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  1. Yogarathinam LT, Velswamy K, Gangasalam A, Ismail AF, Goh PS, Narayanan A, et al.
    J Environ Manage, 2022 Jan 01;301:113872.
    PMID: 34607142 DOI: 10.1016/j.jenvman.2021.113872
    Effluent originating from cheese production puts pressure onto environment due to its high organic load. Therefore, the main objective of this work was to compare the influence of different process variables (transmembrane pressure (TMP), Reynolds number and feed pH) on whey protein recovery from synthetic and industrial cheese whey using polyethersulfone (PES 30 kDa) membrane in dead-end and cross-flow modes. Analysis on the fouling mechanistic model indicates that cake layer formation is dominant as compared to other pore blocking phenomena evaluated. Among the input variables, pH of whey protein solution has the biggest influence towards membrane flux and protein rejection performances. At pH 4, electrostatic attraction experienced by whey protein molecules prompted a decline in flux. Cross-flow filtration system exhibited a whey rejection value of 0.97 with an average flux of 69.40 L/m2h and at an experimental condition of 250 kPa and 8 for TMP and pH, respectively. The dynamic behavior of whey effluent flux was modeled using machine learning (ML) tool convolutional neural networks (CNN) and recursive one-step prediction scheme was utilized. Linear and non-linear correlation indicated that CNN model (R2 - 0.99) correlated well with the dynamic flux experimental data. PES 30 kDa membrane displayed a total protein rejection coefficient of 0.96 with 55% of water recovery for the industrial cheese whey effluent. Overall, these filtration studies revealed that this dynamic whey flux data studies using the CNN modeling also has a wider scope as it can be applied in sensor tuning to monitor flux online by means of enhancing whey recovery efficiency.
  2. Yogarathinam LT, Usman J, Othman MHD, Ismail AF, Goh PS, Gangasalam A, et al.
    J Hazard Mater, 2022 02 15;424(Pt A):127298.
    PMID: 34571470 DOI: 10.1016/j.jhazmat.2021.127298
    In this study, an economic silica based ceramic hollow fiber (HF) microporous membrane was fabricated from guinea cornhusk ash (GCHA). A silica interlayer was coated to form a defect free silica membrane which serves as a support for the formation of thin film composite (TFC) ceramic hollow fiber (HF) membrane for the removal of microplastics (MPs) from aqueous solutions. Polyacrylonitrile (PAN), polyvinyl-chloride (PVC), polyvinylpyrrolidone (PVP) and polymethyl methacrylate (PMMA) are the selected MPs The effects of amine monomer concentration (0.5 wt% and 1 wt%) on the formation of poly (piperazine-amide) layer via interfacial polymerization over the GCHA ceramic support were also investigated. The morphology analysis of TFC GCHA HF membranes revealed the formation of a poly (piperazine-amide) layer with narrow pore arrangement. The pore size of TFC GCHA membrane declined with the formation of poly (piperazine-amide) layer, as evidenced from porosimetry analysis. The increase of amine concentration reduced the porosity and water flux of TFC GCHA HF membranes. During MPs filtration, 1 wt% (piperazine) based TFC GCHA membrane showed a lower transmission percentage of PVP (2.7%) and other suspended MPs also displayed lower transmission. The impact of humic acid and sodium alginate on MPs filtration and seawater pretreatment were also analyzed.
  3. Yogarathinam LT, Velswamy K, Gangasalam A, Ismail AF, Goh PS, Subramaniam MN, et al.
    Chemosphere, 2022 Jan;286(Pt 3):131822.
    PMID: 34416593 DOI: 10.1016/j.chemosphere.2021.131822
    In this study, fouling mechanism and modelling analysis of synthetic lignocellulose biomass and agricultural palm oil effluent was studied using polyethersulfone (PES) ultrafiltration (UF) 10 kDa membrane. The impact of process variables (transmembrane pressure (TMP), pH and concentration of feed solution) on lignocellulosic flux was analysed using pore blocking model. The feasible approaches on utilising deep learning artificial neural network (ANN) to predict smaller flux datasets are studied. Among the input variables, pH of lignin feed solution has significant control towards flux and lignin rejection coefficient for both lignin and lignocellulosic solution. Alteration in the structure of lignin at different pH conditions contributed in the improvement of lignin rejection coefficient to 0.98 at the feed pH of 9. A maximum steady state flux of 52.03 L/m2h was observed at the lower lignin concentration (0.25 g/L), TMP of 200 kPa and feed pH of 3. At high TMP and concentration, lignin rejection decreased due to enhancement of feed concentration on membrane surface. The mechanistic model exhibited that cake layer phenomena was dominant in both lignin and lignocellulosic solution. The proposed ANN model showed good correlation (R2-1.00) with experimental non-linear flux dynamic data of both lignin and synthetic lignocellulosic solution. In ANN analysis, activation function, algorithm and neuron effect have significant effect in design of accurate model for prediction of small flux datasets. Aerobically-treated palm oil mill filtration analysis also showed that cake layer phenomenon was dominant. A water recovery of 82 % was achieved even at low TMP under short durations.
  4. Yogarathinam LT, Goh PS, Ismail AF, Gangasalam A, Ahmad NA, Samavati A, et al.
    Chemosphere, 2022 Jan 11;293:133561.
    PMID: 35031248 DOI: 10.1016/j.chemosphere.2022.133561
    Membrane technology is a sustainable method to remove pollutants from petroleum wastewater. However, the presence of hydrophobic oil molecules and inorganic constituents can cause membrane fouling. Biomass derived biopolymers are promising renewable materials for membrane modification. In this study, fouling resistant biopolymer N-phthaloylchitosan (CS)- based polythersulfone (PES) mixed matrix membranes (MMMs) incorporated with nanocrystalline cellulose (NCC) was fabricated via phase inversion method and applied for produced water (PW) treatment. The morphological and Fourier-transform infrared spectroscopy (FTIR) analyses of the as-prepared NCC evidenced the formation of fibrous sheet-like structure and the presence of hydrophilic group. The membrane morphology and AFM analysis showed that the NCC altered the surface and cross-sectional morphology of the CS-PES MMMs. The tensile strength of NCC-CS-PES MMMs was also enhanced. 0.5 wt% NCC-CS-PES MMMs displayed a water permeability of 1.11 × 10-7 m/s.kPa with the lowest contact angle value of 61°. It affirmed that its hydrophilicity increased through the synergetic interaction between CS biopolymer and NCC. The effect of process variables such as transmembrane pressure (TMP) and synthetic produced water (PW) concentration were evaluated for both neat PES and NCC-CS-PES MMMs membranes. 0.5 wt% NCC-CS-PES MMMs exhibited the highest PW rejection of 98% when treating 50 mgL-1 of synthetic PW at a transmembrane pressure (TMP) of 200 kPa. The effect of nano silica and sodium chloride on the long-term PW filtration of NCC-CS-PES MMMs was also investigated.
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