Light sensors that act like pixels in a digital camera have been created by scientists at the University of Toronto. The sensors benefit from a phenomenon known as multi-exciton generation (MEG). Until now, no group had collected an electrical current from a device that takes advantage of MEG. According to the group, this discovery could lead to advancements in the performance of a variety of electronic devices, including digital cameras. The paper appears in the June 19 edition of the journal Science. Researchers created a light sensor – like a pixel in a digital camera – that benefits from a phenomenon known as multi-exciton generation (MEG). Until now, no group had collected an electrical current from a device that takes advantage of MEG. "Digital cameras are now universal, but they suffer from a major limitation: they take poor pictures under dim light. One reason for this is that the image sensor chips inside cameras collect, at most, one electron's worth of current for every photon (particle of light) that strikes the pixel," says Ted Sargent, professor in U of T's Department of Electrical and Computer Engineering. "Instead generating multiple excitons per photon could ultimately lead to better low-light pictures." In solar cells and digital cameras, particles of light - photons - are absorbed in a semiconductor, such as silicon, and generate excited electrons, or excitons. The semiconductor chip then measures a current that flows as a result. Normally, each photon is converted into at most one exciton. This lowers the efficiency of solar cells and it limits the sensitivity of digital cameras. When a scene is dimly lit, small portable cameras like those in laptops suffer from noise and grainy images as a result of the small number excitons. "Multi-exciton generation breaks the conventional rules that bind traditional semiconductor devices," says Sargent. "This finding shows that it's more than a fascinating concept: the tangible benefits of multiple excitons can be seen in a light sensor's measured current." The research was supported by grants from the King Abdullah University of Science and Technology, the Natural Sciences and Engineering Research Council of Canada, the Canada Research Chairs, and the Canada Foundation for Innovation and the Ontario Innovation Trust. For more information, visit: www.utoronto.ca