2018
DOI: 10.1364/ol.43.003465
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Discrimination of bimetallic alloy targets using femtosecond filament-induced breakdown spectroscopy in standoff mode

Abstract: The femtosecond filament-induced breakdown spectroscopy (FIBS) technique coupled with principal component analysis (PCA) is demonstrated for standoff (ST) analysis of metals, alloys (Al, Cu, brass, stainless steel), and bimetallic strips (Ag@Cu, Ag@Au with varying weight percentages). The experiments were performed by analyzing the filament-produced plasma at ∼6.5  m from the laser. The plasma emissions were collected using a Schmidt-Cassegrain telescope (6″ f/10) at ∼8  m away. The variations in intensities o… Show more

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Cited by 20 publications
(7 citation statements)
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References 29 publications
(30 reference statements)
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“…Compared with other techniques, like atomic absorption spectroscopy and inductively coupled plasma optical emission spectroscopy, LIBS has some unique advantages including the capacity of direct analysis without a complex pretreatment of the sample, rapid response, and multiple elemental analysis ability. LIBS is suitable for special requirements of practical solid, [1][2][3][4] liquid, [5][6][7][8] and gas analyses. 9,10 For traditional LIBS systems, nanosecond (ns) pulse lasers are widely used.…”
Section: Introductionmentioning
confidence: 99%
“…Compared with other techniques, like atomic absorption spectroscopy and inductively coupled plasma optical emission spectroscopy, LIBS has some unique advantages including the capacity of direct analysis without a complex pretreatment of the sample, rapid response, and multiple elemental analysis ability. LIBS is suitable for special requirements of practical solid, [1][2][3][4] liquid, [5][6][7][8] and gas analyses. 9,10 For traditional LIBS systems, nanosecond (ns) pulse lasers are widely used.…”
Section: Introductionmentioning
confidence: 99%
“…Typically, the spectral data of characteristic lines are extracted from the spectra and used as a sample set to establish a suitable classification model. Currently, the most common algorithms used in LIBS analysis are principal component analysis (PCA), [82][83][84][85] linear discriminant analysis (LDA), [86][87][88] support vector machine (SVM), [89][90][91] random forest (RF), [92][93][94] and artificial neural networks (ANN). [95][96][97][98] For the classification of pollutants, these methods work equally well.…”
Section: Atmospheric Pollution Sourcesmentioning
confidence: 99%
“…Depending on the lens combinations one can focus the pulses at few meters to few hundreds of meters. We had earlier successfully investigated bimetallic targets (Ag@ Au, Ag@Cu) 40 and a set of six energetic imidazoles 41 in the same configuration. In both cases we could achieve excellent discrimination using the PCA.…”
Section: Discrimination Of Hems In St-fibs2 (Configuration 3) Using Femtosecond Filamentsmentioning
confidence: 99%