Introduction of a novel fluorescence based method for the composition estimation of petroleum fuel–biofuel blends

Prakash, John; Mishra, Ashok Kumar

doi:10.1016/j.fuel.2013.02.043

Cited by 13 publications

(4 citation statements)

References 31 publications

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“…The concentration of biodiesel in blended fuels has been measured using various spectroscopic techniques, including infrared [3,4,5,6,7] and fluorescence [8,9] spectroscopy combined with multivariate analysis methods, such as Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), or Partial Least Squares (PLS). Electrospray ionization mass spectrometry has been combined with chemometric methods to analyze different feedstocks and blend compositions of biodiesel [10,11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of single and multi-feedstock biodiesel – diesel blends using GCMS and chemometric methods

Flood

Connolly

Comiskey

et al. 2016

Fuel

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Single and multi-feedstock biodiesel-diesel blends were evaluated using gas chromatography mass spectrometry along with several unsupervised and supervised chemometric methods. Peak areas of diesel alkane components and/or biodiesel fatty acid methyl ester (FAME) components were evaluated using Principal Component Analysis (PCA), k nearest neighbors (kNN), soft independent modeling of class analogy (SIMCA), and partial least squares (PLS) analysis. Using PCA (an unsupervised method), samples clustered based on feedstock type (soybean, waste grease, canola, tallow) and concentration (diesel, B2-B100). Using the supervised chemometric methods, feedstock type and concentration were validated for the training set and predicted for several unknown test samples. Concentration and feedstock were predicted using kNN, while concentration alone was predicted using SIMCA. PLS also allowed prediction of concentration but the success of the prediction heavily depended on the training model used. In addition, multi-feedstock fuel blends created from 2 and 3 feedstock components (soybean, canola, tallow) were evaluated with PCA, kNN, and SIMCA. Samples clustered based on concentration and feedstock makeup/ratio in PCA. Using kNN and SIMCA, multifeedstock blends were predicted based on concentration, while kNN could be used to predict relative ratio of multiple feedstocks. The results demonstrate the utility of chemometric

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Section: Introductionmentioning

confidence: 99%

Evaluation of single and multi-feedstock biodiesel – diesel blends using GCMS and chemometric methods

Flood

Connolly

Comiskey

et al. 2016

Fuel

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“…The reduction of data dimension (3D to 2D), fast data acquisition, spectral veracity, sim Dip Probe Fiber Optic spectrometerplicity in analysis, cost-effectiveness and portability are additional features of the WLEF method. The perks of WLEF are already exploited in monitoring quality of fuel blends 23 , biofluids 24 , etc.…”

Section: Wlef Instrumentation and Data Acquisitionmentioning

confidence: 99%

Simultaneous Quantification of Multiple Polycyclic Aromatic Hydrocarbons in Aqueous Media using Micelle Assisted White Light Excitation Fluorescence

Prakash

Mishra

2020

Sci Rep

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“…The robustness of the WLEF technique and its compatibility towards multivariate techniques were already explored in the analysis of multifluorophores [30]. WLEF could analyze simple fluorophores or complex multifluorophores without any change in instrument configuration [31]. Also, the WLEF technique does not need a very high power light source, which reduces the possibility of photobleaching and means it can be used for biological analytes [32].…”

Section: Theory Of Wlefmentioning

confidence: 99%

Fabrication, optimization and application of a dip-probe fluorescence spectrometer based on white-light excitation fluorescence

Prakash¹,

Mishra²

2013

Meas. Sci. Technol.

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A dip-probe adapter was designed for easy analysis of complex multifluorophoric systems. The newly fabricated fiber optic compatible spectrometer design with dip-probe adapter could reach and analyze fluorophores kept at a distance from the analyzer. The new design and its parameters were optimized using standard fluorophores to get an optimal spectral response. This white-light excitation fluorescence (WLEF) based spectrometer could analyze any fluorophoric system rapidly without changing the instrument configuration. Fuel–oil blends such as petrol–2T oil and petrol–4T oil were precisely quantified with high accuracy (0.3% error) using a WLEF–multivariate analysis combination.

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Introduction of a novel fluorescence based method for the composition estimation of petroleum fuel–biofuel blends

Cited by 13 publications

References 31 publications

Evaluation of single and multi-feedstock biodiesel – diesel blends using GCMS and chemometric methods

Evaluation of single and multi-feedstock biodiesel – diesel blends using GCMS and chemometric methods

Simultaneous Quantification of Multiple Polycyclic Aromatic Hydrocarbons in Aqueous Media using Micelle Assisted White Light Excitation Fluorescence

Fabrication, optimization and application of a dip-probe fluorescence spectrometer based on white-light excitation fluorescence

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