Micro-LED Embedded Layer-by-Layer Synthesized Conductive Metal-Organic Framework Chemiresistor Arrays

Electrically conductive metal-organic frameworks (cMOFs) are gaining attention as chemiresistive gas sensors due to their flexible catalytic properties and well-structured meso-/micro-porosity, which allows for tunable gas selectivity and diffusion. Despite their potential, room-temperature operation of cMOFs has been limited by insufficient activation, keeping most demonstrations at the proof-of-concept stage. To overcome this, we developed a solution-processed, layer-by-layer (LBL) synthesis approach to fabricate highly sensitive Cu₃HHTP₂ based cMOF thin films and integrate them onto an ultra-low power micro-LED (μLED) platform for photoactivated gas sensing. The solution-based LBL method allows precise control over cMOF thickness and morphology, enabling fine-tuning of deposited layers and catalytic overlayers to enhance gas reactivity. The relationship between cMOF film thickness and its gas adsorption properties was carefully studied, leading to the design of cMOF arrays tailored for four analytes such as ethanol, trimethylamine (TMA), ammonia, and nitrogen dioxide (NO₂). Following the integration of cMOFs onto the μLEDs, the light intensity of the μLEDs was carefully optimized for each cMOF film, facilitating the generation of charge carriers to enhance gas molecule interactions. This led to significant improvements in sensitivity, particularly for gases such as ethanol and TMA. Furthermore, the system addressed challenges in reversible NO₂ sensing by overcoming issues with irreversible adsorption, a common limitation in traditional room-temperature gas sensors.
The resulting sensor array, composed of four distinct cMOF-based sensors, demonstrated impressive energy efficiency, consuming a total power of only 587 µW. The sensor platform was also paired with a convolutional neural network (CNN)-based deep learning algorithm, enabling rapid gas classification with 99.8% accuracy and a regression error of just 7.94% for concentration prediction. Real-time detection was achieved within seconds, demonstrating the practical applicability of this system in dynamic environments.
This work highlights the scalability of solution-processed cMOF sensors integrated with μLED platforms, proving the feasibility of producing energy-efficient, high-performance gas sensing devices at room temperature. The systematic LBL synthesis method not only enhances the material's functionality but also allows for versatile adaptation across different gas sensing needs. This integrated approach paves the way for next-generation gas sensors that combine the benefits of low power consumption, high sensitivity, and real-time detection, making them suitable for a broad range of applications in internet of things (IoT), environmental monitoring, and beyond.