This toolbox for analysing spectroscopic reaction data allows you to
extract time-based trendlines from GRAMS® multifiles. ReactionSleuth™
includes visual tools for selecting features and using them to create
simple, or baseline-corrected, trendlines.
Complex features can be analysed using Peakfitting models created in
GRAMS® to deconvolute complex spectra and generate trendlines based
on individual peak areas. The PCA/Iterative Target Transformation capability
allows you to extract principal components and synthetic spectra from
highly complex data sets, along with trendlines showing their changing
contribution over the course of the reaction. When time-varying spectroscopic
data is available in a multifile format, the ReactionSleuth™ ActiveApp®
offers a simple but powerful visual interface for a range of reaction
analysis tools. ReactionSleuth™ displays the multifile as a 3D object
which can be rotated and re-scaled to let you pick up reaction trends
The secondary plot shows individual spectra from the dataset or it can
be used to display trendlines. The simplest type of trendline graph the
absorbance at a single frequency against time. The ReactionSleuth™
PeakPicker is a visual tool for visually selecting features for simple
More complex features in a spectrum can be analysed by building a peak
model using the GRAMS® Peak Fitting application. You can use a peak-fit
model in ReactionSleuth™ to generate a set of trendlines based on
peak area versus time - the lines appear on a list of lines available
for display after the model has been run against the multifile dataset.
Both simple and peak-fitted trendlines can be used in the autoscaled
display, and all of the calculated trendlines can be saved in ASCII files
for later use in spreadsheets etc. When simple techniques are not enough,
the ReactionSleuth™ PCA/Iterative Target Transform capabilities
can be used to find trends in datasets and generate "synthetic spectra".
ReactionSleuth™'s simple visual interface gives you access to sophisticated
mathematical methods, but leaves you in control of the way the methods
Both the principal components and the synthetic spectra can be individually
subtracted from the dataset. Once all of the calculated factors or spectra
have been subtracted, the 3D display of the residuals gives a good indication
of the quality of the fit and can be useful for identifying any small
unmodelled features such as transient a intermediate.
Finally syntetic spectra of the species identified using the Target Transformation
process can be exported as .SPC files and further processed in GRAMS or
identified using Spectral
here to download a demo.