Artificial neural networks for insights into adsorption capacity of industrial dyes using carbon-based materials
Published in Separation and Purification Technology, 2023
Recommended citation: Sara Iftikhar, Nallain Zahra, Fazila Rubab, Raazia Abrar Sumra, Muhammad Burhan Khan, Ather Abbas, Zeeshan Haider Jaffari, Artificial neural networks for insights into adsorption capacity of industrial dyes using carbon-based materials, Separation and Purification Technology, Volume 326, 2023 https://doi.org/10.1016/j.seppur.2023.124891
A dataset of 1,514 observations covering 48 carbon-based materials and 16 industrial dyes was used to compare neural networks and other machine-learning approaches. SHAP analysis identified the experimental, adsorption, and synthesis conditions driving predictions.