IR and Raman: Capturing the Artistry of Spectral Interpretation Michael Boruta Optical Spectroscopy Product Manager, ACD/Labs Contents Background 2 Where We Have Been for the Past 10 Years 3 What is Possible Today? 4 When No Structure is Available 5 Databasing—How Much Effort? 6 Store, Share, and Re-use 6 References 7
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IR and Raman: Capturing the Artistry of Spectral Interpretation · 2013-03-04 · IR and Raman: Capturing the Artistry of Spectral Interpretation Michael Boruta Optical Spectroscopy
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IR and Raman:
Capturing the Artistry of Spectral Interpretation
Michael BorutaOptical Spectroscopy Product Manager, ACD/Labs
Contents
Background 2
Where We Have Been for the Past 10 Years 3
What is Possible Today? 4
When No Structure is Available 5
Databasing—How Much Effort? 6
Store, Share, and Re-use 6
References 7
In the scientific world, sharing information is one of the
key factors in the advancement of science. Fortunately for
IR spectroscopists and, to a slightly lesser extent, Raman
spectroscopists, there exist a number of excellent text books1-3
in which the authors have shared with us their compiled
information about spectrum-to-structure correlations. These
correlations help us understand and interpret the spectra we
work with every day.
In a corporate environment it is common for individuals to,
over time, gain detailed knowledge about the correlation
between some spectral features and the materials they work
with on a daily basis. This knowledge often exceeds the more
general information available in text books. However, until
recently, there has not been a method available to capture
that specialized knowledge. It either resides in the mind of
the individual or is sometimes handwritten on a chart and
filed away—hardly useful to propagate knowledge sharing
throughout the corporate environment or to share with future
spectroscopists.
This paper will briefly touch on analytical data management
while focusing primarily on a means of capturing spectrum-to-
structure correlations for IR and Raman spectra. We will discuss
methods that can be used to obtain, archive, and retrieve this
knowledge so that, once derived, it will remain a resource
within the laboratory beyond the confines of individual analyst
expertise. The aim of such a system is to not only capture
your own knowledge but also to combine it with that of your
colleagues to help you make better decisions.
Background
Infrared and Raman spectroscopy are valuable tools for many
different kinds of materials and are used to acquire chemical
and structural information such as verifying a proposed
chemical structure, or confirming the presence of functional
groups. Unfortunately the interpretation of the resulting spectra
can often be a difficult and time-consuming task, therefore
spectral interpretation has traditionally fallen under the realm of
the experienced spectroscopist.
In the past there used to be much more time available for
training—for older more experienced spectroscopists to transfer
their knowledge to younger/less experienced users. While
mentoring still exists, the time available for such training has
decreased in an age where researchers are continually expected
to do more with less. The situation is most pronounced in areas
such as spectral interpretation—often referred to as an art,
because so much of it is based on the experience of the user.
Several factors make spectral interpretation difficult for the
inexperienced. Two of the most common are the overlap of
regions where certain functional groups can exhibit bands,
and the movement of bands due to the physical or chemical
environment. Traditional methods of interpreting these spectra
rely heavily on the expert’s experience, the use of multiple
reference books or spectra, and some preconceived ideas about
the chemistry of the material in question. Spectral searching can
assist with interpretation; however, it has mostly been used as
an aid to chemical identification.
Historically, the primary resource for information on spectrum-
to-structure correlations has been personal experience, the
expertise of their colleagues or one of the many reference books
on the subject of group frequencies. More recently several
software programs have become available to assist in the
interpretation of spectra.
Collections of correlation tables and charts (often from several
different sources or books) containing information about the
band frequencies of various functional groups can contain
hundreds or thousands of known characteristic frequencies.
Manually searching these tables requires considerable time and
effort, even for experienced spectroscopists.
2
The most predominant method for capturing spectrum-to-
structure correlations in the past has been hand written notes
on printed spectra. The charts were often indexed and saved
in filing cabinets for future reference. A major drawback of
this system is the difficulty in finding the right chart with the
right information when needed. It is often easier to re-run and
re-analyze a compound than it is to track down the original
information. This can be a significant waste of time and
resources to reproduce or relearn what was already known.
Yet, the information contained on these charts is an important
resource to a corporation’s current and future needs as it is a
product of the organization’s costly investment in research. IR
and Raman information in particular might serve to categorize
particular compounds or classes of compounds that are of
interest to the corporation, often for legal purposes. A second
purpose is to provide a resource for colleagues to share
information and knowledge that has been created over many
years.
Figure 1. Example of a spectrum on a paper chart with hand
written notations.
Many scientists still rely on paper copy to “archive” the
interpretations they make. Some may use annotation abilities
within the instrument’s software while others have moved
to tools like MS Power Point where they can draw a structure
fragment or write a note near a peak. These methods are
primarily used for reporting purposes. This methodology is
adequate for a one time assessment of some spectral feature.
However, if there is a desire to retain and share the knowledge
gained, these methods leave much to be desired.
Where We Have Been for the Past 10 Years
We have progressed in many areas for storage of analytical
spectroscopic data for IR and Raman instruments over the
past couple of decades. Today software is available from most
instrument manufacturers to manage and database spectral
data. Several software packages can also manage textual
data and peak tables. These software programs allow an easy
means to search for and retrieve this data. There also exist a few
independent software providers that can provide the means to
include structures with the data and, in some cases, multiple
data types such as IR and Raman in the same database.
With some of these software packages it is now possible to
take the spectral data, combine it with a structure, and add
annotations on the spectrum to indicate the spectrum-to-
structure correlations for reporting purposes (see figure 2).
Figure 2. Digital spectrum with annotations—same sample as
figure 1.
Although digitally annotating a spectrum in Microsoft
PowerPoint or another software package is better than writing
notes on a chart (the ink will not fade and the handwriting
is easier to read) we are still essentially writing notes on a
spectrum. This method is adequate for producing reports, both
paper and electronic, but leaves much to be desired in terms of
sharing information with colleagues.
3
What is Possible Today?
A new software tool, ACD/Optical Workbook, is now available
that allows spectroscopists to store the spectrum-to-structure
correlations for their own experimental data on in-house
compounds. This software is part of the ACD/Labs Spectrus
family of chemical and analytical knowledge management
software.
ACD/Optical Workbook is an advanced tool for processing and
interpretation of a variety of optical spectroscopy techniques
including IR and Raman. Optical Workbook addresses the
challenge of making spectrum-to-structure correlations and
facilitates knowledge sharing through flexible reporting and