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

Author:

Chavez-Angel Emigdio1ORCID,Ng Ryan C.1ORCID,Sandell Susanne2ORCID,He Jianying2ORCID,Castro-Alvarez Alejandro3ORCID,Torres Clivia M. Sotomayor14ORCID,Kreuzer Martin5ORCID

Affiliation:

1. Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC and BIST, The Universitat Autònoma de Barcelona Campus, 08193 Barcelona, Spain

2. NTNU Nanomechanical Lab, Department of Structural Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway

3. Laboratorio de Bioproductos Farmacéuticos y Cosméticos, Centro de Excelencia en Medicina Traslacional, Facultad de Medicina, Universidad de La Frontera, Temuco 4780000, Chile

4. Institución Catalana de Investigación y Estudios Avanzados (ICREA), 08010 Barcelona, Spain

5. CELLS-ALBA, Synchrotron Light Source, 08290 Barcelona, Spain

Abstract

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 um2 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.

Funder

LEIT funded by the European Research Council

Severo Ochoa program from the Spanish Research Agency

European Research Council

Marie Sklodowska Curie Individual Fellowship

NorFab

HEFACE project

Publisher

MDPI AG

Subject

Polymers and Plastics,General Chemistry

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