The Engineer

Scene recognition is one of the visual perception capabilities of digital image sensors developed at King Abdullah University of Science and Technology (KAUST).

Exploiting charge-coupled device (CCD) image sensors found in early digital cameras, Dayanand Kumar, Nazek El-Atab and colleagues have adapted and enhanced the CCD's core structure to create memory devices that can be programmed by light. In particular, the research team embedded the two-dimensional material MoS2 (molybdenum disulphide) into a semiconductor capacitor (MOSCAP) structure that underpins the charge-storing pixels of a CCD sensor.

The resulting Al/Al2O3/MoS2/Al2O3/Si MOSCAP structures are claimed to function as a charge-trapping ‘in-memory’ sensor that is sensitive to visible light and can be programmed optically and erased electrically.

"The in-memory light sensors are smart multifunctional memory devices that can perform the roles of multiple - traditionally discrete - devices at once, including optical sensing, storage and computation," El-Atab said in a statement. "Our long-term goal is to be able to demonstrate in-memory sensors that can detect different stimuli and compute."

El-Atab continued: "This overcomes the memory wall and allows for faster and more real-time data analysis using reduced power consumption, which is a requirement in many futuristic and…applications such as Internet of Things, autonomous cars and artificial intelligence, among others."

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According to KAUST, experiments with light with a wavelength anywhere in the blue to the red spectral region indicate that a photo-generated charge can be trapped or stored with an extremely long-lived retention time. The resulting ‘memory window’ voltage of >2V can be stored for up to 10 years prior to being electrically erased by applying a +/-6V signal. Moreover, it can be operated for many millions of cycles.

The team's ultimate aim is to create a single optoelectronic device that can perform optical sensing and storage with computing capabilities.

By combining their MoS2 MOSCAP structure with a neural network, the team showed that it was possible to perform simple binary image recognition, distinguishing between images of either a dog or a car, with an accuracy of 91 per cent. Each image was 32×32 pixels in size, and only the blue information from the images was extracted since that corresponds to the device's peak sensitivity.

"Current memory devices can be programmed optically but require erasing electrically," said Kumar. "In the future, we would like to explore in-memory optical sensors that can be fully optically operated."

The team's findings have been detailed in Light: Science & Applications.