Structural machine learning for high resolution tip-enhanced Raman spectroscopy
Description of the granted funding
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.
Show moreStarting year
2025
End year
2029
Granted funding
Funder
Research Council of Finland
Funding instrument
Academy research fellows
Decision maker
Scientific Council for Natural Sciences and Engineering
12.06.2025
12.06.2025
Other information
Funding decision number
371875
Fields of science
Physical sciences
Research fields
Fysiikka
Identified topics
photonics, optics, laser