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Characterisation and prediction of membrane separation performance: An industrial assessment. / Darren Lee Oatley

Swansea University Author: Darren Lee Oatley

Abstract

The main objective of this work was to develop the existing predictive models for membrane nanofiltration, previously verified at the laboratory scale, and apply these theoretical descriptions to separations of real industrial importance. A detailed comparison was made between the updated Donnan ste...

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Published: 2004
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
URI: https://cronfa.swan.ac.uk/Record/cronfa42747
first_indexed 2018-08-02T18:55:27Z
last_indexed 2018-08-03T10:10:59Z
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recordtype RisThesis
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spelling 2018-08-02T16:24:30.3206001 v2 42747 2018-08-02 Characterisation and prediction of membrane separation performance: An industrial assessment. 385bf845eaf98536468f65e28f3c49c3 NULL Darren Lee Oatley Darren Lee Oatley true true 2018-08-02 The main objective of this work was to develop the existing predictive models for membrane nanofiltration, previously verified at the laboratory scale, and apply these theoretical descriptions to separations of real industrial importance. A detailed comparison was made between the updated Donnan steric partitioning model (UDSPM) model and the simplified linear UDSPM model and the extent of deviation over a wide range of possible nanofiltration conditions was small. This result justified the use of the simplified model for predicting multi-component separations reducing computational time and complexity. A theoretical and experimental comparison was made between two existing continuum descriptions of dielectric exclusion phenomenon. The two models were found to calculate the total contribution of dielectric exclusion effects to the same order of magnitude. The Born model was suggested as the most practical description at present because of the model's inherent simplicity. The UDSPM and linear UDSPM were then employed as a predictive tool in the isolation of N-acetyl-D-neuraminic acid, an important precursor in the production of the influenza antiviral RelenzaTM. The NanomaxTM-50 commercially available NF membrane was characterised and a membrane charge isotherm was developed from a study of the diafiltration components. Excellent agreement between the experimental findings and the model predictions was observed when the membrane charge was varied with pyruvate ion concentration. The linear UDSPM model was then used to assess the performance of a possible full scale industrial process for the recovery of sodium cefuroxime from a process effluent. The model results indicate that inclusion of nanofiltration technology will indeed facilitate the recovery of the high value antibiotic and produce an effluent of significantly improved quality. Overall, as a result of the rational approach taken in this study, the application of existing predictive nanofiltration models for the design, optimisation and scale-up of more complex industrially relevant separations has been established. This will further promote the use of membrane technology in the process industries, such as pharmaceutical and fine chemical manufacture, by significantly reducing development risk and time. E-Thesis Chemical engineering. 31 12 2004 2004-12-31 COLLEGE NANME Engineering COLLEGE CODE Swansea University Doctoral Ph.D 2018-08-02T16:24:30.3206001 2018-08-02T16:24:30.3206001 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Darren Lee Oatley NULL 1 0042747-02082018162518.pdf 10807516.pdf 2018-08-02T16:25:18.7900000 Output 13014737 application/pdf E-Thesis true 2018-08-02T16:25:18.7900000 false
title Characterisation and prediction of membrane separation performance: An industrial assessment.
spellingShingle Characterisation and prediction of membrane separation performance: An industrial assessment.
Darren Lee Oatley
title_short Characterisation and prediction of membrane separation performance: An industrial assessment.
title_full Characterisation and prediction of membrane separation performance: An industrial assessment.
title_fullStr Characterisation and prediction of membrane separation performance: An industrial assessment.
title_full_unstemmed Characterisation and prediction of membrane separation performance: An industrial assessment.
title_sort Characterisation and prediction of membrane separation performance: An industrial assessment.
author_id_str_mv 385bf845eaf98536468f65e28f3c49c3
author_id_fullname_str_mv 385bf845eaf98536468f65e28f3c49c3_***_Darren Lee Oatley
author Darren Lee Oatley
author2 Darren Lee Oatley
format E-Thesis
publishDate 2004
institution Swansea University
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description The main objective of this work was to develop the existing predictive models for membrane nanofiltration, previously verified at the laboratory scale, and apply these theoretical descriptions to separations of real industrial importance. A detailed comparison was made between the updated Donnan steric partitioning model (UDSPM) model and the simplified linear UDSPM model and the extent of deviation over a wide range of possible nanofiltration conditions was small. This result justified the use of the simplified model for predicting multi-component separations reducing computational time and complexity. A theoretical and experimental comparison was made between two existing continuum descriptions of dielectric exclusion phenomenon. The two models were found to calculate the total contribution of dielectric exclusion effects to the same order of magnitude. The Born model was suggested as the most practical description at present because of the model's inherent simplicity. The UDSPM and linear UDSPM were then employed as a predictive tool in the isolation of N-acetyl-D-neuraminic acid, an important precursor in the production of the influenza antiviral RelenzaTM. The NanomaxTM-50 commercially available NF membrane was characterised and a membrane charge isotherm was developed from a study of the diafiltration components. Excellent agreement between the experimental findings and the model predictions was observed when the membrane charge was varied with pyruvate ion concentration. The linear UDSPM model was then used to assess the performance of a possible full scale industrial process for the recovery of sodium cefuroxime from a process effluent. The model results indicate that inclusion of nanofiltration technology will indeed facilitate the recovery of the high value antibiotic and produce an effluent of significantly improved quality. Overall, as a result of the rational approach taken in this study, the application of existing predictive nanofiltration models for the design, optimisation and scale-up of more complex industrially relevant separations has been established. This will further promote the use of membrane technology in the process industries, such as pharmaceutical and fine chemical manufacture, by significantly reducing development risk and time.
published_date 2004-12-31T04:36:25Z
_version_ 1821559997741400064
score 11.047674

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