Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

CNN-Optimized Electrospun TPE/PVDF Nanofiber Membranes for Enhanced Temperature and Pressure Sensing

Version 1 : Received: 22 July 2024 / Approved: 23 July 2024 / Online: 23 July 2024 (12:29:03 CEST)

How to cite: Ma, M.; Jin, C.; Yao, S. F.; Li, N.; Zhou, H. C.; Dai, Z. CNN-Optimized Electrospun TPE/PVDF Nanofiber Membranes for Enhanced Temperature and Pressure Sensing. Preprints 2024, 2024071800. https://doi.org/10.20944/preprints202407.1800.v1 Ma, M.; Jin, C.; Yao, S. F.; Li, N.; Zhou, H. C.; Dai, Z. CNN-Optimized Electrospun TPE/PVDF Nanofiber Membranes for Enhanced Temperature and Pressure Sensing. Preprints 2024, 2024071800. https://doi.org/10.20944/preprints202407.1800.v1

Abstract

Temperature and pressure sensors currently encounter challenges such as slow response times, large sizes, and insufficient sensitivity. To address these issues, we developed tetraphenylethylene (TPE)-doped polyvinylidene fluoride (PVDF) nanofiber membranes using electrospinning, with process parameters optimized through a convolutional neural network (CNN). We systematically analyzed the effects of PVDF concentration, spinning voltage, tip-to-collector distance, and flow rate on fiber morphology and diameter. The CNN model achieved high predictive accuracy, resulting in uniform and smooth nanofibers under optimal conditions. Incorporating TPE enhanced the hydrophobicity and mechanical properties of the nanofibers. Additionally, the fluorescent properties of the TPE-doped nanofibers remained stable under UV exposure and exhibited significant linear responses to temperature and pressure variations. The nanofibers demonstrated a temperature sensitivity of -0.976 gray value/°C and pressure sensitivity with an increase in fluorescence intensity from 537 a.u. to 649 a.u. under 600 g pressure. These findings highlight the potential of TPE-doped PVDF nanofiber membranes for advanced temperature and pressure sensing applications.

Keywords

Electrospinning; PVDF nanofiber membranes; Convolutional neural network; Tetraphenylethylene; Temperature/pressure-sensitive fluorescence

Subject

Chemistry and Materials Science, Materials Science and Technology

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