Characterization of Diesel Fuel Using a Modular Raman System
Based on the Application note Written by Yvette Mattley, PhD, Ocean Optics
Raman spectroscopy stands out as an exceptional technique for the identification and characterization of fuels. Requiring no sample preparation, this powerful method can both identify and quantify materials, making it invaluable across various industries. When applied to fuel samples, Raman spectra reveal a rich array of spectral features due to different types of hydrocarbons, providing a unique Raman fingerprint based on composition.
Raman Spectroscopy in Fuel Analysis
Raman spectroscopy, complemented by chemometric models, can fully characterize fuels, determining critical parameters such as octane rating and density. Additionally, Raman spectroscopy aids in detecting counterfeit fuels by using Raman spectral markers, enabling rapid field confirmation of fuel composition, quality, and source.
The Role of Raman Spectroscopy in Biodiesel Production
Biodiesel, a renewable diesel fuel made from vegetable oil or animal fats, is produced through transesterification. This process involves reacting the oil or fat with an alcohol to remove glycerin and produce biodiesel as fatty acid methyl esters. Biodiesel is compatible with most diesel engines with minimal modification and can be blended with petroleum diesel to create a cleaner-burning fuel with lower emissions.
As the shift toward renewable energy sources gains momentum, biodiesel production is increasing. Raman spectroscopy offers numerous opportunities to optimize this process, from assessing incoming raw materials to monitoring production and confirming the quality of the final product.
Modular Raman System for Fuel Characterization
With the growing popularity of Raman spectroscopy, measurement options have expanded significantly. Users can choose from handheld systems like the IDRaman mini, fully integrated systems for lab use like the IDRaman reader, or modular systems comprising spectrometers, lasers, fiber optic probes, and sample holders.
Measurement Conditions
For those opting for a modular Raman spectrometer approach, several back-thinned CCD array detector options are available, including the Ventana, QE series, and Maya2000 series spectrometers. In this application, we utilized the Maya2000 Pro-NIR, preconfigured for Raman and low-light shortwave NIR applications. This setup includes the Maya2000 Pro-NIR spectrometer, a 785 nm Raman laser, a Raman-coupled fiber probe for 785 nm Raman, and a sample holder.
The 785 nm laser was chosen to avoid the fluorescence background often associated with shorter wavelength laser excitation. Acquisition parameters included a 500 millisecond integration time, with no scans averaged and no boxcar smoothing. Samples of corn oil (a potential diesel alternative) and petroleum-based diesel were analyzed in small glass vials to demonstrate Raman’s capability to distinguish diesel fuels and characterize biodiesel raw materials.
Results and Analysis
The Raman spectra for corn oil and diesel, displayed in Figure 1, reveal distinct differences in the fingerprint region from 500–2000 cm-1, despite some common hydrocarbon features. These distinctions allow for easy identification and characterization of the fuels. Notably, the spectrum for corn oil exhibits stearate peaks in the 1600-1800 cm-1 region, absent in the petroleum-based diesel spectrum.
Figure 1: Raman is an excellent method for distinguishing corn oil-based biodiesel fuels from petroleum-based diesel fuel.
Such spectral differences enable clear discrimination between fuels. Even samples with closely aligned spectral peaks can be distinguished by using a narrower slit in the spectrometer’s optical bench, achieving higher Raman shift resolution over a narrower spectral range.
Conclusion
Fuels, with their unique hydrocarbon compositions, are ideally suited for identification and characterization using Raman analysis. The detailed spectral features in fuel Raman spectra support a range of applications, including critical fuel parameter determination, fuel classification, and counterfeit fuel detection. The Maya2000 Pro-NIR, with its sensitivity in the NIR region, is particularly well-suited for Raman measurements using NIR laser excitation.
While the setup described here is one effective toolset for Raman measurements, numerous other configurations are available to accommodate different sample types and conditions. Ocean Optics’ QE series high sensitivity spectrometers, for instance, feature cooled back-thinned detectors to minimize dark noise during long integration times required for low-intensity Raman scattering detection.
Additionally, Raman excitation lasers (available in 532 nm and 785 nm) and a variety of Raman probes with built-in laser line filtering and shutters offer further customization. Probes designed for hostile environments, immersion in samples, and different focal lengths, as well as custom flow cells for monitoring flowing sample streams, enhance the versatility of Raman systems.
With these diverse options, the modular approach to Raman measurements allows for nearly limitless customization, meeting evolving measurement needs with ease.
Note:
This article was written some time ago. To ensure accuracy and relevance, consult our experts to determine the most suitable spectrometer for performing these measurements currently.
