Structural machine learning for high resolution tip-enhanced Raman spectroscopy
Bidragets beskrivning
Optical spectroscopy has long been an important characterization technique capable of providing chemical and structural information from molecules and nano materials in a non-destructive manner. However, due to the Abbe diffraction limit, propagating light cannot be localized in a region smaller than approximately half of its wavelength. For example, the wavelength of green light is 500 nm, resulting in a spatial resolution of ~ 250 nm, way larger than typical interatomic distances. To overcome this, scientists have been illuminating samples with a light coming from a source way smaller than the typical wavelength of light, which enables them to get amazing Å-scale resolution images. In this project, we will focus on simulating an experiment where the light is trapped between a very sharp tip and the sample creating a plasmonic field, which is then interpreted by a Raman spectrometer. This technique is called tip enhanced Raman spectroscopy, or TERS for short.
Visa merStartår
2025
Slutår
2029
Beviljade finansiering
Finansiär
Finlands Akademi
Typ av finansiering
Akademiforskare
Beslutfattare
Forskningsrådet för naturvetenskap och teknik
12.06.2025
12.06.2025
Övriga uppgifter
Finansieringsbeslutets nummer
371875
Vetenskapsområden
Fysik
Forskningsområden
Fysiikka
Identifierade teman
photonics, optics, laser