The neural network was trained using the input data for simulation of the adsorption capacity. Artificial neural network (ANN) technique was used for simulation of the data in which ion type and initial concentration of the ions in the feed was selected as the input variables to the neural network. A number of measured data was collected and used in the simulations via the artificial intelligence technique. This novel adsorbent showed high surface area for adsorption capacity, and was chosen to develop the model for study of ions removal using this adsorbent. The simulated adsorbent was a composite of UiO-66-(Zr)-(COOH) 2 MOF grown onto the surface of functionalized Ni 50-Co 50-LDH sheets. We developed a computational-based model for simulating adsorption capacity of a novel layered double hydroxide (LDH) and metal organic framework (MOF) nanocomposite in separation of ions including Pb(II) and Cd(II) from aqueous solutions.
0 kommentar(er)
