Raman @ spectroscopyNOW. The
Raman spectroscopy channel covers research into all aspects of this non-destructive technique including surface-enhanced
Raman spectroscopy (SERS), and related
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spectroscopy is routinely used in analytical chemistry for the quantitative determination of different analytes, such as transition metal ions, highly conjugated organic compounds, and
biological macromolecules.Spectroscopic analysis is commonly carried out in solutions but …
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Raman Spectroscopy (SORS) Spatially offset
Raman spectroscopy (SORS) is a unique way to analyze objects when the contents are behind nontransparent layers or containers. In recent years, there have been significant advances in the application of vibrational
spectroscopy to the analysis of forensic samples. Igor K. Lednev, a professor in the Department of Chemistry at the University at Albany, the State University of New York, has been developing the use of
Raman spectroscopy for a variety of forensic
applications, including the determining the age of blood ...
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Raman spectroscopy for a varietyof forensic
applications, including determining the age of blood stains and linking gunshot residues to …
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Raman Spectroscopy can be helpful in the analysis of cathodes and anodes in Li-ion batteries. Today’s state of art of technology requires more reliable, more efficient and powerful energy sources.
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Raman spectroscopy is yet to attain the popularity of FT-IR techniques, although the number of publications is steeply increasing.
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Raman spectra are very low in intensity and coded in the most mysterious of energy units (wavenumbers, or cm-1), they probe molecular structure as effectively as IR
spectroscopy, but with greater ease of use, more versatility, and lower cost.
Raman spectral signatures can play a role in fundamental research, or be matched to a known database for instant identification and quantification ... The present study utilizes exosomes purified from pancreatic cancer and pancreatic epithelial cell lines and surface enhanced
Raman spectroscopy (SERS) spectra to train an algorithm by Principle Component-Differential Functional Analysis (PC-DFA).
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