Â鶹ÒùÔº

International Iberian Nanotechnology Laboratory (INL) researchers have developed a neuromorphic photonic semiconductor neuron capable of processing optical information through self-sustained oscillations. Exploring the use of light to control negative differential resistance (NDR) in a micropillar quantum resonant tunneling diode (RTD), the research indicates that this approach could lead to highly efficient light-driven neuromorphic computing systems.

Neuromorphic computing seeks to replicate the information-processing capabilities of biological neural networks. Neurons in biological systems rely on rhythmic burst firing for sensory encoding, pattern recognition, and network synchronization, functions that depend on oscillatory activity for signal transmission and processing.

Existing neuromorphic approaches replicate these processes using electrical, mechanical, or thermal stimuli, but optical-based systems offer advantages in speed, energy efficiency, and miniaturization. While previous research has demonstrated photonic synapses and artificial afferent nerves, these implementations require additional circuits that increase power consumption and complexity.

While previous neuromorphic photonic neurons have been demonstrated, this study uniquely integrates both sensory reception and oscillatory behavior within a single III-V semiconductor device using light-induced NDR, eliminating the need for external components.

In the study, "Light-induced negative differential resistance and neural oscillations in neuromorphic photonic semiconductor micropillar sensory neurons," in Scientific Reports, researchers developed and tested micropillar RTD photodetectors to investigate their ability to function as artificial oscillatory neurons activated by near-infrared light.

Researchers designed and fabricated n-type gallium arsenide micropillar RTD photodetectors with diameters ranging from 6 to 10 micrometers. These devices feature double barrier quantum well layers, which facilitate quantum resonant tunneling, producing a distinctive electrical response where, as voltage increases, current first rises, then drops, and then rises again. This NDR behavior emerges when the device is exposed to near-infrared light.

Testing involved characterizing the current-voltage response of the devices under both dark and illuminated conditions. Near-infrared light at 830 nanometers was delivered via a laser diode, and the electrical output was measured to determine the conditions under which oscillations occurred. Researchers also tested pulse-modulated light inputs to explore how different illumination intensities influenced excitatory and inhibitory responses.

Under dark conditions, the micropillar RTD devices displayed only positive differential resistance with no self-sustained oscillations. When exposed to controlled levels of near-infrared light, a light-induced NDR region emerged, leading to the generation of self-sustained voltage oscillations.

Observations revealed that burst firing oscillations could be activated or suppressed by modulating the input optical power. At optimal light intensities, the device exhibited stable, periodic burst oscillations, resembling the oscillatory activity observed in biological neurons. These oscillations occurred at frequencies around 350 kilohertz and were tunable based on bias voltage and illumination conditions.

Devices exhibited stable oscillatory behavior over prolonged measurement cycles (>10³ cycles), confirming reliable operation under controlled conditions. Pulse-modulated illumination enabled control over excitation and inhibition of burst firing, demonstrating the feasibility of encoding sensory input into spatiotemporal neural-like signals.

Findings confirm that neuromorphic photonic neurons can be realized using light-activated RTDs, merging sensory input processing and oscillatory neural computation within a single miniaturized semiconductor device.

This research provides an important bridge to high-speed, energy-efficient artificial vision systems and neuromorphic edge computing applications. The compatibility of these III-V semiconductor devices with existing light detection and ranging (LiDAR) and 3D sensing technologies positions them as promising candidates for next-generation bio-inspired computing.

© 2025 Science X Network