and Adsorption Kinetics Prediction; International Journal of Scientific and Research Publications (IJSRP)
15(6) (ISSN: 2250-3153), DOI: http://dx.doi.org/10.29322/IJSRP.15.06.2025.p16217