Flexible temperature-pressure bimodal sensing arrays can detect multiple types of information, including force and heat, making them crucial for applications such as object classification, human-machine interaction, and artificial intelligence. However, current sensors primarily focus on single-parameter and single-point measurements, while lacking a continuous and stable power supply. This study developed flexible, self-powered temperature-pressure sensing arrays by integrating a stepped microcone structure with thermoelectric materials. This stepped distribution microstructure design enabled effective pressure measurements across a wide range, with high sensitivity and fast response. Temperature-independent measurements were achieved synchronously over a wide temperature range (35–173 °C) by incorporating high-performance Bi2Te3-based thermoelectric films. These temperature and pressure sensing units can discern temperature and pressure stimuli without mutual interference. Furthermore, with the assistance of deep learning, these bimodal sensing arrays performed spatial mapping of temperature and pressure simultaneously, demonstrating their ability to identify different types of objects with an accuracy exceeding 98 %. Therefore, this study shows promise for advancing human-machine interaction, artificial intelligence, and self-powered electronic skins.

中文翻译：

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具有阶梯式微锥结构和基于 Bi2Te3 的薄膜的自供电温度压力传感阵列，用于深度学习辅助对象识别


灵活的温度-压力双峰传感阵列可以检测多种类型的信息，包括力和热量，这使得它们对于物体分类、人机交互和人工智能等应用至关重要。然而，电流传感器主要侧重于单参数和单点测量，而缺乏连续稳定的电源。本研究通过将阶梯式微锥结构与热电材料集成，开发了灵活的自供电温度-压力传感阵列。这种阶梯式分布微观结构设计能够在很宽的范围内进行有效的压力测量，具有高灵敏度和快速响应。通过结合基于 Bi2Te3 的高性能热电薄膜，在较宽的温度范围 （35–173 °C） 内同步实现不受温度影响的测量。这些温度和压力传感单元可以识别温度和压力刺激，而不会相互干扰。此外，在深度学习的帮助下，这些双峰传感阵列同时执行温度和压力的空间映射，展示了它们识别不同类型物体的能力，准确率超过 98%。因此，这项研究显示出推进人机交互、人工智能和自供电电子皮肤的前景。