Optimisation of Graphene Biosensors for Brain Disease Diagnosis
Project ID: 2228cd1381 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Chemistry
Lead Supervisor: Bing Li
Project Summary:
Why this research is important? Dementia causes severe neurological impairments and presents a huge economic burden to both the individuals and the society. Recently, great progress has been made in the discovery of novel dementia biomarkers using the state-of-the-art technologies. These important biomarkers measured across populations will facilitate early diagnosis of dementia. However, current methods for detecting dementia biomarkers rely on time-consuming laboratory techniques and are expensive. We aim to develop a portable, rapid, reliable, and cost-effective graphene biosensing platform for the accurate analysis of these important biomarkers, with a vision to deploy the technique into clinical settings to benefit the patients.
The advanced biosensing group, led by Dr Li, has 4 PhD students and 2 RAs at UCL. The group is in close collaboration with multiple departments across UCL and Imperial College for the graphene device micro/nanofabrication. Dr Li is also an Emerging Leader in the national UK Dementia Research Institute, which will provide cross-centre access to clinical samples, antibody engineering related facilities, and a national translation-focused neuroscience network.
This project aims to systematically optimise the performance of graphene field effect biosensors, which aligns with the wider group interest in the development of advanced graphene biosensing technology for dementia and brain disease diagnosis. The project objectives include: the micro/nanofabrication of graphene field effect transistors; chemical functionalisation of graphene surface using various linker molecules, study the molecular density of the linker molecules, immobilisation of antibody for biomarker detection, and optimisation of the antibody orientations.
Candidates should have a 1st class (or closely aligned 2:1) degree and strong interest in nanotechnology, analytical chemistry, or biosensing technology, ideally with a Master level degree. Candidate should have wet lab working experience and ability to work as part of a multidisciplinary team.