Quantification of ethanol in ethanol-petrol and biodiesel in biodiesel-diesel blends using fluorescence spectroscopy and multivariate methods.

Clicks: 403
ID: 109069
2012
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Popular

Ranked #10 of 194 articles by views in Journal of Fluorescence

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 194 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Ethanol blended petrol and biodiesel blended diesel are being introduced in many countries to meet the increasing demand of hydrocarbon fuels. However, technological limitations of current vehicle engine do not allow ethanol and biodiesel percentages in the blended fuel to be increased beyond a certain level. As a result quantification of ethanol in blended petrol and biodiesel in blended diesel becomes an important issue. In this work, calibration models for the quantification of ethanol in the ethanol-petrol and biodiesel in the biodiesel-diesel blends of a particular batch were made using the combination of synchronous fluorescence spectroscopy (SFS) with principal component regression (PCR) and partial least square (PLS) and excitation emission matrix fluorescence (EEMF) with N-way Partial least square (N-PLS) and unfolded-PLS. The PCR, PLS, N-PLS and unfolded-PLS calibration models were evaluated through measures like root mean square error of cross-validation (RMSECV), root mean square error of calibration (RMSEC) and square of the correlation coefficient (R(2)). The prediction abilities of the models were tested using a testing set of ethanol-petrol and biodiesel-diesel blends of known ethanol and biodiesel concentrations, error in the predictions made by the models were found to be less than 2%. The obtained calibration models are highly robust and capable of estimating low as well as high concentrations of ethanol and biodiesel.
Reference Key
kumar2012quantificationjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kumar, Keshav;Mishra, Ashok K;
Journal Journal of Fluorescence
Year 2012
DOI
10.1007/s10895-011-0964-6
URL
Keywords
child principal component analysis pca ffq food frequency questionnaire dietary patterns prenatal cbcl externalising problems gee internalising problems child behaviour checklist generalised estimating equations

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.