Soft colloidal quantum Wells IMage Sensing (SWIMS)

Lead Research Organisation: CARDIFF UNIVERSITY
Department Name: School of Physics and Astronomy

Abstract

Soft image sensors are expected to take vital roles in our future daily life. They can monitor the physiological information of our body to provide real-time, noninvasive medical diagnostics, as well as capture and share photos, videos via wireless communications. However, current image sensing electronics cannot be integrated easily into humans, because they are made of rigid semiconductor photodetectors and integrated with optical filters for colour discrimination. In addition, the use of filter creates additional requirements on the optical path difference, which confines the foldability and limits the resolution of the detector array. To overcome these technological limitations, filterless foldable photodetectors which only detect light within a specific wavelength have emerged as critical elements for building soft image sensors.

Colloidal quantum dots, metal halide perovskite and organic photodetectors have shown excellent flexibility and detectivity. However, their broad light absorption means filters need to be added to make them specific to a certain colour of light. So far, the most successful filterless model is based on charge collection narrowing (CCN) photodiodes, which are semiconductor devices that convert the specific colour of light into an electrical current. However, since the narrowband response is delivered by controlling photogenerated charge collection efficiency, micrometres thickness junction is often required, which results in an array with a greater likelihood of interpixel cross-talk and frequency bandwidth limitations. It has been demonstrated that the junction thickness can be reduced by using high reflectivity cavities, but a number of challenges still remain. In this research, we aim to tackle these challenges to help find suitable semiconductors that use non-toxic elements and are able to efficiently detect light within a specific wavelength of interest at thicknesses as little as few hundred nanometres. If successful, we would be moving a step closer to an eco-friendly soft image sensor with the potential for many applications.

Among all incarnations of solution-processed semiconductors, the recently discovered two-dimensionally (2D) Colloidal Quantum Wells (CQWs) are highly promising for soft image sensor applications, not only do they offer high colour purity with ultranarrow full-width at half-maximum (FWHM) but they also exhibit excellent compatibility with flexible electronics, such as unique stretching enhanced optical polarisation. Unlike colloidal quantum dots, CQW ensembles have no inhomogeneous broadening due to an atomically-precise definition of the short axis and is the reason why CQWs exhibit the narrowest ensemble absorption and emission spectrum of any solution-processed material reported to date. However, looming over much of this success is the fact that all the reported CQWs include toxic heavy metals (e.g., cadmium and lead), and little progress has been made on the fabrication of non-toxic CQWs or CQW narrowband photodetectors. This proposal is therefore designed to substantially address this challenge by using non-toxic mechanically stretchable 2D solution-processed CQWs for the fabrication of soft image sensors. This proposal starts from the growth and surface functionalisation of non-toxic CQWs followed by predictions of the new cavity and charge transport layers for fast CCN. The proposed work will consider the key factors limiting frequency bandwidth, and will demonstrate the inkjet printing of multi-coloured CCN-based photodiodes in a soft image sensor scenario. The high impact objective of this project is the demonstration of a CQWs image sensor which is stretchable and mechanically conformable. This proposal will be underpinned from the established compound semiconductor research expertise at Cardiff University, in close collaboration with Oxford, Cambridge and Bristol University, TCL Corporate Research, Huawei UK, Glaia, 99P Recycling and Hamamatsu UK.
 
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Funding ID BB/X004449/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 04/2023 
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