Neural-based modeling adsorption capacity of metal organic framework materials with application in wastewater treatment

Abstract

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. The simulated adsorbent was a composite of UiO-66-(Zr)-(COOH)2 MOF grown onto the surface of functionalized Ni50-Co50-LDH sheets. 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. A number of measured data was collected and used in the simulations via the artificial intelligence technique. 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. The neural network was trained using the input data for simulation of the adsorption capacity. Two hidden layers with activation functions in form of linear and non-linear were designed for the construction of artificial neural network. The model’s training and validation revealed high accuracy with statistical parameters of R2 equal to 0.99 for the fitting data. The trained ANN modeling showed that increasing the initial content of Pb(II) and Cd(II) ions led to a significant increment in the adsorption capacity (Qe) and Cd(II) had higher adsorption due to its strong interaction with the adsorbent surface. The neural model indicated superior predictive capability in simulation of the obtained data for removal of Pb(II) and Cd(II) from an aqueous solution.

Metal–organic framework composites from a mechanochemical process

“…Due to unique porosity and functional groups, MOF itself has already been employed as a great candidate for adsorption, including gas adsorption, 134 water treatment, 135,136 and specific ion adsorption. 137 The integration of MOFs with other porous materials has demonstrated great potential in increasing their adsorption ability compared with the parent materials.…”

Computational Fluid Dynamics Analysis of Mercury Adsorption by Inverse-Vulcanized Porous Sulfur Copolymers

“…Researchers developed the CFD simulation models to study the various pollutants’ adsorption effects inside adsorbent materials. − They were either batch or packed-bed reactor processes . The validation of the CFD model is a crucial part that always needs experimental data.…”