PbS/CsPbBr₃ Heterojunction for Broadband Neuromorphic Vision Sensing.

Area of Science:

• Materials Science
• Optoelectronics
• Artificial Intelligence

Background:

• Neuromorphic light sensors offer energy efficiency and low latency compared to traditional vision chips.
• Metal halide perovskites show promise for visual sensors due to their light-matter interaction and tunable photoresponsivity via ion migration.
• Achieving wide-spectrum response and tunable responsivity simultaneously in perovskites remains a challenge for enhanced image recognition.

Purpose of the Study:

• To develop a broadband neuromorphic visual sensor with tunable photoresponsivity from visible (Vis) to near-infrared (NIR) spectrum.
• To investigate the effect of ion migration in perovskites within a heterostructure for advanced sensor capabilities.
• To enable machine learning-based image processing, including pattern recognition and edge enhancement, for artificial intelligent vision sensing.

Main Methods:

• Fabrication of a PbS/CsPbBr3 heterostructure using single crystals of PbS and CsPbBr3.
• Application of an electric field to induce ion migration and dynamic energy band bending at the heterojunction interface.
• Testing the sensor's photoresponse across the Vis-to-NIR spectrum and its compatibility with convolutional neural network processing.

Main Results:

• Demonstration of a broadband neuromorphic visual sensor (Vis-to-NIR) by coupling PbS and CsPbBr3.
• Observation of reversible, multilevel, and linearly tunable photoresponsivity due to electric-field-induced ion migration in CsPbBr3.
• Successful implementation of convolutional neural network processing for pattern recognition and edge enhancement using the sensor's reconfigurable broadband response.

Conclusions:

• The PbS/CsPbBr3 heterostructure enables a highly tunable and broadband photoresponse for neuromorphic visual sensing.
• The dynamic energy band bending mechanism facilitates advanced image processing capabilities.
• This heterostructure holds significant potential for developing next-generation artificial intelligent vision systems.