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Ovung A, Jamir N, Bhattacharyya J. Lysozyme binding with sulfa group of antibiotics: comparative binding thermodynamics and computational study. LUMINESCENCE 2022; 37:702-712. [DOI: 10.1002/bio.4211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/21/2022] [Accepted: 02/08/2022] [Indexed: 11/12/2022]
Affiliation(s)
- Aben Ovung
- Department of Chemistry National Institute of Technology Nagaland, Chumukedima Dimapur India
| | - Nungshioba Jamir
- Department of Chemistry National Institute of Technology Nagaland, Chumukedima Dimapur India
| | - Jhimli Bhattacharyya
- Department of Chemistry National Institute of Technology Nagaland, Chumukedima Dimapur India
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Yogarathinam LT, Velswamy K, Gangasalam A, Ismail AF, Goh PS, Narayanan A, Abdullah MS. Performance evaluation of whey flux in dead-end and cross-flow modes via convolutional neural networks. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 301:113872. [PMID: 34607142 DOI: 10.1016/j.jenvman.2021.113872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 09/08/2021] [Accepted: 09/26/2021] [Indexed: 06/13/2023]
Abstract
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.
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Affiliation(s)
- Lukka Thuyavan Yogarathinam
- Membrane Research Laboratory, Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, 620 015, India; Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia
| | - Kirubakaran Velswamy
- Department of Chemical and Materials Engineering, Donadeo Innovation Center for Engineering, University of Alberta-T6G 1H9, Edmonton, Canada
| | - Arthanareeswaran Gangasalam
- Membrane Research Laboratory, Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, 620 015, India.
| | - Ahmad Fauzi Ismail
- Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia.
| | - Pei Sean Goh
- Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia
| | - Anantharaman Narayanan
- Membrane Research Laboratory, Department of Chemical Engineering, National Institute of Technology, Tiruchirappalli, 620 015, India
| | - Mohd Sohaimi Abdullah
- Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia
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