Repositorio UFRO · Omeka S

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

Primer Autor	Chavez-Angel, Emigdio
Co-autores	Ng, Ryan C. Sandell, Susanne He, Jianying Castro-Alvarez, Alejandro Torres, Clivia M. Sotomayor Kreuzer, Martin
Título	Application of Synchrotron Radiation-Based Fourier-Transform Infrared Microspectroscopy for Thermal Imaging of Polymer Thin Films
Editorial	MDPI
Revista	POLYMERS
Lenguaje	en
Resumen	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(2) measured in a polymeric thin film on top of CaF2 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.
Fecha Publicación	2023
Tipo de Recurso	artículo original
doi	10.3390/polym15030536
Formato Recurso	PDF
Palabras Claves	thermal imaging synchrotron radiation machine learning temperature dependence FTIR polymer FTIR thermometry
Ubicación del archivo	http://dx.doi.org/10.3390/polym15030536
Categoría OCDE	Ciencia de los polímeros
Materias	imágenes térmicas radiación sincrotrón machine learning dependencia de la temperatura polímero FTIR termometría FTIR
Identificador del recurso (Mandatado-único)	artículo original
Versión del recurso (Recomendado-único)	versión publicada
License	CC BY 4.0
Condición de la licencia (Recomendado-repetible)	CC BY 4.0
Derechos de acceso	acceso abierto
Access Rights	acceso abierto
Id de Web of Science	WOS:000931029600001
Tipo de ruta	verde# dorado
Categoría WOS	Ciencia de los polímeros