PhD studentship opportunities for 2017 entry
Applications are invited for full-time PhD studentships in the School of Chemistry and Chemical Engineering at Queen’s University Belfast, for 2017 entry.
These are DfE-funded studentships for 3 years of full-time research, covering tuition fees at the home rate plus a stipend of £14,296 per annum.
Academic criteria -Candidates must hold a minimum of 2.1 honours in a relevant subject. Candidates with a 2.2 honours degree and a suitable MSc may also be considered.
Residency criteria – only UK residents, as defined by the University’s Postgraduate Office, are eligible for DfE funding.
How to apply
Applications must be submitted via the University’s online applications portal. Only applications submitted via the portal will be accepted.
The closing date is 14 April 2017. Applications must be complete by this date ie the application and with all the required supporting documentation must be uploaded to the portal.
For general enquiries, including queries about the application process, contact Karen Moore in the first instance. For more detailed information about the projects, contact the named supervisor. For queries about eligibility, contact the University’s Postgraduate Office.
Online monitoring and control of high shear granulation process: use of acoustic emission signals coupled with high speed video imaging - Professor Vivek Ranade, Dr Chi Mangwandi, Dr Aditya Putranto
The Process Analytical Technology (PAT) initiative was launched by Food Drug Administration (USA) in 2004. Its main concept is to ensure the safety of drugs by building quality into the products instead of testing the quality after production. This is achieved by understanding the process by defining critical process parameters (CPP) which affect the critical quality attributes (CQA) and monitoring the CCPs timely to minimise batch rejections. Online process monitoring tools such as Acoustic Emission would be used to monitor product properties such as density and composition during the granulation process. Design of Experiment (DoE) and multivariate methods would then be used to gain an in-depth understanding of the granulation the process. High speed video imaging (HSVI) will be used to monitor the size enlargement process during the granulation. The images from the HSVI will be analysed using a bespoke MATLAB code to get information about the size distributions and textural information of the granular product. The size distribution data will be used to determine the kinetics of the granulation process and correlations of the size distribution to the changes in the acoustic signal will be investigated. Appropriate computational models to understand key multiphase flow physics will be developed. The models will be used to simulate and to interpret influence of key design and operating parameters on quality of granulated products. Some aspects of drying will be included in this investigations to relate the work on final product quality. Drying kinetics of the granulated materials will be investigated in conjunction with the textural properties. The developed approach, methods, models and results will be useful to develop improved granulation and drying equipment and processes. The work will be immensely useful to pharmaceutical and other speciality industries.