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.
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Startår

2025

Slutår

2029

Beviljade finansiering

Orlando Silveira Júnior Orcid -palvelun logo
754 253 €

Finansiär

Finlands Akademi

Typ av finansiering

Akademiforskare

Beslutfattare

Forskningsrådet för naturvetenskap och teknik
12.06.2025

Övriga uppgifter

Finansieringsbeslutets nummer

371875

Vetenskapsområden

Fysik

Forskningsområden

Fysiikka

Identifierade teman

photonics, optics, laser