Benefits for analytical chemistry applications
The benefits of Klarite derive from a unique combination of analytical attributes:
- A 1,000,000-fold enhancement in sensitivity of SERs, compared to conventional Raman.
- The reproducibility of results provided by Klarite, compared to other SERS substrates.
This combination promises to launch SERS as a true analytical technique for the first time.
These attributes offer a number of valuable benefits to analytical chemists:
- Lower levels of detection and identification
- Quantitation at very low concentrations
- Detection of low levels of impurities
- The ability to use lower cost Raman equipment for challenging applications
- Simple, repeatable analytical protocols, compared to other SERS substrates
Klarite in analytical chemistry
Surface enhanced Raman Spectroscopy (SERS) is a powerful and versatile tool for both qualitative and quantitative chemical analysis.
SERS provides valuable information on the molecular structure of chemical compounds. Like other vibrational spectroscopic techniques such as FTIR and Raman, SERS spectra provide a distinctive fingerprint of bands. The position (wavenumber) and relative intensities of these bands are determined by the functional groups present in the molecules as well as the molecular geometry.
Applications of these capabilities include :
• Investigating the molecular structure of novel compounds
• Determining the chirality of enantiomeric molecules
• Identifying unknown or suspect samples using the entire spectrum as a fingerprint
• Verifying a known material’s composition by comparing its spectrum with those from a calibration set
The intensity of the bands in SERS spectra is directly related to the quantity of sample being measured. This allows SERS to be used to quantify single analytes as well as multicomponent mixtures.
For simple mixtures, individual or combined band intensities can be used to quantify components directly.
For more complex mixtures, or for samples with overlapping bands, whole-spectrum chemometric techniques such as partial least squares (PLS) are more reliable.
The sensitivity of SERS lends itself to analysing very low levels of analyte.