Artificial synapse enables near-human colour discrimination
Engineering, Department of Electronic Systems Engineering, Tokyo University of Science (TUS), Japan, has developed a groundbreaking self-powered artificial synapse capable of distinguishing colours with remarkable precision. The study was co-authored by Mr. Hiroaki Komatsu and Ms. Norika Hosoda, also from TUS.
Despite significant progress due to AI and sensors, machine vision systems still face a major challenge in processing the vast amounts of visual data generated every second, which requires substantial power, storage, and computational resources. This makes it difficult to deploy visual recognition capabilities in edge devices such as smartphones, drones, or autonomous vehicles. The artificial synapse developed by the researchers is self-powered, addressing the power limitations inherent in edge applications.
However, unlike conventional machine vision systems, which must capture and process every detail, the human vision system selectively filters information, allowing for higher efficiency in visual processing while consuming minimal power. Neuromorphic computing, which mimics the structure and function of biological neural systems, has thus emerged as a promising approach to overcome existing hurdles in computer vision. However, two major challenges have persisted. The first is achieving colour recognition comparable to human vision, whereas the second is eliminating the need for external power sources to minimize energy consumption.
The researchers integrated two different dye-sensitized solar cells, which respond differently to various wavelengths of light, to create their artificial synapse. Unlike conventional optoelectronic artificial synapses that require external power sources, the proposed synapse generates its electricity via solar energy conversion. This self-powering capability makes it particularly suitable for edge computing applications, where energy efficiency is a crucial requirement.
Extensive experiments have demonstrated that the resulting system can distinguish between colours with a resolution of 10 nanometres across the visible spectrum. This level of discrimination approaches that of the human eye. Furthermore, the device exhibited bipolar responses, producing positive voltage under blue light and negative voltage under red light. This enables the performance of complex logic operations that would typically require multiple conventional devices.
“The results show great potential for the application of this next-generation optoelectronic device, which enables high-resolution colour discrimination and logical operations simultaneously, to low-power AI systems with visual recognition,” notes Dr Ikuno.
To demonstrate a real-world application, the team used the artificial synapse in a physical reservoir computing framework to recognise different human movements recorded in red, green, and blue. The system achieved an impressive 82% accuracy when classifying 18 different combinations of colours and movements using just a single device rather than the multiple photodiodes needed in conventional systems.
The implications of this research extend across multiple industries. For example, in autonomous vehicles, these devices could enable more efficient recognition of traffic lights, road signs, and obstacles. In healthcare, they could power wearable devices that monitor vital signs, such as blood oxygen levels, with minimal battery drain.
“We believe this technology will contribute to the realization of low-power machine vision systems with colour discrimination capabilities close to those of the human eye, with applications in optical sensors for self-driving cars, low-power biometric sensors for medical use, and portable recognition devices,” remarks Dr Ikuno.
https://doi.org/10.1038/s41598-025-00693-0
If you enjoyed this article, you will like the following ones: don't miss them by subscribing to :
