@article{35635,
  author = {Qiye Zheng and Divya Chalise and Mingxin Jia and Yuqiang Zeng and Minxiang Zeng and Mortaza Saeidi-Javash and Ali N.M Tanvir and Gottlieb Uahengo and Sumanjeet Kaur and Javier E Garay and Tengfei Luo and Yanliang Zhang and Ravi S Prasher and Chris Dames},
  title = {Structured illumination with thermal imaging (SI-TI): A dynamically reconfigurable metrology for parallelized thermal transport characterization},
  abstract = {<div class="hlFld-Abstract"><div class="NLM_paragraph">The recent push for the “materials by design” paradigm requires synergistic integration of scalable computation, synthesis, and characterization. Among these, techniques for efficient measurement of thermal transport can be a bottleneck limiting the experimental database size, especially for diverse materials with a range of roughness, porosity, and anisotropy. Traditional contact thermal measurements have challenges with throughput and the lack of spatially resolvable property mapping, while non-contact pump-probe laser methods generally need mirror smooth sample surfaces and also require serial raster scanning to achieve property mapping. Here, we present structured illumination with thermal imaging (SI-TI), a new thermal characterization tool based on parallelized all-optical heating and thermometry. Experiments on representative dense and porous bulk materials as well as a 3D printed thermoelectric thick film (∼50&thinsp;<em>μ</em>m) demonstrate that SI-TI (1) enables paralleled measurement of multiple regions and samples without raster scanning; (2) can dynamically adjust the heating pattern purely in software, to optimize the measurement sensitivity in different directions for anisotropic materials; and (3) can tolerate rough (∼3&thinsp;<em>μ</em>m) and scratched sample surfaces. This work highlights a new avenue in adaptivity and throughput for thermal characterization of diverse materials.</div></div>},
  year = {2022},
  journal = {Applied Physics Reviews},
  volume = {9},
  pages = {021411},
  month = {05/2022},
  url = {https://aip.scitation.org/doi/10.1063/5.0079842},
  doi = {10.1063/5.0079842},
  language = {eng},
}