Advances in Membrane Distillation Module Configurations

Membrane Distillation (MD) is a membrane-based, temperature-driven water reclamation process. While research emphasis has been largely on membrane design, upscaling of MD has prompted advancements in energy-efficient module design and configurations. Apart from the four conventional configurations, researchers have come up with novel MD membrane module designs and configurations to improve thermal efficiency. While membrane design has been the focus of many studies, development of appropriate system configurations for optimal energy efficiency for each application has received considerable attention, and is a critical aspect in advancing MD configurations. This review assesses advancements in modified and novel MD configurations design with emphasis on the effects of upscaling and pilot scale studies. Improved MD configurations discussed in this review are the material gap MD, conductive gap MD, permeate gap MD, vacuum-enhanced AGMD/DCMD, submerged MD, flashed-feed MD, dead-end MD, and vacuum-enhanced multi-effect MD. All of these modified MD configurations are designed either to reduce the heat loss by mitigating the temperature polarization or to improve the mass transfer and permeate flux. Vacuum-enhanced MD processes and MD process with non-contact feed solution show promise at the lab-scale and must be further investigated. Hollow fiber membrane-based pilot scale modules have not yet been sufficiently explored. In addition, comparison of various configurations is prevented by a lack of standardized testing conditions. We also reflect on recent pilot scale studies, ongoing hurdles in commercialization, and niche applications of the MD process.

Model Based Simulation and Genetic Algorithm Based Optimisation of Spiral Wound Membrane RO Process for Improved Dimethylphenol Rejection from Wastewater

Reverse Osmosis (RO) has already proved its worth as an efficient treatment method in chemical and environmental engineering applications. Various successful RO attempts for the rejection of organic and highly toxic pollutants from wastewater can be found in the literature over the last decade. Dimethylphenol is classified as a high-toxic organic compound found ubiquitously in wastewater. It poses a real threat to humans and the environment even at low concentration. In this paper, a model based framework was developed for the simulation and optimisation of RO process for the removal of dimethylphenol from wastewater. We incorporated our earlier developed and validated process model into the Species Conserving Genetic Algorithm (SCGA) based optimisation framework to optimise the design and operational parameters of the process. To provide a deeper insight of the process to the readers, the influences of membrane design parameters on dimethylphenol rejection, water recovery rate and the level of specific energy consumption of the process for two different sets of operating conditions are presented first which were achieved via simulation. The membrane parameters taken into consideration include membrane length, width and feed channel height. Finally, a multi-objective function is presented to optimise the membrane design parameters, dimethylphenol rejection and required energy consumption. Simulation results affirmed insignificant and significant impacts of membrane length and width on dimethylphenol rejection and specific energy consumption, respectively. However, these performance indicators are negatively influenced due to increasing the feed channel height. On the other hand, optimisation results generated an optimum removal of dimethylphenol at reduced specific energy consumption for a wide sets of inlet conditions. More importantly, the dimethylphenol rejection increased by around 2.51% to 98.72% compared to ordinary RO module measurements with a saving of around 20.6% of specific energy consumption.

Efficient CH4/CO2 Gas Mixture Separation through Nanoporous Graphene Membrane Designs

Nanoporous graphene membranes have drawn special attention in the gas-separation processes due to their unique structure and properties. The complexity of the physical understanding of such membrane designs restricts their widespread use for gas-separation applications. In the present study, we strive to propose promising designs to face this technical challenge. In this regard, we investigated the permeation and separation of the mixture of adsorptive gases CO2 and CH4 through a two-stage bilayer sub-nanometer porous graphene membrane design using molecular dynamics simulation. A CH4/CO2 gashouse mixture with 80 mol% CH4 composition was generated using the benchmarked force-fields and was forced to cross through the porous graphene membrane design by a constant piston velocity. Three chambers are considered to be feeding, transferring, and capturing to examine the permeation and separation of molecules under the effect of the two-stage membrane. The main objective is to investigate the multistage membrane and bilayer effect simultaneously. The permeation and separation of the CO2 and CH4 molecules while crossing through the membrane are significantly influenced by the pore offset distance (W) and the interlayer spacing (H) of the bilayer nanoporous graphene membrane. Linear configurations (W = 0 Å) and those with the offset distance of 10 Å and 20 Å were examined by varying the interlayer spacing between 8 Å, 12 Å, and 16 Å. The inline configuration with an interlayer spacing of 12 Å is the most effective design among the examined configurations in terms of optimum separation performance and high CO2 and CH4 permeability. Furthermore, increasing the interlayer distance to 16 Å results in bulk-like behavior rather than membrane-like behavior, indicating the optimum parameters for high selectivity and permeation. Our findings present an appropriate design for the effective separation of CH4/CO2 gas mixtures by testing novel nanoporous graphene configurations.

Data-driven and DFT Assisted Theoretic Guide for Membrane Design in Flow Batteries

Solvent treatment has been proved to be an effective strategy for preparation of highly selective porous membrane in flow batteries. Herein, a fast and efficient method to screen suitable solvent...