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Optrode Array for Simultaneous Optogenetic Modulation and Electrical Neural Recording

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Photonic-Mediated Neuromorphic Computing Enabled by a Copper Oxide Microcrystal Optoelectronic Synapse.

Semyon Bachinin¹, Maria Timofeeva¹, Alexandra Gavrilova¹

¹School of Physics and Engineering, ITMO University, St. Petersburg 197101, Russia.

ACS Applied Materials & Interfaces

|August 11, 2025

Summary

Researchers developed a novel copper oxide microcrystal optical synapse for photonic neuromorphic computing. This breakthrough enables fast, energy-efficient, and autonomous data processing with high accuracy and endurance.

Keywords:

handwritten digit recognition neuromorphic computing optical synapse optoelectronic device semiconducting microcrystal

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Area of Science:

Optoelectronics
Neuromorphic Engineering
Materials Science

Background:

Photonic neuromorphic computing promises faster, more energy-efficient data processing than electronic systems.
Designing active materials for efficient photonic neuromorphic devices remains a significant challenge.

Purpose of the Study:

To demonstrate a novel copper oxide microcrystal optical synapse for enhanced photonic neuromorphic computing.
To investigate the neuromorphic behavior and performance metrics of the developed optical synapse.

Main Methods:

Optically pumping a single copper oxide microcrystal with 2.3 eV photons.
Controlling the history-dependent photoexcited electron response (spike) by adjusting the pumping repetition rate.
Evaluating performance metrics including spike response time, on/off ratio, endurance, and accuracy in handwritten digit recognition.

Main Results:

Observed a history-dependent photoexcited electron response (spike) with a 1 ms response time.
Achieved a 10^2 on/off ratio and exceptional endurance over 13,400 cycles.
Demonstrated 95% accuracy in handwritten digit recognition within three training epochs.

Conclusions:

The copper oxide microcrystal optical synapse offers efficient, fast, and highly enhanced photonic neuromorphic computing.
This novel device surpasses existing designs, paving the way for efficient and long-lasting photonic neuromorphic data processing.