Monereo O, Illera S, Varea A, Schmidt M, Sauerwald T, Schütze A, Cirera A, Prades J D
MIND-IN2UB, Department of Electronics, University of Barcelona, 08028, Barcelona, Spain.
Lab of Measurement Technology, Department of Mechatronics, Saarland University, 66123, Saarbrucken, Germany.
Nanoscale. 2016 Mar 7;8(9):5082-8. doi: 10.1039/c5nr07158e.
One dimensional (1D) nanostructures offer a promising path towards highly efficient heating and temperature control in integrated microsystems. The so called self-heating effect can be used to modulate the response of solid state gas sensor devices. In this work, efficient self-heating was found to occur at random networks of nanostructured systems with similar power requirements to highly ordered systems (e.g. individual nanowires, where their thermal efficiency was attributed to the small dimensions of the objects). Infrared thermography and Raman spectroscopy were used to map the temperature profiles of films based on random arrangements of carbon nanofibers during self-heating. Both the techniques demonstrate consistently that heating concentrates in small regions, the here-called "hot-spots". On correlating dynamic temperature mapping with electrical measurements, we also observed that these minute hot-spots rule the resistance values observed macroscopically. A physical model of a random network of 1D resistors helped us to explain this observation. The model shows that, for a given random arrangement of 1D nanowires, current spreading through the network ends up defining a set of spots that dominate both the electrical resistance and power dissipation. Such highly localized heating explains the high power savings observed in larger nanostructured systems. This understanding opens a path to design highly efficient self-heating systems, based on random or pseudo-random distributions of 1D nanostructures.
一维（1D）纳米结构为集成微系统中实现高效加热和温度控制提供了一条充满希望的途径。所谓的自热效应可用于调节固态气体传感器设备的响应。在这项工作中，发现具有与高度有序系统（例如单个纳米线，其热效率归因于物体的小尺寸）相似功率要求的纳米结构系统的随机网络会发生高效自热。在自热过程中，利用红外热成像和拉曼光谱对基于碳纳米纤维随机排列的薄膜的温度分布进行映射。这两种技术一致表明，加热集中在小区域，即这里所说的“热点”。在将动态温度映射与电学测量相关联时，我们还观察到这些微小的热点决定了宏观上观察到的电阻值。一维电阻器随机网络的物理模型帮助我们解释了这一观察结果。该模型表明，对于给定的一维纳米线随机排列，电流在网络中的扩散最终会确定一组主导电阻和功率耗散的点。这种高度局部化的加热解释了在较大纳米结构系统中观察到的高功率节省。这种认识为基于一维纳米结构的随机或伪随机分布设计高效自热系统开辟了一条道路。
