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Membrane Separation in API Manufacture – Scoping and Performance Prediction


   School of Engineering and Materials Science

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  Prof Andrew Livingston  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

Separations are widely acknowledged to constitute 50-70% of the capital and operating costs of chemical processes. Membranes have been shown to offer significant potential improvements, offering major reductions in energy and reducing the high process mass intensity. While membranes have been shown by academic groups to be effective in many unit operations, they have not had major industrial impact in the pharma industry to date. We assert that a major reason for this is that it remains difficult to scope the feasibility of available membranes for a given solvent/solute separation, due to lack of design tools; and that significant lab-based work is still required to determine feasibility. Ideally one would like to be able to make a reasonable prediction of the solvent flux and solute separations that would be obtained for a given solvent mixture and combination of solvents, based on data for a fixed number of solvents and model solutes.

The objective of this Case Studentship is to focus on developing a scoping and design tool for processes used in API manufacture.

This project would focus on the characterisation of commercially available membranes using a base set of 5-7 single solvents ranging from polar to apolar and a base set of 10-12 single solutes in the MW range 300-800 chosen for solubility across the solvent range, to be agreed with AZ. The permeance of the solvents and solutes would be determined and used to characterise performance using established membrane transport models. The base set data would be used to predict the performance on 3 further single solvents and 3 further single solutes, using the descriptors for the further solvents and solutes, and the membranes. These predictions will be tested experimentally. The OSN Designer programme developed will be adapted/developed for prediction of various industrial unit operations and verified experimentally.

Funding

This studentship is fully funded via the UKRI EPSRC Doctoral Training Programme for 3.5 years and includes a stipend (currently £17,609 in 2021/2022) and Home Fees.

Eligibility

  • Candidates are expected to start from September 2022
  • Available to applicants from the UK Home applicants. (See: http://www.welfare.qmul.ac.uk/money/feestatus/ for details of UK Home status)
  • The minimum requirement for this studentship opportunity is a good Honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of 6.0 in Writing and 5.5 in all sections (Reading, Listening, Speaking).

Supervisor Contact Details:

For informal enquiries about this position, please contact Professor Andrew Livingston, E-mail: [Email Address Removed]

Application Method:

To apply for this studentship and for entry on to the PhD Full-time Chemical Engineering - Semester 1 (September Start) please follow the instructions detailed on the following webpage:

Research degrees in Engineering:​ http://www.qmul.ac.uk/postgraduate/research/subjects/engineering.html

Further Guidance: http://www.qmul.ac.uk/postgraduate/research/

Please be sure to include a reference to ‘2022 EPSRC DTP AL’ to associate your application with this studentship opportunity.

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