Title data
Bocklitz, Thomas ; Guo, Shuxia ; Ryabchykov, Oleg ; Vogler, Nadine ; Popp, Jürgen:
Raman based molecular imaging and analytics : a magic bullet for biomedical applications!?
In: Analytical Chemistry.
Vol. 88
(2016)
Issue 1
.
- pp. 133-151.
ISSN 1520-6882
DOI: https://doi.org/10.1021/acs.analchem.5b04665
Abstract in another language
The Raman effect was predicted by Schmekal1 in 1923 and independently discovered in 1928 by two Indian physicists, Raman and Krishna.2,3 In principle, monochromatic light is inelastically scattered at a quantiffed structure like the vibrational states of a molecule. The occurring energy shifts are an indirect representation of the vibrational states of the molecule and, thus, are molecule specific. If this principle is spectroscopically used, an ensemble of molecules is measured and the result is called a Stokes-Raman spectrum, or shorter a Raman spectrum. The Stokes-Raman spectrum is the part of inelastically scattered light, which is shifted to lower energies.4,5 This is the dominant effect at room temperatures, which is the reason for skipping the attribute. Due to the ensemble mixing the Raman spectrum is not representing the vibrational states of one molecule but of a mixture of molecules. Thus, the Raman spectrum is a superposition of Raman spectra of substances within the excitation focus. Because the unmixing of this superposition is only possible for limited cases, the Raman spectrum is used as a vibrational fingerprint. This fingerprint is either interpreted with a certain set of reference Raman spectra or evaluated by means of statistical methods. The latter procedure is often applied, if heterogonous mixtures like cells or tissues are investigated, while the former method is used, if pure substances or easy mixtures are studied. As investigations on biological samples, like cells or tissue are the topic of the review, we will focus on biological samples in the following. Therefore, a Raman spectrum is used as vibrational fingerprint.
Further data
Item Type: | Article in a journal |
---|---|
Refereed: | Yes |
Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie > Lehrstuhl Künstliche Intelligenz in der Mikroskopie und Spektroskopie - Univ.-Prof. Dr. Thomas Wilhelm Bocklitz |
Result of work at the UBT: | No |
DDC Subjects: | 500 Science > 530 Physics |
Date Deposited: | 19 May 2023 10:17 |
Last Modified: | 19 May 2023 10:17 |
URI: | https://eref.uni-bayreuth.de/id/eprint/76292 |