Raman and Infrared Spectra: Capturing the Artistry of Spectral Interpretation

In the scientific world, information-sharing is one of the key factors in the advancement of science. In a corporate environment, it is common for individuals to gain detailed knowledge over time 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 textbooks.1–3 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 article focuses on a means of capturing spectrum-to-structure correlations for Raman and infrared spectra. It discusses 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 the user’s own knowledge, but to combine it with the knowledge of colleagues to help the user make better decisions.

Traditional spectral interpretation techniques

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, more time was available for training, i.e., 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 because so much of it is based on the experience of the user.

Figure 1 – Example of a spectrum on a paper chart with handwritten notations.

The most predominant method for capturing spectrum-to-structure correlations has traditionally been handwritten notes on printed spectra (see Figure 1). 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. Yet, the information contained on these charts is an important resource to a corporation’s current and future needs because it is a product of the organization’s costly investment in research.

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 PowerPoint where they can draw a structure fragment or write a note near a peak.

Although digitally annotating a spectrum 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.

Applying structural and spectral integration to optical spectroscopy

ACD/Labs (Toronto, Ontario, Canada) has a long history of integrating structures with spectra, initially with respect to NMR data. With this background it seemed a natural extension to apply this ability to integrate spectra and structures to the field of optical spectroscopy. Any approach to a better solution for acquiring and sharing knowledge of spectral interpretation needs to consider several factors:

1. The linking of spectroscopic peaks to a structure is not often a simple one-structure fragment to one peak. Typically correlations are one-to-many or many-to-one. All or part of a spectrum and structure may need to be assigned. A single structure fragment can be “linked” to several peaks, or a single peak “linked” to several parts of the structure (see Figure 2). Once saved, the spectrum, structure, and any correlations made are stored together as a single file.

Figure 2 – Assignment of one peak to several fragments and one fragment to several peaks.

2. As pointed out previously, the knowledge required to create spectrum–structure relationships is not trivial to obtain; therefore including a knowledge base for IR and Raman correlations would be helpful to assist in finding the general regions where the structure fragment’s bands may be found. Structural fragments can be easily assigned to spectral peaks using a click-and-drag approach (see Figure 3). When no structure is available, assignments can be made directly from rows in the knowledge base to the spectrum.

Figure 3 – Assignment of CH2 symmetric stretch band. Several possible peaks for a CH2 group in the molecule have been highlighted by the software. The user has the option of using some or all of the suggested peaks.

3. Another important consideration is how to display the captured information. A simple table of assignments could be used to display the correlations, but reading text is not always the easiest way to see information. Because the spectrum–structure correlations have been linked, a more visual approach was also considered. The user can simply drag the mouse over any piece of information to see all of the data linked to it (see Figure 4).

Figure 4 – Running the mouse over the peak at 1736 cm–1 highlights the peak, the C=O in the structure it is assigned to, and the row in the assignment table.

4. Another major consideration is the user’s work flow. No matter what the benefits, adding work to an existing process always presents a hurdle. Any additional work is minimized by the history of spectral and structure import of ACD/Labs. If an interpretation has been done in the software, it is automatically available for reports or databasing. If the interpretation has been done outside of the software, the spectra (and structure if available) can be easily imported and assignments can be quickly added to the data so that no reinterpretation is needed. Once assignments are made, placing the spectrum, structure, and its assignments, along with any additional textual data, into an analytical database can be accomplished with just a single mouse click.

5. Lastly, the ability to share this captured information with colleagues is the ultimate goal. Once the information is uploaded into a database, these libraries of spectra—along with their structures or fragments, assignments, other interpretations, and associated information—can be accessed by colleagues around the globe, now or in the future. Data can be searched by spectrum, structure, or meta data to view and even manipulate existing information. Results from a search can be overlaid with a query spectrum to see the assigned bands matching the user’s query spectrum and helping to identify the part of the structure that matched the query. ACD/Optical Workbook includes a small IR database of assigned polymers and a small Raman database of assigned amino acids as a basis for spectral searching (see Figure 5).

Figure 5 – Spectral search results with the assignment feature being used to help identify the spectra–structure correlations of matching peaks.

ACD/Optical Workbook is a software tool that addresses the challenge of making spectrum-to-structure correlations for in-house experimental data. It facilitates knowledge-sharing through flexible reporting and powerful library searching capabilities as part of ACD/Labs’ Spectrus platform for chemical and analytical knowledge management. Optical Workbook also offers advanced tools for processing and interpretation of a variety of optical spectroscopy techniques including IR and Raman. Optical Workbook can import IR or Raman spectra from most instruments and public formats such as JCAMP-DX and ACSII text files. Additionally, it conveniently includes basic processing and interpretation for NMR, MS, and chromatography, and can also be used to draw structures, or structures can be copied and pasted from other drawing packages.

ACD/Labs’ databases save the human interpretation of the data with the spectrum, thereby cataloging spectrum-to-structure correlations. This expertise can be made available as a local database on a desktop computer, or as part of a global enterprise-wide database using the company’s scaleable analytical and chemical knowledge-management solutions.

A complete knowledge-management solution for the laboratory

Research organizations make large investments in developing knowledge to solve current research problems and are now beginning to realize the value of capturing that knowledge to be reapplied to future research, not only the tangible results of analytical experiments and assays, but the tacit knowledge and interpretations that have until now been relegated to the mind of a single in-house expert. This knowledge would eventually be lost upon retirement or as employees leave the company. With ACD/Optical Workbook (and other technique-specific workbooks from ACD/Labs), this knowledge can be easily stored and retrieved when it is needed by new users or scientists throughout a corporation.

References

  1. Socrates, G. Infrared and Raman Characteristic Group Frequencies: Tables and Charts; Wiley: New York, NY, 2004.
  2. Ferraro, J.R.; Nakamoto, K. Introductory Raman Spectroscopy; Academic Press: San Diego, CA, 1994.
  3. Lin-Vien, D.; Colthrup, N.B. et al. The Handbook of Infrared and Raman Characteristic Frequencies of Organic Molecules; Academic Press: San Diego, CA, 1991.

Mr. Boruta is Optical Spectroscopy Product Manager, Advanced Chemistry Development, Inc. (ACD/Labs), 8 King St. E., Ste. 107, Toronto, Ontario M5C 1B5, Canada; tel.: 416-368-3435; e-mail: michael.boruta@acdlabs.com.

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