Experimental study demonstrates multiphysics signal decoupling in an integrated graphene platform, reducing airflow sensing errors below 5% and indicating a path for reliable wearable devices.
Airflow sensing underpins applications in environmental monitoring, industrial safety, and wearable health care. Piezoresistive airflow sensors offer a compact and energy-efficient solution, yet their accuracy is severely compromised by complex multiphysical field perturbations. Here, we report an integrated graphene-based system fabricated by in situ laser printing that simultaneously measures airflow, temperature, and humidity. We reveal that a standalone piezoresistive airflow sensor can incur substantial errors exceeding 100% under fluctuating environmental conditions. Through targeted surface functionalization and microstructural engineering, we develop a humidity-insensitive temperature sensor, a high-fidelity humidity sensor, and a piezoresistive airflow sensor. Integrating these components into a multiphysics decoupling model enables analytical separation of intertwined signals, markedly reducing airflow measurement errors to below 5%. The optimized platform achieves high-precision, low power consumption, and strong integration airflow sensing with stable output under real-time fluctuations. These capabilities further allow dual-parameter airflow communication, while the scalable, mask-free laser-printing process provides a pathway toward portable, multifunctional sensing systems.
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Li et al. (2026) studied this question.
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