Photonic computing is expected to provide alter­natives to traditional electronic approaches. Such systems could be faster, consume less energy and compute visual information more effi­ciently through simultaneous, parallel processing. To date, photonic computing has faced a limitation in achieving nonlinear responses, which means producing signals not directly proportional to the input. Nonlinearity makes universal computing applications, including artificial intelli­gence, possible.

Nonlinear materials and devices under development need a substantial amount of light to work. Previously, this required high-powered lasers that operate only in a narrow band of the electromagnetic spectrum; absorbing light over time, making processing slow; or using energy-inefficient materials that take in lots of light but preclude applications that require light efficiency or transparency. Now, a recent collaborative study from members of the California Nano­Systems Institute at University of California, Los Angeles UCLA, or CNSI, has introduced a device that overcomes these hurdles.

In a major step toward optical computing for processing visual information, the investigators showed that a tiny array of transparent pixels could produce a fast, broadband, nonlinear response from low-power ambient light. The team also demonstrated an application that combines their device with a smartphone camera to reduce glare in images. “Optical non­linearities are far behind what we need for visual computing appli­cations,” said Aydogan Ozcan. “We need low-power, broadband, low-loss and fast nonlinearities for optical systems to meet our visual computing needs. This work helps fill that gap.”

Potential applications for the techno­logy – beyond the glare reduction validated in the study – cross a variety of consumer and industrial uses: improved sensing for autonomous vehicles; cameras that recognize certain objects while hiding others; image encryption; and efficient, effective detection of defects in robotic assembly lines, among many others.

The device could offer many advantages. For example, the incoming images could be processed without conversion to a digital signal, speeding results and reducing the amount of data being sent to the cloud for digital processing and storage. The researchers envision linking their technology with cheap cameras and compressing data to produce images with vastly higher resolution than was realized before, and more precisely and accurately capturing useful information about the arrangement of objects in space and the electro­magnetic spectra present in the light. “An inexpensive device measuring a couple of centimeters could make a low-powered camera work like a super-resolution camera,” said Ozcan. “That would democratize access to high-resolution imaging and sensing.”

The device in the study is a transparent plane measuring one centimeter square. It uses a 2D semiconductor material that was developed by Xiangfeng Duan from the UCLA College. The thinness of the material makes it transparent, while it retains qualities that enable incoming photons to effi­ciently regulate electrical conductivity. The research team coupled the 2D semi­conductor with a layer of liquid crystal and made it functional with an array of electrodes. The result is a smart filter comprising 10,000 pixels, each able to selectively and quickly darken in a nonlinear way when exposed to broadband ambient light.

“Basically, we want to use a material that does not absorb a lot of light, but still produces sufficient signal that can be used to process the light,” Duan said. “Each pixel can change from completely transparent to partially transparent to opaque. It only takes a small number of photons to change the transparency dramatically.” (Source: UCLA)

Reference: D. Zhang et al.: Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array, Nat. Commun. 15, 2433 (2024); DOI: 10.1038/s41467-024-46387-5

Link: California NanoSystems Institute (CNSI), University of California, Los Angeles, USA