Infrared In-Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays

Area of Science:

• Materials Science
• Nanotechnology
• Solid State Physics

Background:

• Traditional von Neumann architectures limit Internet of Things (IoT) development.
• Near- or in-sensor computing with imaging sensors offers a promising alternative.
• Exploring novel materials and architectures is crucial for next-generation computing.

Purpose of the Study:

• Investigate multi-scale van der Waals (vdWs) interactions in 1D tellurium (Te) atomic chains.
• Develop a photothermoelectric (PTE) Te nanomesh for in-sensor computing applications.
• Demonstrate the potential of Te nanomesh in edge computing and infrared image sensing.

Main Methods:

• Exploration of vdWs interactions in 1D Te atomic chains.
• Deposition of a PTE Te nanomesh on a polyimide substrate via lateral vapor growth.
• Characterization of electrical and mechanical properties, including PTE responsivity.
• Investigation of thermal-coupled bi-directional photoresponse for convolutional network demonstration.

Main Results:

• Successful deposition of a well-connected Te nanomesh with robust properties.
• Achieved a PTE responsivity of approximately 120 V/W in the infrared regime.
• Demonstrated a proof-of-principle in-sensor convolutional network for edge computing.
• Established a scalable approach for assembling functional vdWs Te nanomesh.

Conclusions:

• vdWs Te nanomesh is a viable material for advanced imaging sensors and edge computing.
• The developed PTE nanomesh offers a promising solution for IoT limitations.
• This work highlights the potential of Te nanomesh in PTE image sensing and convolutional processing.