约束环境中高温传感的温度响应微型机器人。

IF 10.7 1区 综合性期刊 Q1 Multidisciplinary
Research Pub Date : 2025-07-04 eCollection Date: 2025-01-01 DOI:10.34133/research.0760
Shaobo Ding, Junmin Liu, Jiaxu Dong, Rencheng Zhuang, Enbo Shi, Shutong Wang, Yuhang Xiao, Dekai Zhou, Longqiu Li, Xiaocong Chang
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引用次数: 0

摘要

长期以来,密闭环境中的温度测量一直是一个重大挑战。由于空间受限、能见度低,传统的测温仪和现有的纳米尺度测温仪难以实现高效、准确的温度检测。作为一项新兴技术,微型机器人在如此具有挑战性的条件下提供了巨大的温度传感潜力。在这里,我们提出了一种温度响应微机器人(TRM),它将人工神经网络集成到微尺度热传感中,能够在复杂和受限的环境中进行定量温度测量。TRM在160 - 240°C的高温范围内发生不可逆的颜色变化。它具有由Cu(NH3) 4so4基热致变色材料和镍涂层磁致动层组成的Janus结构,可在多孔地质结构和受限微空间等非透明和几何受限环境中可靠运行。系统地研究了TRM在高温下的热致变色机理和运动动力学。该微型机器人在不同温度下表现出不同的色响应。基于色度与温度的相关性,建立了多层感知器神经网络。通过将观察到的颜色特征输入到训练好的模型中,可以定量地确定周围的温度。模拟多孔微通道模型的实验结果证实了TRM局部高温检测的可行性和有效性。这项工作为限制环境下的温度传感提供了一种新的解决方案,为微型机器人在工业高温监测中的应用奠定了坚实的基础,突出了它们在复杂条件下的实际部署潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Temperature-Responsive Microrobot for High-Temperature Sensing in Constrained Environments.

Temperature measurement in confined environments has long been a substantial challenge. Due to poor accessibility to constrained space, and low visibility, conventional thermometry and existing nanoscale thermometers struggle to achieve efficient and accurate temperature detection. As an emerging technology, microrobots offer great potential for temperature sensing in such challenging conditions. Here, we propose a temperature-responsive microrobot (TRM) that integrates artificial neural networks into microscale thermal sensing, enabling quantitative temperature measurement in complex and constrained environments. The TRM undergoes irreversible color changes in a high-temperature range of 160 to 240 °C. It features a Janus structure composed of a Cu(NH3)4SO4-based thermochromic material and a nickel-coated magnetic actuation layer, allowing reliable operation in nontransparent and geometrically confined environments such as porous geological structures and constrained microspaces. The thermochromic mechanism and motion dynamics of the TRM under elevated temperatures were systematically investigated. The microrobot exhibits distinct chromatic responses at different temperatures. Based on the correlation between chromaticity and temperature, a multilayer perceptron neural network was developed. By inputting the observed color features into the trained model, the surrounding temperature can be quantitatively determined. Experimental results in a simulated porous microchannel model confirmed the feasibility and effectiveness of the TRM for localized high-temperature detection. This work provides a new solution for temperature sensing in restricted environments and lays a solid foundation for the application of microrobots in industrial high-temperature monitoring, highlighting their potential for real-world deployment in complex conditions.

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来源期刊
Research
Research Multidisciplinary-Multidisciplinary
CiteScore
13.40
自引率
3.60%
发文量
0
审稿时长
14 weeks
期刊介绍: Research serves as a global platform for academic exchange, collaboration, and technological advancements. This journal welcomes high-quality research contributions from any domain, with open arms to authors from around the globe. Comprising fundamental research in the life and physical sciences, Research also highlights significant findings and issues in engineering and applied science. The journal proudly features original research articles, reviews, perspectives, and editorials, fostering a diverse and dynamic scholarly environment.
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