Twisting van der Waals Heterostructures Enables Thermographic In-Sensor Computing and Logics

Area of Science:

• Materials Science
• Nanotechnology
• Biophysics

Background:

• In-sensor computing is crucial for machine vision but faces challenges in thermal applications.
• Developing sensitive thermal perception is key for advanced imaging and intelligent systems.

Purpose of the Study:

• To present a bioinspired thermoreceptor array based on twisted graphene and titanium diselenide heterostructures.
• To demonstrate the potential for in-sensor computing and logic operations in thermal imaging.

Main Methods:

• Fabrication of twisted graphene and few-layer titanium diselenide (TiSe2) heterostructures.
• Characterization of twist-angle dependent electron-phonon interactions and thermal reception.
• Integration into a (64 × 64) thermoperception array with a convolutional neural network (CNN) framework.

Main Results:

• Demonstrated twist-angle dependent phonon-induced gap in graphene, enabling thermal reception from 20 to 350 K.
• Achieved 46% enhancement in thermal image detection accuracy and 99% classification accuracy for pathological cells.
• Successfully demonstrated "AND", "OR", and "AND/OR" logic operations using the thermoreceptor arrays.

Conclusions:

• The developed thermoreceptor array offers sensitive thermal reception and in-sensor computing capabilities.
• This technology simplifies machine vision architecture and provides a pathway for next-generation intelligent systems.
• The bioinspired design and demonstrated logic operations pave the way for advanced thermal sensing applications.