2024 : 5 : 28
Majid Sanaeepur

Majid Sanaeepur

Academic rank: Assistant Professor
ORCID: https://orcid.org/0000-0001-8818-2897
Education: PhD.
ScopusId: 35796193100
Faculty: Engineering
Address: Arak University
Phone: 086-32625628


Carbon nanofiber-reinforced Pt thin film-based airflow sensor for respiratory monitoring
Respiratory sensors Piezoresistive sensors Finite-element simulation Carbon reinforcement-based sensors Platinum thin films Laser Doppler Vibrometry
Journal Sensors and Actuators A: Physical
Researchers Sajad Abolpour Moshizi ، Abolfazl Abedi ، Christopher Pastras ، Shuying Wu ، Majid Sanaeepur ، Mohsen Asadnia ، shuhua peng


Recognizing abnormal respiratory patterns is vital for detecting emergency signs or symptoms for diagnosing disease and dysfunction. This paper suggests design and fabrication of a novel airflow sensor based on platinum (Pt) thin films reinforced by carbon nanofibers (CNFs). The conductive Pt thin films were supported by polydimethylsiloxane (PDMS), which endows the sensors with great bendability and ultrahigh sensitivity. CNFs bridge and deflect the microcracks formed in Pt thin film when subjected to external stress, resulting in increased piezoresistive properties. The Pi-shaped air flow sensor was subjected to various airflow rates to study the sensor performance including sensitivity, response time, and recovery time. The results indicate the sensor possesses high sensitivity (27.6 mV (m/s)-1) and low response time (> 0.6 s) with a low-velocity threshold of 15 L min-1 or 0.83 m/s. A finite-element model was developed in COMSOL Multiphysics package to study fluid-solid interactions and piezoresistive effects of the Pt-CNFs/PDMS nanocomposite. Direct measurements of sensor tip displacement were also quantified using single-point laser Doppler vibrometry, which was compared against the numerical simulations. The calibration plot and the numerical results are in good agreement. When compared with previous studies, our airflow sensor showed superior sensing performance in terms of their sensor length, sensitivity, and velocity threshold under various experimental conditions. As a proof of concept, we tested the airflow sensor for monitoring a human respiratory pattern for two extreme conditions, sitting and running.