High-temperature-resistance flexible piezoelectric sensor via cyclized PAN/BTO nanofibers

IF 17.1 1区 材料科学 Q1 CHEMISTRY, PHYSICAL Nano Energy Pub Date : 2025-06-01 Epub Date: 2025-03-24 DOI:10.1016/j.nanoen.2025.110910
Tingting Zhou , Shenglong Wang , Yong Ao , Boling Lan , Yue Sun , Guo Tian , Tao Yang , Longchao Huang , Long Jin , Lihua Tang , Weiqing Yang , Weili Deng
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Abstract

Maintaining stable sensing performance in extreme environments, such as high temperatures, is critical for accurate signal monitoring. Conventional rigid sensors fail to fit on uneven surfaces and polymer-based piezoelectric sensors degrade at elevated temperatures, restricting their utilization in harsh environments. Herein, we design a flexible and high-temperature-resistant piezoelectric sensor based on cyclized polyacrylonitrile (PAN) and barium titanate (BTO) nanoparticles. Computational and experimental results indicate that the integration of BTO into the PAN matrix increases the interfacial dipole interactions and raises the activation energy of the PAN cyclization reaction (Ea = 221.63 kJ/mol). As a result, the developed sensor exhibits a broad operating temperature range (room temp. to 500 °C), an improved piezoelectric performance (d33 = 41.5 pC/N), a remarkable frequency response (500 Hz), and an excellent flame-retardant property (LOI = 40 %). Supported by machine learning algorithms, the PAN/BTO fiber-based monitoring system achieves accurate fault diagnosis in high-temperature mechanical vibration scenarios, with an impressive accuracy of 96 %. This innovative approach paves the way for designing unique high-temperature-resistant materials and flexible piezoelectric sensors for real-time sensing under harsh conditions.

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环化PAN/BTO纳米纤维耐高温柔性压电传感器
在极端环境(如高温)中保持稳定的传感性能对于精确的信号监测至关重要。传统的刚性传感器无法适应不平整的表面,聚合物压电传感器在高温下会降解,限制了它们在恶劣环境中的应用。本文设计了一种基于环化聚丙烯腈(PAN)和钛酸钡(BTO)纳米颗粒的柔性耐高温压电传感器。计算和实验结果表明,BTO在PAN基体中的加入增加了界面偶极相互作用,提高了PAN环化反应的活化能(EaEa = 221.63 kJ/mol)。因此,所开发的传感器具有较宽的工作温度范围(室温至500°C),改进的压电性能(d33d33 = 41.5 pC/N),显著的频率响应(500 Hz)和优异的阻燃性能(LOILOI = 40%)。在机器学习算法的支持下,基于PAN/BTO光纤的监测系统在高温机械振动场景下实现了准确的故障诊断,准确率高达96%。这种创新的方法为设计独特的耐高温材料和柔性压电传感器铺平了道路,可以在恶劣条件下进行实时传感。
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来源期刊
Nano Energy
Nano Energy CHEMISTRY, PHYSICAL-NANOSCIENCE & NANOTECHNOLOGY
CiteScore
30.30
自引率
7.40%
发文量
1207
审稿时长
23 days
期刊介绍: Nano Energy is a multidisciplinary, rapid-publication forum of original peer-reviewed contributions on the science and engineering of nanomaterials and nanodevices used in all forms of energy harvesting, conversion, storage, utilization and policy. Through its mixture of articles, reviews, communications, research news, and information on key developments, Nano Energy provides a comprehensive coverage of this exciting and dynamic field which joins nanoscience and nanotechnology with energy science. The journal is relevant to all those who are interested in nanomaterials solutions to the energy problem. Nano Energy publishes original experimental and theoretical research on all aspects of energy-related research which utilizes nanomaterials and nanotechnology. Manuscripts of four types are considered: review articles which inform readers of the latest research and advances in energy science; rapid communications which feature exciting research breakthroughs in the field; full-length articles which report comprehensive research developments; and news and opinions which comment on topical issues or express views on the developments in related fields.
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