Produced Water Desalination via Pervaporative Distillation

The roles of artificial intelligence techniques for increasing the prediction performance of important parameters and their optimization in membrane processes: A systematic review

Membrane-based separation processes has been recently of significant global interest compared to other conventional separation approaches due to possessing undeniable advantages like superior performance, environmentally-benign nature and simplicity of application. Computational simulation of fluids has shown its undeniable role in modeling and simulation of numerous physical/chemical phenomena including chemical engineering, chemical reaction, aerodynamics, drug delivery and plasma physics. Definition of fluids can be occurred using the Navier-Stokes equations, but solving the equations remains an important challenge. In membrane-based separation processes, true perception of fluid's manner through disparate membrane modules is an important concern, which has been significantly limited applying numerical/computational procedures such s computational fluid dynamics (CFD). Despite this noteworthy advantage, the optimization of membrane processes using CFD is time-consuming and expensive. Therefore, combination of artificial intelligence (AI) and CFD can result in the creation of a promising hybrid model to accurately predict the model results and appropriately optimize membrane processes and phase separation. This paper aims to provide a comprehensive overview about the advantages of commonly-employed ML-based techniques in combination with the CFD to intelligently increase the optimization accuracy and predict mass transfer and the unfavorable events (i.e., fouling) in various membrane processes. To reach this objective, four principal strategies of AI including SL, USL, SSL and ANN were explained and their advantages/disadvantages were discussed. Then after, prevalent ML-based algorithm for membrane-based separation processes. Finally, the application potential of AI techniques in different membrane processes (i.e., fouling control, desalination and wastewater treatment) were presented.

Enhanced cellulose nanofiber mechanical stability through ionic crosslinking and interpretation of adsorption data using machine learning

Herein we report the fabrication of cationic functionalized cellulose nanofibers (c-CNF) having 0.13 mmol.g^-1 ammonium content and its ionic crosslinking via the pad-batch process. The overall chemical modifications were justified through infrared spectroscopy. It is revealed that the tensile strength of ionic crosslinked c-CNF (z_c-CNF) improved from 3.8 MPa to 5.4 MPa over c-CNF. The adsorption capacity of z_c--CNF was found to be 158 mg.g^-1 followed by the Thomas model. Further, the experimental data were used to train and test a series of machine learning (ML) models. A total of 23 various classical ML models (as a benchmark) were compared simultaneously using Pycaret which helped reduce the programming complexity. However, shallow, and deep neural networks are used that outperformed the classic machine learning models. The best classical-tuned ML model using Random Forests regression had an accuracy of 92.6 %. The deep neural network made effective by early stopping and dropout regularization techniques, with 20 × 6 (Neurons x Layers) configuration, showed an appreciable prediction accuracy of 96 %.

Pervaporation Membranes for Seawater Desalination Based on Geo-rGO-TiO2 Nanocomposites: Part 2-Membranes Performances

This is part 2 of the research on pervaporation membranes for seawater desalination based on Geo-rGO-TiO₂ nanocomposite. The quality of the Geo-rGO-TiO₂ pervaporation membranes (PV), as well as the suitability of the built pervaporation system, is thoroughly discussed. The four membranes described in detail in the first article were tested for their capabilities using the parameters turbidity, salinity, total suspended solids (TSS), and electrical conductivity (EC). The membranes' flux permeate was measured as a function of temperature, and salt rejection was calculated using the electrical conductivity values of the feed and permeate. Fourier-transform infrared (FTIR) and X-ray diffraction (XRD) techniques were used to investigate changes in the chemical composition and internal structure of the membranes after use in pervaporation systems. The morphology of the membrane's surfaces was examined by means of scanning electron microscopy (SEM), and the elemental distribution was observed by using X-ray mapping and energy dispersive spectroscopy (EDS). The results showed that the pervaporation membrane of Geo-rGO-TiO₂ (1, 3) achieved a permeate flux as high as 2.29 kg/m²·h with a salt rejection of around 91%. The results of the FTIR and XRD measurements did not show any changes in the functional group and chemical compositions of the membrane after the pervaporation process took place. Long-term pressure and temperature feed cause significant cracking in geopolymer and Geo-TiO₂ (3) membranes. SEM results revealed that the surface of all membranes is leached out, and elemental distribution based on X-ray mapping and EDS observations revealed the addition of Na+ ions on the membrane surface. The study's findings pave the way for more research and development of geopolymers as the basic material for inorganic membranes, particularly with the addition of rGO-TiO₂ nanocomposites.

Desalinating a real hyper-saline pre-treated produced water via direct-heat vacuum membrane distillation

Membrane distillation (MD) is an emerging thermal desalination technology capable of desalinating waters of any salinity. During typical MD processes, the saline feedwater is heated and acts as the thermal energy carrier; however, temperature polarization (as well as thermal energy loss) contributes to low distillate fluxes, low single-pass water recovery and poor thermal efficiency. An alternative approach is to integrate an extra thermal energy carrier as part of the membrane and/or module assembly, which can channel externally provided heat directly to the membrane-feedwater interface and/or along the feed channel length. This direct-heat delivery has been demonstrated to increase single-pass water recovery and enhance the overall thermal efficiency. We developed a bench-scale direct-heated vacuum MD (DHVMD) process to desalinate pre-treated oil and gas "produced water" with an initial total dissolved solids of 115,500 ppm at a feed temperature ranging between 24 and 32 °C. We evaluated both water flux and specific energy consumption (SEC) as a function of water recovery. The system achieved a 50% water recovery without significant scaling, with an average flux >6 kg m^-2 hr^-1 and a SEC as low as 2,530 kJ kg^-1. The major species of mineral scales (i.e., NaCl, CaSO₄, and SrSO₄) that limited the water recovery to 68% were modeled in terms of thermodynamics and identified by scanning electron microscopy and energy-dispersive X-ray spectroscopy. In addition, we further developed and employed a physics-based process model to estimate temperature, salinity, water transport and energy flows for full-scale vacuum MD and DHVMD modules. Model results show that a direct-heat input rate of 3,600 W can increase single-pass water recovery from 2.1% to 3.1% while lowering the thermal SEC from 7,800 kJ kg^-1 to 6,517 kJ kg^-1 in an unoptimized module. Finally, the scaling up potential of DHVMD process is briefly discussed.

Modern Use of Water Produced by Purification of Municipal Wastewater: A Case Study

All the urban areas of developed countries have hydric distribution grids and sewage systems for collecting municipal wastewater to treatment plants. In this way, the municipal wastewater is purified from human excreta and other minor contaminants while producing excess sludges and purified water. In arid and semi-arid areas of the world, the purified water can be used, before discharging, to enhance the energy efficiency of seawater desalination and solve the problems of marine pollution created by desalination plants. Over the past half-century, seawater desalination has gradually met demand in urbanized, oil-rich, arid areas. At the same time, technological evolution has made it possible to significantly increase the energy efficiency of the plants and reduce the unit cost of the produced water. However, for some years, these trends have flattened out. The purified water passes through the hybridized desalination plant and produces renewable osmotic energy before the final discharge in the sea to restart the descent behaviour. Current technological development of reverse osmosis (RO), pressure retarded osmosis (PRO) and very efficient energy recovery devices (ERDs) allows this. Furthermore, it is reasonable to predict that, in the short-medium term, a new generation of membranes specifically designed for improving the performance of the pressure retarded osmosis will be available. In such circumstances, the presently estimated 13-20% decrease of the specific energy consumption will improve up to more than 30%. With the hybrid plant, the salinity of the final discharged brine is like that of seawater, while the adverse effect of GHG emission will be significantly mitigated.