High-Performance Organic Photodetectors With Synergistic Trap-State Passivation and Interfacial Engineered ZnO...

Area of Science:

• Materials Science
• Organic Electronics
• Sensor Technology

Background:

• Organic photodetectors (OPDs) face challenges from trap-induced dark current and unstable interfaces.
• ZnO electron transport layers (ETLs) are crucial but prone to defects affecting performance.

Purpose of the Study:

• To investigate defect evolution in ZnO ETLs and its impact on OPD performance.
• To enhance OPD stability and detectivity through defect mitigation and interfacial engineering.
• To demonstrate the application of optimized OPDs in wearable, self-powered sensing platforms.

Main Methods:

• Systematic study of ZnO defect evolution, including air aging and light activation.
• Introduction of PDINN interfacial modifier for defect passivation and energy-level alignment.
• Device characterization including specific detectivity, dark current, and response time.
• Integration into a wearable platform and evaluation with a neural network for pulse acquisition.

Main Results:

• A "resting effect" in ZnO ETLs was identified, where aging/activation reduces trap states and energetic disorder.
• Optimized OPDs achieved high specific detectivity (∼8.30 × 10¹³ Jones) with suppressed dark current and microsecond response.
• Performance improvements were consistent across various non-fullerene active layers.
• Wearable self-powered platform demonstrated high-fidelity pulse acquisition (SNR > 25 dB).

Conclusions:

• ZnO defect regulation and PDINN interfacial tuning effectively reduce traps and improve energy-level alignment in OPDs.
• Optimized OPDs exhibit enhanced detectivity, stability, and fast response for sensing applications.
• The developed system enables accurate motion-induced pulse classification (97.14% accuracy) using AI, highlighting potential for advanced wearable health monitoring.