Infrared nanospectroscopy and hyperspectral nanoimaging of organic matter
- Autores: Iban Amenabar Altuna
- Directores de la Tesis: Rainer Hillenbrand (dir. tes.)
- Lectura: En la Universidad del País Vasco - Euskal Herriko Unibertsitatea ( España ) en 2017
- Idioma: inglés
- Tribunal Calificador de la Tesis: Thomas Taubner (presid.), Juan José Sáenz Gutiérrez (secret.), Javier Aizpurua Iriazabal (voc.)
- Materias:
- Enlaces
- Tesis en acceso abierto en: ADDI
- Resumen
Infrared (IR) spectroscopy is a highly valuable tool for materials characterization in widely different fields, ranging from polymer sciences to biomedical imaging. However, the diffraction limit prevents nanoscale infrared studies. The IR diffraction limit can be circumvented, among other techniques by infrared scattering type scanning near-field optical microscopy (IR s-SNOM) and its extension to nanoscale Fourier transform infrared spectroscopy (nano-FTIR), which enable infrared imaging and spectroscopy with nanoscale spatial resolution, respectively.In this thesis, we introduce mapping of protein structure with 30nm lateral resolution and sensitivity to individual protein complexes by nano-FTIR. We present local broadband spectra of one virus, ferritin complexes, purple membranes and insulin aggregates, which can be interpreted in terms of their ¿-helical and/or ¿-sheet structure. Applying nano-FTIR for studying insulin fibrils - model system widely used in neurodegenerative disease research - we find clear evidence that 3-nm-thin amyloid-like fibrils contain a large amount of ¿-helical structure.To gain further insights into the structure of the samples, spectroscopic information at each pixel of an image is desirable, that is hyperspectral imaging. In this thesis, we introduce hyperspectral infrared nanoimaging based on nano-FTIR with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5000 pixel, each one covering the spectral range from 1000 to 1900 cm-1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine.
