A team from the University of California Los Angeles (UCLA) and the California NanoSystems Institute designed an optoelectronic neuron array device to allow nonlinear transmission of spatially incoherent light (see video).
“Nonlinear optical processing of ambient natural light is highly desired for computational imaging and sensing,” says Aydogan Ozcan, a professor of electrical and computer engineering and bioengineering and Volgenau Chair for Engineering Innovation with UCLA’s Samueli School of Engineering, who led this work alongside Xiangfeng Duan, a professor in the UCLA Department of Chemistry and Biochemistry.
The novel neuron array prompted “a large nonlinear contrast over a broad spectrum at orders-of-magnitude lower intensity than is achievable in most optical nonlinear materials,” Ozcan adds.
Experimenting with optoelectronic neurons
The team merged 2D transparent phototransistors (TPTs) with liquid crystal (LC) modulators to create a 10,000-pixel optoelectronic neuron array (see Fig. 1).
Under low-light illumination, the TPT—on which most of the voltage drop occurs—was found to be highly resistive. The LC, on the other hand, was unperturbed and remained transmissive. At high input optical power, however, the TPT became conductive and most of the voltage drops across the LC layer instead, which shuts off the optical transmission.
But the optoelectronic neurons allowed spatially and temporally incoherent light in the visible wavelengths to nonlinearly modulate its own amplitude with just a 20% photon loss. The array also demonstrated strong nonlinear behavior under laser and white light illumination. Essentially, Ozcan explains, a mini array of transparent pixels was shown to produce a fast, broadband, nonlinear response from low-power ambient light (see Fig. 2).
In further testing, the nonlinear optoelectronic array device was integrated into a cell phone-based imaging system for intelligent glare reduction—an aspect important for various imaging applications, including autonomous driving, machine vision, and security cameras. This selectively blocks intense glare while presenting little attenuation for the weaker-intensity objects within the imaging field of view. Ozcan says the device modeling suggests a very low optical intensity threshold of 56 μW/cm2 to generate a significant nonlinear response, and a low energy consumption of 69 fJ per photonic activation for optimized devices.
Future applications
Aside from intelligent glare reduction, Ozcan says “the cascaded integration of optoelectronic neuron arrays with linear diffractive optical processors could be used to construct nonlinear optical networks.” It could potentially find widespread applications in computational imaging and sensing. It could also open the door to new nonlinear optical processor designs using ambient light.
The rapid nonlinear processing of incoherent broadband light might find applications in optical computing, as well, where nonlinear activation functions for ambient light conditions would be in high demand.
As the optoelectronic neuron array enables nonlinear self-amplitude modulation of spatially incoherent light—featuring a low optical intensity threshold, strong nonlinear contrast, broad spectral response, fast speed, and low photon loss—the device is also an attractive possibility for enhanced image processing and visual computing systems that do not rely on intense laser beams.
What’s next?
“Our team will be exploring various applications stemming from this device architecture, including a variety of consumer and industrial uses,” Ozcan says, citing 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.
Various transformative features for optical computing could also be on the horizon. 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.
“We envision linking our 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,” Ozcan says. “An inexpensive device measuring a couple of centimeters could make a low-powered camera work like a super-resolution camera. That would democratize access to high-resolution imaging and sensing.”
FURTHER READING
D. Zhang et al., Nat. Commun., 15, 2433 (2024); https://doi.org/10.1038/s41467-024-46387-5.
Justine Murphy | Multimedia Director, Digital Infrastructure
Justine Murphy is the multimedia director for Endeavor Business Media's Digital Infrastructure Group. She is a multiple award-winning writer and editor with more 20 years of experience in newspaper publishing as well as public relations, marketing, and communications. For nearly 10 years, she has covered all facets of the optics and photonics industry as an editor, writer, web news anchor, and podcast host for an internationally reaching magazine publishing company. Her work has earned accolades from the New England Press Association as well as the SIIA/Jesse H. Neal Awards. She received a B.A. from the Massachusetts College of Liberal Arts.