Flux model development and synthesis optimization for an enhanced GO embedded nanocomposite membrane through FFD and RSM approach

Abstract

A two-level full factorial design was used to analyze several factors involved in PSF–GO–Pebax thin film nanocomposite membranes development. Permeate flux was chosen as a single response for four possible factors: Pebax selective layer concentration, amount of GO load to Pebax selective layer, Pebax–GO selective layer thickness, and amount of GO load to PSF substrate. The study is aimed at factors interaction and contribution towards the highest permeation flux via FFD and RSM approach. R 2 obtained from the ANOVA is 0.9937 with Pebax concentration as the highest contributing factor. Pebax concentration–amount of GO load to PSF substrate is the only interaction contributing to the highest flux. A regression analysis concluded the study with model development and an optimized condition for the membrane design.

Maximizing Permeate Flux of IPA Dehydration via Optimizing Pervaporation Condition Through Central Composite Design (CCD)

“…The Pebax-GO-PSF membrane used in this pervaporation setup is a self-made and continuous study via OFAT [7] and combined FFD-RSM [8] techniques. The binary mixture of IPA-water used in the pervaporation cycles is an isopropyl alcohol (IPA) with 99.98 % purity that was supplied by HmbG Chemicals and our own laboratory process distilled waterthe mixture was continuously stirred for 2 hours before immediately used for separation purposes.…”

Performance optimization of polyetherimide‐zeolite 4A mixed matrix membranes for carbon dioxide/methane separation process using response surface methodology

“…Response surface methodology generally enables constructing an empirical model from data obtained from a few systematically designed trials. The response surface methodology combined mathematical and statistical tools and was primarily derived from numerical methods [18]. Before beginning the optimization process, the response surface methodology starts with the experiment design to figure out the important model parameters [19,20].…”