Application of Synchrotron Radiation-Based Fourier-Transform Infrared Microspectroscopy for Thermal Imaging of Polymer Thin Films

The thermal imaging of surfaces with microscale spatial resolution over micro-sized areas remains a challenging and time-consuming task. Surface thermal imaging is a very important characterization tool in mechanical engineering, microelectronics, chemical process engineering, optics, microfluidics,...

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Detalles Bibliográficos
Autores: Chávez Ángel, Emigdio|||0000-0002-9783-0806, Ng, Ryan C.|||0000-0002-0527-9130, Sandell, Susanne|||0000-0003-1906-6790, He, Jianying|||0000-0001-8485-7893, Castro-Alvarez, Alejandro|||0000-0001-8360-8027, Sotomayor Torres, Clivia M.|||0000-0001-9986-2716, Kreuzer, Martin|||0000-0002-7305-5016
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:272444
Acceso en línea:https://ddd.uab.cat/record/272444
https://dx.doi.org/urn:doi:10.3390/polym15030536
Access Level:acceso abierto
Descripción
Sumario:The thermal imaging of surfaces with microscale spatial resolution over micro-sized areas remains a challenging and time-consuming task. Surface thermal imaging is a very important characterization tool in mechanical engineering, microelectronics, chemical process engineering, optics, microfluidics, and biochemistry processing, among others. Within the realm of electronic circuits, this technique has significant potential for investigating hot spots, power densities, and monitoring heat distributions in complementary metal-oxide-semiconductor (CMOS) platforms. We present a new technique for remote non-invasive, contactless thermal field mapping using synchrotron radiation-based Fourier-transform infrared microspectroscopy. We demonstrate a spatial resolution better than 10 um over areas on the order of 12,000 um measured in a polymeric thin film on top of CaF substrates. Thermal images were obtained from infrared spectra of poly(methyl methacrylate) thin films heated with a wire. The temperature dependence of the collected infrared spectra was analyzed via linear regression and machine learning algorithms, namely random forest and k-nearest neighbor algorithms. This approach speeds up signal analysis and allows for the generation of hyperspectral temperature maps. The results here highlight the potential of infrared absorbance to serve as a remote method for the quantitative determination of heat distribution, thermal properties, and the existence of hot spots, with implications in CMOS technologies and other electronic devices.