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
Colecciones
Colección Publicaciones Científicas
Colección ANID
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