当前位置: X-MOL 学术Nanoscale Horiz. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Realizing the nanoscale quantitative thermal mapping of scanning thermal microscopy by resilient tip–surface contact resistance models
Nanoscale Horizons ( IF 9.7 ) Pub Date : 2018-04-24 00:00:00 , DOI: 10.1039/c8nh00043c
Yifan Li 1, 2, 3, 4, 5 , Nitin Mehra 1, 2, 3, 4, 5 , Tuo Ji 1, 2, 3, 4, 5 , Jiahua Zhu 1, 2, 3, 4, 5
Affiliation  

Quantitative assessment of thermal properties by scanning thermal microscopy (SThM) is a demanded technology, but still not yet available due to the presence of unpredictable thermal contact resistance (TCR) at the tip/substrate interface. The TCR is mainly affected by three major interfacial characteristics including surface roughness, hardness and contacting force. In this work, the TCR is mathematically derived into linear and non-linear models based on the interfacial micro-characteristics. The models have the capability to predict the TCR for both rough and smooth surfaces with satisfactory accuracy. With a predictable TCR, the heat transport across the tip/substrate nanointerface can be precisely described and thus quantitative thermal properties can be predicted from SThM measurements. The models are tested in three polymeric material systems, PDMS, epoxy and PVA. The thermal conductivity from the model prediction matches very well (<10% error) with the measured values from bulk polymer samples. Such models use general surface features as inputs, so they have wide applicability to other similar materials, especially polymers. Moreover, the models have been shown to be valid in doped PVA samples when extrapolated to predict thermal conductivity beyond the range of model development. This work extends the capability of SThM in quantitative measurement and enables a unique platform for thermal conductivity measurement at nanometer spatial resolution.

中文翻译:

通过弹性尖端-表面接触电阻模型实现扫描热显微镜的纳米级定量热图绘制

通过扫描热显微镜(SThM)定量评估热性能是一项必不可少的技术,但由于在尖端/基板界面处存在不可预测的热接触电阻(TCR),因此尚不可用。TCR主要受三个主要界面特性的影响,包括表面粗糙度,硬度和接触力。在这项工作中,基于界面微特征,TCR在数学上被推导出为线性和非线性模型。这些模型能够以令人满意的精度预测粗糙和光滑表面的TCR。利用可预测的TCR,可以精确描述跨尖端/基底纳米界面的热传递,因此可以根据SThM测量结果预测定量的热性能。这些模型在三种聚合材料系统(PDMS,环氧树脂和PVA)中进行了测试。通过模型预测得出的热导率与散装聚合物样品的测量值非常匹配(误差小于10%)。这样的模型使用一般的表面特征作为输入,因此它们对其他类似材料(尤其是聚合物)具有广泛的适用性。此外,已证明该模型在外推预测模型开发范围以外的热导率时在掺杂的PVA样品中是有效的。这项工作扩展了SThM在定量测量中的功能,并为纳米空间分辨率的热导率测量提供了一个独特的平台。这样的模型使用一般的表面特征作为输入,因此它们对其他类似材料(尤其是聚合物)具有广泛的适用性。此外,已证明该模型在外推预测模型开发范围以外的热导率时在掺杂的PVA样品中是有效的。这项工作扩展了SThM在定量测量中的功能,并为纳米空间分辨率的热导率测量提供了一个独特的平台。这样的模型使用一般的表面特征作为输入,因此它们对其他类似材料(尤其是聚合物)具有广泛的适用性。此外,已证明该模型在外推预测模型开发范围以外的热导率时在掺杂的PVA样品中是有效的。这项工作扩展了SThM在定量测量中的功能,并为纳米空间分辨率的热导率测量提供了一个独特的平台。
更新日期:2018-04-24
down
wechat
bug