Computational fluid dynamics simulation study of hypersaline water desalination via membrane distillation: Effect of membrane characteristics and operational parameters.

In this study, a comprehensive model was developed using Computational Fluid Dynamics (CFD), and the behaviour of a direct contact membrane distillation (DCMD) system was investigated at hypersaline feedwater conditions. The effects of various operating parameters including feed and permeate velocities, temperatures and salinities, as well as different membrane characteristics like thickness, porosity, and thermal conductivity were studied. The developed simulation model was also validated using experimental data.

Novel prosperous computational estimations for greenhouse gas adsorptive control by zeolites using machine learning methods.

To predict CO adsorptive capture, as a vital environmental issue, using different zeolites including 5A, 13X, T-Type, SSZ-13, and SAPO-34, different models have been developed by implementing artificial intelligence algorithms. Hybrid adaptive neuro-fuzzy inference system (Hybrid-ANFIS), particle swarm optimization-adaptive neuro-fuzzy inference system (PSO-ANFIS) and the least-squares support vector machine (LSSVM) modeling optimized with the coupled simulated annealing (CSA) optimization have been employed for the models. The developed models, validated by utilizing various graphical and statistical methods exhibited that the Hybrid-ANFIS model estimations for the gas adsorption on 5A, T-Type, SSZ-13, and SAPO-34 zeolites with average absolute relative deviation (AARD) % of 8.

Chitosan-wrapped multiwalled carbon nanotube as filler within PEBA thin film nanocomposite (TFN) membrane to improve dye removal.

Herein, a thin film nanocomposite (TFN) membrane was prepared through deposition of a very thin mixed matrix layer of PEBAX®1657/chitosan-wrapped multiwalled carbon nanotubes (CWNTs) on an ultraporous polyethersulfone (PES) substrate. The eco-friendly CWNTs were synthesized via non-covalent functionalization of MWNTs by carbohydrate polymer chitosan. They were then incorporated into PEBAX®1657 matrix at different loadings (0, 0.

3-Aminopropyltriethoxysilane-aided cross-linked chitosan membranes for gas separation: grand canonical Monte Carlo and molecular dynamics simulations.

Molecular simulations were performed to consider the structural and transport properties of chitosan/3-aminopropyltriethoxysilane (APTEOS) mixed matrix membranes (MMMs). In order to consider the presence of APTEOS content on the performances of membrane, various amounts of APTEOS were added to the polymeric matrix as a cross-linker. Structural characterizations such as radial distribution function (RDF), fractional free volume (FFV) and X-ray diffraction (XRD) were carried out on the simulated cells.

Rigorous prognostication and modeling of gas adsorption on activated carbon and Zeolite-5A.

Gas adsorption on various adsorbents is of highly important issue for the separation of gas mixtures in many industrial processes. In this work, estimation of pure gases (CH, N, CO, H, CH) adsorption on activated carbon (AC) and CO, CH, N on Zeolite-5A adsorbent were studied by developing four different computing techniques, namely MLP-ANN, ANFIS, LSSVM, and PSO-ANFIS for a broad range of experimental data found in the literature. Temperature, pressure, pore size (only for AC) and kinetic diameter of adsorbed gases are considered as the inputs and the gas adsorption as the output parameters of the developed models.

Effects of ZnO Nanoparticle on the Gas Separation Performance of Polyurethane Mixed Matrix Membrane.

Polyurethane (PU)-ZnO mixed matrix membranes (MMM) were fabricated and characterized for gas separation. A thermogravimetric analysis (TGA), a scanning electron microscope (SEM) test and an atomic-force microscopy (AFM) revealed that the physical properties and thermal stability of the membranes were improved through filler loading. Hydrogen Bonding Index, obtained from the Fourier transform infrared spectroscopy (FTIR), demonstrate that the degree of phase separation in PU-ZnO 0.