PhD Studentship: An Advanced Computational Modelling Framework for the Design and Optimization of Agitated Filter Dryers

Application deadline: Friday, August 30, 2024 

Stipend: £21,237 per annum + UK fees 

Duration of Studentship: 3.5 years 

Start date: 1 February 2025 

Vacancy information

The Chemical Engineering Department is seeking an enthusiastic and dedicated PhD student to research the design and optimization of agitated filter dryers via advanced computational fluid dynamics modelling. This project is in collaboration with AstraZeneca, a global pharmaceutical company with strong focus on research and development (R&D). The post-holder will have the opportunity to share ideas and results with the industrial partner and collaborate with its R&D team.

Studentship description

Particle size distribution (PSD) is a critical quality attribute in the production of active pharmaceutical ingredients (APIs). Owing to particle attrition, breakage and/or agglomeration, in agitated filter dryers the PSD is prone to deviate from specifications. Failure to meet the required PSD can result in poor powder flowability, potentially leading to batch rejection. Because drying is a crucial final step in API manufacturing, controlling the PSD is critical. Batch rejection incurs significant costs and has substantial implications for sustainability. To address this challenge and enhance right-first-time manufacturing, this project aims to leverage modelling and simulation to understand more deeply the complex multiphysics phenomena occurring in agitated filter dryers. To characterize these unit operations, existing models are either too simplistic, lacking in detail, or too computationally expensive (e.g., discrete element methods). This project aims to model the isolation and drying of crystals from the mother liquor following the upstream crystallization process. The workflow involves constructing a detailed computational fluid dynamics (CFD) model for solid-liquid mixing. Subsequent stages will include incorporating population balance modelling (PBM) into the CFD model for describing the drying of the crystals. Additionally, the student will develop a reduced-order model (ROM) by combining data generated from the CFD/PBM simulations with experimental data provided by the industrial partner. This integrated approach aims to offer a more accurate representation of the complex phenomena involved, facilitating the effective control and optimization of agitated filter dryers.

The post-holder will learn how to use multiphase CFD codes and post-process the results of the simulations, which will be validated against experimental data. The techniques and skills that the student will learn are transferable to technological problems relevant to several industrial sectors, e.g., healthcare and catalysis.

The post-holder will present the research results at international conferences and in peer-reviewed journal articles of high international standing.

Person specification

The successful candidate must be a dedicated student who has completed a first-class degree at the MEng/MSc level in Chemical or Mechanical Engineering, Physics or a related discipline. Willingness to perform independently, yet within a collaborative environment, is a must. Demonstrable knowledge of research methods, multiphase flows, computational fluid dynamics and transport phenomena are desirable.

Eligibility

The post is fully funded (stipend and UK fees) for 3.5 years. Overseas students may apply, provided they can independently cover the difference between UK and overseas tuition fees.

Applications should be submitted through: https://evision.ucl.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RRDCENSING01&code2=0037

Please nominate Prof. Luca Mazzei as supervisor and include a statement of interest.

For informal enquiries please contact Prof. Luca Mazzei at l.mazzei@ucl.ac.uk.

For further information on the MPhil/PhD course as well as the recruitment and selection process, please click on the link below:

https://www.ucl.ac.uk/chemical-engineering/study/mphilphd

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