Determination of Octane Numbers and Reid Vapor Pressure of Commercial Petroleum Fuels Using FT-Raman Spectroscopy and Partial Least-Squares Regression Analysis

Cooper, John B.; Wise, Kent L.; Groves, J. R.; Welch, William T.

doi:10.1021/ac00118a011

Cited by 63 publications

(33 citation statements)

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“…Raman is expected to evaluate the lysozyme concentration changes in vapour diffusion hanging drop method with and without LangmuirBlodgett nanotemplate. Raman spectra have previously been subjected to quantitative infrared partial least-squares (PLS) models with remarkable success [4]. The PLS model generated correlates the spectral region from 2700 to 3600 cm -1 with the concentration (g/ ml) of lysozyme.…”

Section: Introductionmentioning

confidence: 99%

In situ Monitoring By Raman Spectroscopy of Lysozyme Conformation during “Nanotemplate” Induced Crystallization

Nicolini

Belmonte²,

Максимов³

et al. 2013

J Microb Biochem Technol

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Using Raman spectroscopy and lysozyme, this latter as model protein, we investigate the differences in protein conformation before and after LB nanotemplate-induced crystal nucleation and growth. It was found that the main difference in lysozyme conformation is associated to the higher amount of S-S bonds in lysozyme of LB crystals, probably in C-end of protein, resulting in the higher stiffness of the lysozyme molecules and LB crystal in a whole. Growth in size of LB crystal over time is also accompanied by the formation of S-S bonds. Atomic structure, determined by X-ray diffraction, correlates Raman spectroscopy results confirm the main differences between LB and classical crystals are in terms of water molecules environment previously associated to the increased radiation stability of LB crystals.

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Section: Introductionmentioning

confidence: 99%

In situ Monitoring By Raman Spectroscopy of Lysozyme Conformation during “Nanotemplate” Induced Crystallization

Nicolini

Belmonte²,

Максимов³

et al. 2013

J Microb Biochem Technol

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“…The resulting spectrum is similar to both the spectrum of the .525 8C boiling residue and of highly ordered graphite. All three spectra exhibit a strong peak at 1600 cm 2 1 , while the clay tailings spectrum also exhibits a weak, broad peak at 1380 cm 21 . No peaks were observed under these conditions in the UV Raman spectrum of an Australian kaolinite, a control clay sample.…”

Section: Resultsmentioning

confidence: 98%

UV Raman Spectroscopy of Oilsands-Derived Bitumen and Commercial Petroleum Products

et al. 2002

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Raman and resonance Raman spectroscopy with ultraviolet excitation were performed on several sample types of oilsands-derived bitumen, highly heterogeneous mixtures of hydrocarbons, and commercial gasoline samples. Only excitation wavelengths below ∼240 nm successfully yielded fluorescence-free Raman spectra on all of the samples tested. The spectra were surprisingly simple in the 800–1800 cm−1 region, with most of the samples yielding spectra containing only 2 bands. The results presented here tentatively suggest that ultraviolet (UV) Raman spectroscopy in the “fingerprint” spectral regions will be useful for the qualitative identification of saturate, mono-, bi-, tri-, and polycyclic aromatic hydrocarbons. Tentative marker bands for total aromatic, saturate, mono-, and bicyclic (or higher) aromatic hydrocarbons are clearly observed at ∼1600, <900, 1036, and ∼1380 cm−1, respectively. Observed relative intensities vary with the excitation wavelength from 220 to 234 nm, suggesting that some selectivity is achievable by wavelength tuning. Preliminary investigations of commercial gasoline samples indicate that UV Raman spectroscopy can be used for refinery/vendor identification of unknown gasoline samples.

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“…PLS is a multivariate regression method based on forming latent variables that maximize the covariance between the observed variables and the response variables [23] by emphasizing and utilizing the regions in the Raman spectrum that correlate mostly with product formation. By using PLS regression models built from Raman spectra, Cooper et al demonstrated accurate predictions of chemical and physical properties, including the octane number and vapor pressures of petrochemical solutions [24]. This was further demonstrated by Dearing et al who predicted physical properties of crude oil distillates when combining IR, Raman, and nuclear magnetic resonance (NMR) information into data-fused models [25].…”

Section: Introductionmentioning

confidence: 97%

Moffat-Swern Oxidation of Alcohols: Translating a Batch Reaction to a Continuous-Flow Reaction

Bleie¹,

Roberto²,

Dearing³

et al. 2015

J Flow Chem

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The Moffatt-Swern oxidation (MSO) is a multistep, versatile, metal-free reaction by which alcohols are transformed into aldehydes and ketones. Batch MSO requires low temperatures (−70°C) due to a highly exothermic reaction step that generates intermediates. This work shows that a rigorous investigation of the MSO in batch can be used as a stepping-stone to its implementation in a continuous-flow reactor (CFR). This work has two parts: the first part details the investigation of MSO in batch; the second covers the translation of the knowledge derived from batch to a CFR. The MSO batch reaction was performed under cryogenic conditions with real-time process monitoring. The reaction was monitored with Raman spectroscopy and could be tracked throughout the reaction. All concentrations were validated using offline high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). Two configurations of the CFR were produced. Configuration 1 used the traditional batch methodology in terms of reagent addition and reaction conditions. Configuration 2 used the information derived from the batch reaction, changing the order of the reagent addition and increasing the temperature of the reactor. Real-time quantitative monitoring of chemical yield in the CFR was demonstrated via Raman spectroscopy and partial least squares (PLS) regression modeling. Reaction yield was accurately predicted every 15 s, reducing the need for chromatographic validation once the model was built. Configuration 2 was shown to perform comparably to configuration 1 at low temperature and far outperforming it at higher temperatures. Both CFR configurations performed significantly better than the batch setup in terms of temperature and yield, as was expected.

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Determination of Octane Numbers and Reid Vapor Pressure of Commercial Petroleum Fuels Using FT-Raman Spectroscopy and Partial Least-Squares Regression Analysis

Cited by 63 publications

References 0 publications

In situ Monitoring By Raman Spectroscopy of Lysozyme Conformation during “Nanotemplate” Induced Crystallization

In situ Monitoring By Raman Spectroscopy of Lysozyme Conformation during “Nanotemplate” Induced Crystallization

UV Raman Spectroscopy of Oilsands-Derived Bitumen and Commercial Petroleum Products

Moffat-Swern Oxidation of Alcohols: Translating a Batch Reaction to a Continuous-Flow Reaction

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