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Motor Oil Classification Based on Time-Resolved Fluorescence
Author(s) -
Taotao Mu,
Siying Chen,
Yinchao Zhang,
Pan Guo,
He Chen,
Fandong Meng
Publication year - 2014
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0100555
Subject(s) - fluorescence , motor oil , laser induced fluorescence , biological system , steady state (chemistry) , computer science , analytical chemistry (journal) , chemistry , pattern recognition (psychology) , materials science , artificial intelligence , chromatography , optics , physics , biology , thermodynamics
A time-resolved fluorescence (TRF) technique is presented for classifying motor oils. The system is constructed with a third harmonic Nd:YAG laser, a spectrometer, and an intensified charge coupled device (ICCD) camera. Steady-state and time-resolved fluorescence (TRF) measurements are reported for several motor oils. It is found that steady-state fluorescence is insufficient to distinguish the motor oil samples. Then contour diagrams of TRF intensities (CDTRFIs) are acquired to serve as unique fingerprints to identify motor oils by using the distinct TRF of motor oils. CDTRFIs are preferable to steady-state fluorescence spectra for classifying different motor oils, making CDTRFIs a particularly choice for the development of fluorescence-based methods for the discrimination and characterization of motor oils. The two-dimensional fluorescence contour diagrams contain more information, not only the changing shapes of the LIF spectra but also the relative intensity. The results indicate that motor oils can be differentiated based on the new proposed method, which provides reliable methods for analyzing and classifying motor oils.

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