A Novel Optimizing Method for the Structural Parameters of High-Temperature Thin-Film Heat Flux Sensors Based on Thermo- Mechanical-Electrical Coupled Model

材料科学 薄膜 温度测量 焊剂(冶金) 热流密度 电子工程 机械工程 光电子学 传热 工程类 机械 热力学 纳米技术 物理 冶金
作者
Fan Li,Yonghai Wang,Haiming Huang,Yugang Yin,Jinglai Zheng,Xinchao Qiu
出处
期刊:IEEE Sensors Journal [IEEE Sensors Council]
卷期号:25 (13): 25848-25860 被引量:2
标识
DOI:10.1109/jsen.2025.3573215
摘要

High-sensitivity thin-film heat flux sensors with microsecond-level response capabilities are urgently required for advanced thermal management in aerospace and nuclear power systems, yet their operational reliability under extreme high-temperature conditions (>1700K) remains a persistent technical bottleneck. This study presents an innovative multi-physics optimization framework combining thermo-mechanical-electrical coupling analysis with three-dimensional micro/nanoscale finite element simulations. Through orthogonal experimental design and interaction regression modeling, we systematically investigated the coupled effects of four critical structural parameters: substrate, thermal resistance layer, thermopile layer, and protective layer thicknesses. Key findings reveal that increasing the substrate thickness from 0.5 mm to 2.5 mm resulted in a 17.6% reduction in peak temperature (from 1700 K to 1400 K), but led to a 39% decrease in output potential. In contrast, thickening the thermal resistance layer from 1μm to 3μm improved output potential by 56% (to 38μV) at the expense of doubling the response time (from 4μs to 8μs). Mechanically, thicker substrates and protective layers dispersed stress (40% stress reduction at 2.5mm substrate thickness), while excessive thermopile layer thickness (>0.4μm) induced localized stress concentration. The optimal configuration (substrate: 2.5mm, thermal resistance: 1.5μm, thermopile layer: 0.4μm, protective layer: 1μm) achieved a 273% performance improvement over the traditional design, balancing rapid response, high output potential, and low stress. This work establishes a dual-objective optimization paradigm resolving the inherent conflict between sensor sensitivity and structural reliability, particularly under transient thermal loads exceeding 1700K. The proposed methodology provides critical insights for next-generation sensor design in extreme thermal environments.
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