Using Electronic Noses (ENoses) in brewery and distillation processes

These projects are open to students worldwide, but have no funding attached. Therefore, the successful applicant will be expected to fund tuition fees at the relevant level (home or international) and any applicable additional research costs. Please consider this before applying.

This project is on developing Electronic-Nose (ENose) technology in collaboration with a spin-out company from the University of Aberdeen called ScensAi. Just like a human nose, ENoses use many individual sensors and neural nets to interpret the sensor signals into identifying compounds. What makes the ScensAi ENose unique is that it can quantitatively identify a wide range of gases and vapors in seconds thanks to detailed chemical kinetic modelling for the surface chemistry of the sensors. This chemical modelling forms a normalization layer under our machine learning making it easy to transfer training from one ENose to another, to continually add more training, or to adapt to new designs/applications.

There’s many potential uses for ENose technology, from environmental monitoring (where many of the sensors we use come from) to healthcare; however, ScensAi is currently working with local breweries to providing rapid chemical analysis for the distillation and brewing industries. There are many chemicals that affect the quality and safety of produced drinks, from methanol in the distillation process which can cause blindness to butyric acide indicating bacterial contamination of beers. Detecting these “off” flavours is normally the job of the human brewers but our ENose can provide real-time feedback on fermentation process, indicating potential quality issues as they develop allowing rapid intervention, or simply allowing faster brewing cycles by indicating when the batch will complete fermentation.

Depending on the background and interests of the applicant, the PhD project can focus on different aspects of this research. First, our AI models use modern techniques like neuro-differential equations to dynamically predict the environment, and these are coupled with some chemical models describing the interactions on the surface of the sensors. There is a lot of data science in the selection of these models and how to train the model to include new chemical signatures which can be explored with our current datasets and test systems. We need to improve our underlying models to better capture environmental effects or background chemicals on our sensors so this could expand to more detailed chemical modelling. Experimentally we are building automated high-throughput testing systems to generate large datasets for training our models, and the design and development of these can be explored. Finally, our ENose is designed and developed using fluid dynamics to minimize the response times, as well as all of the standard design issues of a consumer electronics device (mechanical design, rapid prototyping through 3D printing, electronic design, design for manufacturing). A PhD project might include several of these aspects and will include appropriate training in these areas. Informal inquiries are encouraged to discuss which areas might be of interest.

Decisions will be based on academic merit. The successful applicant should have, or expect to obtain, a UK Honours Degree at 2.1 (or equivalent) in Engineering, Computing Science, or related disciplines. Sufficient research background and previous experience would be preferred.

Application Procedure:

Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php.

You should apply for PhD in Engineering to ensure your application is passed to the correct team for processing.

Please clearly note the name of the lead supervisor and project titleon the application form. If you do not include these details, it may not be considered for the studentship.

Your application must include: A personal statement, an up-to-date copy of your academic CV, and clear copies of your educational certificates and transcripts.

Please note: you do not need to provide a research proposal with this application.

Informal enquiries can be made by contacting Dr M Bannerman at m.campbellbannerman@abdn.ac.uk. If you require any additional assistance in submitting your application or have any queries about the application process, please don't hesitate to contact us at researchadmissions@abdn.ac.uk

Funding Notes

This is a self-funding project open to students worldwide. Our typical start dates for this programme are February or October.

Fees for this programme can be found here Finance and Funding | Study Here | The University of Aberdeen