Dataset and MATLAB Code for AI-Driven Deep Learning Prediction of Copper Adsorption on Zeolite-Silver Nanocomposites

This repository contains the complete dataset, raw experimental data, MATLAB code, and generated figures associated with the preprint: "Artificial Intelligence-Driven Deep Learning for Predicting Copper Adsorption on Zeolite-Silver Nanocomposites in Sustainable Water Treatment" (SSRN DOI: 10.2139/ssrn.5194712). The package includes the raw experimental adsorption data (01_Raw_Experimental_Data.csv), the main MATLAB script (Codigo_Preprint_SSRN_5194712.m) used to train 8 Machine Learning algorithms (including various Artificial Neural Network architectures), and the resulting figures (Figures 3, 4, and 5) and performance metrics (Table1_Algorithm_Comparison.csv). The experimental data were extracted from our previously published work in Nanomaterials (DOI: 10.3390/nano14030258). This repository aims to promote Open Science, ensuring the full reproducibility of the computational analysis presented in the manuscript. Licensing: The dataset and figures are licensed under CC BY 4.0, while the MATLAB code is licensed under the MIT License