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On-Demand MXene-Coupled Pyroelectricity for Advanced Breathing Sensors and IR Data Receivers.
Gupta, Varun; Mallick, Zinnia; Choudhury, Amitava; Mandal, Dipankar.
  • Gupta V; Quantum Materials and Devices Unit, Institute of Nano Science and Technology, Knowledge City, Sector 81, Mohali 140306, Punjab, India.
  • Mallick Z; Quantum Materials and Devices Unit, Institute of Nano Science and Technology, Knowledge City, Sector 81, Mohali 140306, Punjab, India.
  • Choudhury A; Department of Computer Science and Engineering, Pandit Deendayal Energy University, Gandhinagar 382007, Gujarat, India.
  • Mandal D; Quantum Materials and Devices Unit, Institute of Nano Science and Technology, Knowledge City, Sector 81, Mohali 140306, Punjab, India.
Langmuir ; 40(17): 8897-8910, 2024 Apr 30.
Article en En | MEDLINE | ID: mdl-38626396
ABSTRACT
MXene-inspired two-dimensional (2D) materials like Ti3C2Tx are widely known for their versatile properties, including surface plasmon, higher electrical conductivity, exceptional in-plane tensile strength, EMI shielding, and IR thermal properties. The MXene nanosheets coupled poly(vinylidene fluoride) (PVDF) nanofibers with d33 ∼-26 pm V-1 are able to capture the smaller thermal fluctuation due to a superior pyroelectric coefficient of ∼130 nC m-2 K-1 with an improved (∼7 times with respect to neat PVDF nanofibers) pyroelectric current figure of merit (FOMi). The significant enhancement of the pyroelectric response is attributed to the confinement effect of 2D MXene (Ti3C2Tx) nanosheets within PVDF nanofibers, as evidenced from polarized Fourier transform infrared (FTIR) spectroscopy and scanning probe microscopy (SPM). In subsequent studies, the practical applications of self-powered pyroelectric sensors of MXene-PVDF have been demonstrated. The fabricated flexible, hydrophobic pyroelectric sensor could be utilized as an excellent pyroelectric breathing sensor, a proximity sensor, and an IR data transmission receiver. Further, supervised machine learning algorithms are proposed to distinguish different types of breathing signals with ∼98% accuracy for healthcare monitoring purposes.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Año: 2024 Tipo del documento: Article