The Chemical Abstracts Service Registry currently lists in excess of 144 million unique chemical compounds. While many of these, such as elements, isotopes, metals, alloys, and nuclear particles, are not infrared or Raman spectrometry active, the vast majority of compounds in the Registry can be measured by vibrational spectrometry. Commercial databases, such as the KnowItAll libraries certainly have extensive collections of spectra, on the order of hundreds of thousands. Therefore, it is not unreasonable to expect that some compounds would not be found in the spectral databases. Even so, a spectral search system can be most valuable to determine the chemical structure of an unknown sample.

Such a situation arose when the US Drug Enforcement Administration was in possession of a sample from a putative clandestine laboratory. Infrared and mass spectra were collected of the sample and neither yielded acceptable results from computer searches. The sample was pure, but clearly a heretofore unknown compound. A request was made to see if the infrared spectrum could be interpreted manually. From the appearance of the spectrum the compound appeared to be a relatively rigid molecule and certainly there were immediate indications it was an aromatic compound. A standard interpretation procedure was undertaken, but there were spectral features that were consistent with other compounds, but no exact matches were found. Regions of the unknown spectrum were searched to determine if similar compounds existed and clues could be elucidated to substructures. Once some of these substructures were identified, the veracity of the analysis was confirmed or discarded with the use of spectral heatmaps. In the end, two chemical structures were found, and they differed simply by the position of a single methyl group. An organic chemist at the DEA immediately realized that one of the structures was most probable and recognized that the compound led to a simple and rapid synthesis of methamphetamine.

Microplastics are increasingly of global environmental concern. These polymer particles are defined as < 5 mm in size with an assortment of morphologies (fiber, fragment, bead, film). As these particles are ubiquitous, the need to accurately identify and possibly target sources of these contaminants is of great interest to scientists worldwide. Microplastics are found in both seawater and freshwater bodies around the world with higher concentrations along coastlines. Polymer materials breakdown in the natural environment over time via photochemistry and mechanical fragmentation. The most prevalent microplastics are: polyethylene, polypropylene, polystyrene and polyethylene terephthalate. Routine identification methods include: reflection light microscopy, density gradient separation and spectroscopy (infra-red (IR) and Raman). Fairly pure polymers can be readily matched to spectral databases; however, some microplastic fragments exhibit a more complex FTIR spectrum. Spectral subtraction can be applied in multi-component characterization but often requires time and expertise to properly utilize. This presentation will discuss the ‘mixture analysis’ application in KnowItAll to identify copolymers and more complex microplastics. For example, a small blue fragment exhibited polyurethane functionality but could not be matched as a single component spectrum. Mixture analysis identified the fragment as ~73% polyurethane and ~27% glass filled polyester. Accurate characterization of multi-component microplastic fragments could be applied to track sources. Environmental scientists are working to educate the public and ultimately work with local and state governmental agencies to capture these fragments before they enter freshwaters contaminating our environment.

The Raman microscope, introduced in the mid 1970’s is being focused on applications in areas where microparticle identification is key to an area of analytical research. The implementation of smart sampling (ParticleFinder™) hardware and software has been developed to accommodate these requirements. We will show examples from Forensic Trace Evidence, Microplastics (generally retrieved for the world’s oceans) and Aerosols.

In the field of Forensic Trace Evidence, identification of fibers can connect a suspect with a crime scene. Not only can the polymer be identified, but the colorant or other additives as well.

In the field of microplastics, identification of microparticles of polymers ingested by marine organisms can sometimes be important in order to understand the specific toxicity of a particular polymer to an organism.

In the field of aerosols, identification of particles can be important for environmental testing. Asbestos particles are a hazard in building remediation. Sulfate, sulfite, nitrate and nitrite particles are of interest in causing acid rain. Years ago, people at NBS (now NIST) documented the occurrence of heavy metal oxides in particles collected in the Antarctica; because these particles presumably come from power plants, that means that we are documenting their distribution by air currents above the surface of the earth. And because the metal composition of petroleum and coal reflects their sources, it is possible to trace the origin of these particulates.

Contamination control for Space involves stringent requirements for mission assurance. Materials selected for Space launch vehicles need to stay below particulate and vacuum outgassing thresholds and adhere to restrictions on allowable contaminants and specialized contamination control plans. Due to the requirements and the concern that harmful residues may deleteriously impact the mission, contamination understanding is of utmost importance. Any sighting of an unknown residue requires investigation and mitigation. Residues manifest as slight discolorations, extremely thin layers formed on surfaces, or observed as changes in surface energy. Residues come about by either unforeseen chemical reactions, unplanned chemical incompatibility, or can be generated during processing and assembly. Fourier Transform Infrared- Attenuated Total Reflection (FTIR-ATR) methods are a good choice for quickly analyzing these residues, and for providing an indication of what the material is since the method can deal with limited sample size. To be able to identify low level residues, FTIR-ATR is used to analyze bulk materials, the residue left behind on the ATR crystal after a bulk material measurement, analysis of individual adhesive components in uncured states, and extracts of the materials using typical cleaning solvents used in manufacturing. This presentation will demonstrate special databases we have created and show how residue spectra differ from bulk material spectra, and how the KnowItAll software helps to provide analysis of mixtures of a variety of contamination using our database in conjunction with purchased databases.

KnowItAll from Bio‑Rad has become an industry standard database and software package providing spectral search, spectral identification, mixture analysis, functional group analysis and many other powerful spectral analysis tools. We have been exploring the combined use of KnowItAll software with two-dimensional correlation spectroscopy (2D-COS). 2D-COS analyzes a set of spectra systematically collected for a system under an influence of some external perturbation. It is essentially a model-free data analysis technique, which does not require the specific knowledge about the origins of spectroscopic features. Molecular information supported by the vast database of KnowItAll brings in powerful additional aspect to 2D-COS analysis. 2D-COS traditionally required a relatively large number of spectra, but a newly introduced form of 2D-COS called two-trace two-dimensional (2T2D) correlation spectroscopy now uses only a pair of spectra. Spectral intensity changes of bands arising from the same origin, which cannot change independently of each other, are synchronized. Meanwhile, those arising from different sources may and often do change asynchronously. By taking advantage of this property, one can distinguish and classify a number of contributing bands present in the original pair of spectra in a systematic manner using 2T2D-COS. Highly overlapped neighboring bands originating from different sources can be identified by the presence of asynchronous cross peaks, thus enhancing the spectral resolution and differentiation. We report the potential of spectral identification capability of KnowItAll effectively combined with the spectral resolution afforded by 2D-COS.

Infrared spectroscopy is among the most common chemical characterization techniques used in industry and academia. The fact that modern Fourier transform infrared (FT-IR) instruments produce excellent spectra and are easy to use has enabled this powerful capability to be used by many nonexperts in their research and for industrial problem solving. IR spectra are complicated and contain a tremendous amount of information about the molecular structure of a material. Because the community of analysts who are truly experts at interpreting IR spectra is shrinking, there is an increased need for database searching help to solve important problems. Even though use of KnowItAll database searching can help analysts inexperienced in the art infrared interpretation to solve problems, it works far more effectively in the hands of a trained, experienced spectroscopist.

Condensed phase IR spectral line shapes tend to be broad, often resulting in highly overlapped bands. IR peak positions, line widths, and bandshapes are easily perturbed by the environment of the molecule. This can be turned into an advantage if we are able to interpret the spectroscopic subtleties. IR spectra can also vary depending on the accessory used to collect the spectrum. Many analytical laboratories rely heavily on attenuated total reflection (ATR) because it requires less sample preparation than transmission measurements where very thin or diluted samples are required to get photometrically accurate IR spectra. ATR spectral intensities, however, need to be corrected in order to properly match database spectra collected in transmission. Peak positions and lineshapes of the most intense IR bands can also be significantly distorted, depending on the refractive index difference between the internal reflection element (IRE) and the sample. Understanding how these spectral distortions can affect KnowItAll searches is important for helping use the tool to identify unknown spectra that many times are not pure materials.

A new approach that uses the photothermal infrared (PTIR) response of the sample produces IR spectra that do not require any correction. A visible laser is used to sense the photothermal response when a tunable IR pump laser wavenumber is absorbed by molecular vibrations in the sample. The visible optical response is measured in a reflection geometry, resulting in IR spectra that match those acquired in transmission mode in KnowItAll searches, even for thick samples.

Several examples of KnowItAll searches illustrating these points will be presented.

Learn about the most recent advances in KnowItAll software as Bio‑Rad continually adds spectral intelligence to its platform.

Bio‑Rad's KnowItAll product manager and head of software development will engage current KnowItAll users in a discussion on new software features and modifications that the user community feels will have a significant impact on improving their work.