Spectrochimica Acta Part B 59 (2004) 567–575
Large area mapping of non-metallic inclusions in stainless steel by an
automated system based on laser ablation夞
´ M.P. Mateo, J.J. Laserna*
L.M. Cabalın,
´
´
Department of Analytical Chemistry, Faculty of Sciences, University of Malaga,
E-29071 Malaga,
Spain
Received 1 November 2003; accepted 15 January 2004
Abstract
Large area compositional mapping ()6 mm2 ) using a fast and automated system based on laser-induced plasma spectrometry
is presented. The second harmonic of a flat top Nd:YAG laser beam was used to generate a microline plasma on the sample
surface. The emitted light from the microline plasma was imaged onto the entrance slit of an imaging spectrograph and was
detected by an intensified charge-coupled device to generate a spatially and spectrally resolved data set. Individual LIPS images,
each measuring roughly 2500=2500 mm with spatial resolution of 50 mm between adjacent craters and 4.8 mm along the
microline are presented. These large area maps were acquired in less than 1 min. Steel samples containing MnS and TiN
inclusions were chosen as the most adequate for this study. The results are presented for the characterization of inclusionary
material in stainless steel products in terms of morphology, distribution and abundance.
䊚 2004 Elsevier B.V. All rights reserved.
Keywords: Laser-induced plasma spectrometry; Stainless steel; Materials characterization; Large area mapping
1. Introduction
Stainless steel plays an important role in all emerging
technologies. However, steel melt usually contains insoluble components in form of particles which appear as
inclusions in the solid material. The main part of these
impurities in steel (oxides, sulfides and nitrides) are
formed by reactions of elements dissolved in the steel
(endogeneous inclusions) or by contamination of the
steel by the slag or the refractory materials (exogeneous
inclusions) and are the so-called non-metallic inclusions
w1–3x. The dimension of these inclusions is within a
range of 0.1–100 mm. Although the presence of inclusions with well defined composition (in machinable
steels especially) can introduce beneficial effects w4x, in
general for most steel grades the presence of inclusions
can cause surface defects or deteriorate the mechanical
properties (castability, deformability and brittle fracture,
hardness, corrosion, fatigue strength etc.) w5x. The det夞 This paper was presented at the Colloquium Spectroscopicum
Internationale XXXIII, held in Granada, Spain, 7–12 September 2003
and is published in the special issue of Spectrochimica Acta Part B,
dedicated to that conference.
*Corresponding author. Tel.: q34-952131881; fax: q34952132000.
E-mail address: laserna@uma.es (J.J. Laserna).
rimental effects of inclusions not only depend on their
sizes, but also on their ductility and fracture behavior
during the rolling process. Of all the inclusions, the hard
and brittle inclusions produce the most harmful consequence on the properties of steels. For this reason, the
characterization of non-metallic inclusions in steel in
terms of number, size, shape, chemical composition and
spatial distribution is an essential requirement on metallurgical process technology in order to determine their
origin and to control their formation, and to produce a
final product of high quality. Methodologies employed
to assess steel cleanliness depend on the size of the
impurities, the time available for assessment (on-line or
off-line), the degree of detail needed and the state of
the steel, e.g. liquid or solidified steel w6x. However,
most of these techniques are time consuming, not proper
for routine process control and have limited applicability
for steel cleanliness assessment of large sample areas.
Based on these requirements, the development of fast,
reliable and accurate methods for the characterization of
inclusions during the production process becomes a
need.
At present, laser induced plasma spectrometry (LIPS)
has become an important tool in the steel industry
allowing solving a large number of analytical problems.
0584-8547/04/$ - see front matter 䊚 2004 Elsevier B.V. All rights reserved.
doi:10.1016/j.sab.2004.01.014
568
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
Rapid in situ analysis of steel products without sample
preparation and micro and macromapping over several
centimeters by scanning the optical system or moving
the sample on a translation stage are interesting capabilities of LIPS. This technique has been applied successfully in bulk w7–11x and quantitative analysis w12–14x,
analysis of liquid w15,16x and high temperature steel
w17x, surface topography studies w18,19x, depth profiling
of coated steel w20–24x, automation w25,26x and routine
industrial applications for quality assessment w27x and
remote analysis w17,28–31x. For these applications,
numerous experimental approaches have been proposed
to achieve better analytical performance and to improve
surface sensitivity, lateral resolution, detection power,
analysis time and precision in materials analysis.
Advancement in the investigations has resulted in the
development of a new approach for fast generation of
compositional maps from large areas. The basic idea
relies on focusing the laser beam with a cylindrical lens
to produce a long and narrow microline plasma in a
direction parallel to the spectrometer entrance slit and
to exploit both the multielemental and the spatial resolving capabilities of charge-coupled device (CCD) detectors. This focusing and acquisition method provides
several advantages compared to conventional LIP spectrometry, including the improvement of data collection
speed due to the reduction of laser pulse number
necessary for generating LIPS chemical maps. This work
discusses how large area compositional mapping using
a fast and automated line-focused LIPS system can be
successfully used to provide qualitative and quantitative
information of elemental distribution of inclusionary
material in stainless steel products. Two sampling procedures for obtaining chemical maps of good quality
have been evaluated. Large area chemical maps of
manganese and titanium in stainless steel products are
presented.
2. Experimental
2.1. Instrumentation
The LIPS experimental set-up employed in this study
has been previously reported w32–35x and therefore,
only some details are given here. The second harmonic
(532 nm) of a pulsed Q-Switched Nd:YAG laser with
top hat energy profile (Spectron, model SL 284, pulse
width 5 ns, beam diameter 4 mm) was used to ablate
the sample in air at atmospheric pressure. The output
energy of the laser beam was 52 mJ per pulse at a
repetition rate of 2 Hz, which is the maximum allowed
by the detector and the frame grabber used. The beam
was three-fold expanded by an optical system consisting
of two lenses, a 25-mm focal length concave lens and
a 75-mm focal length convex lens. The beam was then
focused to a line by a cylindrical lens with a focal
length of 50 mm onto the sample surface. With this
optical configuration, the dimensions of the obtained
microline crater were of 14000 mm in length=48 mm
in width, however, it should be noted that only 2500
mm of the cited length was analyzed. A planoconvex
quartz lens with a focal length of 100 mm was used to
image the microline plasma onto the entrance slit of a
0.5-m focal length Czerny–Turner imaging spectrograph
(Chromex, model 500 IS, fy噛 8, fitted with indexable
gratings of 300, 1200 and 2400 grooves mmy1). Spectral
emission was detected by an intensified solid-state twodimensional charge-coupled device (ICCD, Stanford
Computer Optics, model 4Quik 05) with 768=512
pixels, each 7.8=8.7 mm2. This configuration provides
a spectral window of ;15 nm and a spectral resolution
of 0.02 nm pixely1, using an entrance slit width of 20
mm and the grating of 2400 grooves mmy1. The CCD
active area was 6=4.4 mm2. Operation of the detector
was controlled by a personal computer with 4Spec
software. For monitoring MnS and TiN inclusions in
steel, spectral windows centered at 476.0 nm and 388.3
nm, respectively, were used. However, it was assumed
that detection by LIPS of Mn or Ti indicated the
presence of MnS or TiN inclusions in steel. Delay time
of 500 ns and integration time of 1000 ns were employed
in these experiments. For data acquisition, the CCD
system was triggered by an output TTL pulse from the
laser Q-switch system. The sample was placed on two
crossed motorized stages (Physik Instrumente). The
stages were computer controlled which allowed exact
movement of the sample in both x and y directions.
Laser trigger was controlled externally by a digital
delayypulse generator (Stanford Research System Model
DG535). To automate acquisition of large chemical map
data a laboratory software was developed which allowed
the exact synchronization between the motorized stage
movement and laser firing. Communication between
devices was carried out by an IEEE 488 general purpose
interface bus (GPIB). Stored data were treated by a lab
developed software, which reduced the volume of
acquired data to a XY matrix for each element of interest.
For compositional mapping, these matrices were plotted
by means of commercial imaging analysis data software.
The area fraction occupied by inclusions regarding the
total map area was calculated with a commercial image
analysis software package (Visilog 5.2).
2.2. Samples
In order to study the effect of stainless steel manufacturing on the morphology, size and distribution of
inclusionary material, three steel products (cold rolled
sheet, bar and wire rod) containing each a single type
of inclusion were prepared and provided by Acerinox,
S.A. AISI 303, AISI 315 and AISI 319 steel classes
have been chosen since they contain a unique kind of
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
569
Table 1
Chemical composition of AISI 303, AISI 315 and AISI 319 stainless steel materials
Type of
inclusion
Type of
material
MnS
TiN
TiN
AISI 303
AISI 315
AISI 319
*
Chemical composition (wt.%)*
Si
Mn
Ni
Cr
Ti
C
S
N
0.25
0.46
0.65
1.85
1.75
1.68
8.70
9.15
9.65
17.7
17.3
17.4
)0.01
0.36
0.26
0.05
0.02
0.02
0.319
0.001
0.026
0.03
0.01
0.02
These values were measured by X-ray fluorescence spectrometry in Acerinox S.A.
inclusion, manganese sulfide in the case of AISI 303,
and titanium nitride in AISI 315 and AISI 319 steel.
Samples were characterized by scanning electron
microscopy with a microanalysis EDX system and by
optical microscopy. The chemical composition of these
stainless steel grades measured by X-ray fluorescence
spectrometry is shown in Table 1.
To study the spatial distribution inclusionary material,
steel cold rolled sheets 40=30 mm2 with a thickness of
6 mm were analyzed. The procedure for obtaining steel
bar and steel wire rod samples was almost similar in
both cases. Samples of 30–40-mm length, with diameters of 17–24 mm for steel bars and 10 mm for steel
wire rods, were cut by means of a mechanical sawing.
Then, the steel pieces were embedded in resin in order
to obtain a laboratory sample. In the case of bars before
this last step the steel pieces were cut lengthwise.
Finally, the steel samples were polished with a 1000 grit
sandpaper to produce smoother surface, washed several
times with tap water and dried and their metallurgical
structures were developed.
According to their behavior during rolling, inclusions
can be divided into two broad classes: non-deformable
inclusions and deformable inclusions. The typical
appearance of soft MnS inclusions in manufactured AISI
303 steels is presented in Fig. 1. As shown in steel cold
rolled sheet the manganese sulfide inclusions are mainly
globular. In contrast, the shape of these inclusions in
bar and wire rod samples is narrower and longer than
in cold rolled sheet since such inclusions exhibit high
ductibility at steel rolling temperature and deform and
elongate as the steel is rolled. In the case of AISI 315
(for cold rolled sheet) and AISI 319 steel (for steel bar
and steel wire rod), the distribution and aspect of TiN
inclusions are similar for the three products and maintain
their original shape as the steel is deformed. This fact
joins to the hard and brittle nature of TiN species
resulting in a breaking of inclusions during the manufacturing process and consequently the shape of TiN
inclusions is non-uniform. Fig. 2 shows some details of
this type of inclusions in AISI 315 and AISI 319 steels.
3. Results and discussion
3.1. Large area compositional LIPS maps
Large area microline LIPS maps (defined in this work
as LIPS maps of area approx. 6 mm2 in size) were
performed to obtain the characterization and quantification of inclusionary material during processing of steel.
Fig. 1. Photographs of MnS inclusions in manufactured AISI 303 steels (a) cold rolled sheet, (b) bar and (c) wire rod, obtained by optical
microscopy.
570
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
Fig. 2. Photographs of TiN inclusions in manufactured AISI 315 and AISI 319 steels (a) cold rolled sheet, (b) bar and (c) wire rod, obtained by
optical microscopy.
The objective of making such large maps is to obtain
whole information of the surface characteristics of the
sample. As the distribution of inclusions in steel is
heterogeneous, restricting the analysis to small areas
could lead to results non-representative of the sample.
For this reason, chemical images were constructed using
the microline imaging arrangement described w32–35x
which permits to obtain spectral and spatial information
simultaneously of a large surface region from each laser
pulse. With this focusing configuration, long and narrow
craters were produced on the sample surface and each
pixel of the CCD detector along the spatial direction
corresponds to a particular position on the microline
focus (the sampled area).
The greatest challenge in making large area microline
LIPS maps is to obtain images with high lateral resolution and good quality. This can be achieved by combining the net intensity of an element along the microline
plasma obtained from each adjacent position on the
sample, with their spatial coordinates. With the purpose
of generating large chemical images of good quality, a
study of the influence of sampling procedure by using
the microline LIPS approach was carried out with both
steel bar and steel wire rod samples. The two sampling
protocols described in Fig. 3 were evaluated. Chemical
maps of manufactured AISI 303 steel were constructed
by focusing the microline laser beam on the sample
surface at perpendicular and parallel directions to the
rolling of steel. Two large LIPS images of MnS inclusions corresponding to two different sample areas of the
same size (2500=2500 mm2) obtained with both methods in a wire rod sample are compared in Fig. 4.
Chemical maps were conducted with a single laser shot
per position and were realized from 50 single laser shots
with a lateral displacement of 50 mm between adjacent
microline craters. The total analysis time for generating
the chemical maps including time intervals for deceleration and acceleration of the X stage was 55 s. In this
experiment, the stage was moved and stopped for each
X position. The Y direction in the compositional maps
corresponds to the spatial resolution along the microline,
which depends on the number of pixels of CCD detector
(512), the pixel size (8.7 mm), the optical magnification
and plasma expansion. If all these parameters are taken
in account, it was estimated that each pixel represents
;4.8 mm of the microline length w35x. In the chemical
images of Fig. 4, differences in elemental distribution
are presented in binary code to remark the location of
inclusions. The binary code was established by using an
image processing software, which assigns the black color
to any net intensity of Mn, which is three times higher
than the net intensity of the element in the matrix. Thus,
dark zones indicate the presence of MnS inclusions in
steel, while white areas correspond to the steel matrix.
This criterion was used for generating further chemical
images. The results demonstrate that chemical images
obtained by orientating the microline laser beam parallel
to the rolling direction represent more accurately the
dimension and shape of the MnS inclusions in AISI 303
steel than those obtained with the second sampling
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
571
Fig. 3. Description of sampling procedures evaluated for characterization of inclusionary material in steel. A detail of the microline craters
generated in an AISI 303 steel bar (a) perpendicular to the rolling direction and (b) parallel to the rolling direction showing elongated MnS
inclusions in steel is also presented.
Fig. 4. Comparison of two large LIPS maps of MnS inclusions in AISI 303 steel wire rod obtained by both sampling protocols: (a) microline
plasma perpendicular to the rolling direction and (b) microline plasma parallel to the rolling direction. Plotted data correspond to intensity
distribution of Mn (I) 482.352 nm emission line and were acquired by single laser shot on each position. The mapped area was 2500=2500
mm2. Experimental conditions: laser pulse energy 52 mJ, delay time 500 ns and integration time 1000 ns.
572
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
Fig. 5. Microline LIPS images corresponding to the spatial distribution of MnS inclusions in manufactured AISI 303 steels: (a) cold rolled sheet,
(b) steel bar and (c) wire rod shown in Fig. 1. Net intensity of the Mn (I) 482.352 nm line is presented in binary code. The mapped area was
2400=2500 mm2. Other experimental conditions as in Fig. 4.
procedure (perpendicular to the rolling direction). This
fact can be attributed to the better spatial resolution
obtained along the microline crater (approx. 5 mm) than
that obtained between consecutive microlines (50 mm).
The performance of the automated microline approach
for large compositional mapping was tested by studying
the deformation of inclusions in steel products during
rolling. Two types of non-metallic inclusions found in
manufactured steel including a soft one as MnS and
hard one as TiN were characterized. These specimens
were chosen due to present different deformability
features.
A comparison of the large LIPS images corresponding
to the distribution of MnS inclusions in AISI 303 and
TiN inclusions in AISI 315 and AISI 319 steel products
is plotted in Figs. 5 and 6, respectively. These distribution maps were accomplished from single laser shots
per position after cleaning the surface with one laser
shot. A total area of 2400=2500 mm2 was sampled in
a sequence of 49 positions separated by 50 mm. The
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
573
Fig. 6. LIPS maps of TiN inclusions in manufactured AISI 315 and AISI 319 steels: (a) cold rolled sheet, (b) steel bar and (c) wire rod shown
in Fig. 2 using microline imaging approach. Plotted data correspond to net intensity of Ti (I) 395.821 nm emission line. The mapped area was
2400=2500 mm2. Other experimental conditions as in Fig. 4.
large maps required a total acquisition time of 54 s.
These large area maps exhibit whole information of
different behavior of inclusions in stainless steel products as manifested in the differences in shape and
abundance of inclusionary material and indicate the
good correspondence between the chemical maps
obtained by LIPS and the results observed by optical
microscopy. As shown in the case of AISI 303, the
distribution and appearance of MnS inclusion change
during the processing of the steel and these differences
are more acute in bar and wire rod samples, where the
inclusions present an elongated shape and are more
abundant. However, large area composition maps of TiN
inclusions in AISI 315 and AISI 319 steel samples
demonstrated that the analyzed inclusions exhibit a
similar distribution in the three steel products and their
dispersion and aspect differ of MnS inclusions in AISI
303 steel. These maps indicate the different behavior of
both inclusionary materials in steel during the manufacturing process and show clearly that the distribution of
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
574
Table 2
Percentage of MnS and TiN inclusions in steel product (cold rolled
sheet, steel bar and wire rod)
Type of
inclusion
Type of
material
MnS
TiN
TiN
AISI 303
AISI 315
AISI 319
Inclusionary material content (%)*
Cold rolled sheet
Bar
Wire rod
1.4
1.3
–
25
–
1.4
11.6
–
1.1
Data were estimated from LIPS maps of Figs. 5 and 6, respectively.
*
The percentage represents the area fraction occupied by
inclusions.
inclusionary material is not homogenous in the steel
products.
3.2. Quantification of MnS and TiN inclusions content
(area fraction) in stainless steel
Image processing of the large area compositional
maps enable extraction of quantitative information of
inclusionary material. Each position in the map has its
own compositional value defined by its binary code.
The inclusion content present in the three steel products
has been calculated. The resulting data expressed as the
percentage area fraction occupied by MnS and TiN
inclusions in the total area analyzed (2400=2500 mm2)
from the large maps of Figs. 5 and 6 are summarized in
Table 2. Similar values were obtained when other zones
of the samples were analyzed. The percentage of inclusionary material in AISI 303 varied in the range of 1.0–
1.4%, 17.6–25.0% and 9.8–11.6% for cold rolled sheet,
bar and wire rod, respectively. In the case of AISI 315
and AISI 319 steels the content of TiN inclusions is
similar for the three steel products and varied in the
range of 1.1–1.3%, 0.6–1.4% and 1.1–2.3%, respectively. The results from Table 2 indicate that the abundance of MnS inclusions in surface varies considerably
from sample-to-sample and reaches a maximum value
of ca. 25% for the steel bar. However, only 11.6% and
1.4% of the sampled area contain inclusionary material
for wire rod and for cold rolled sheet, respectively. In
the case of AISI 315 and AISI 319 steels, the content
of TiN inclusions is similar for the three steel products
(ca. 1.2%), significantly lower than those observed for
AISI 303 steel samples. However, it should be noted
than the percentage area fraction occupied by the inclusionary material in steel products has been calculated
assuming a lateral resolution of 50 mm, which is defined
by the crater width. In this sense, the values in Table 2
could be over-estimated, mostly when inclusions much
smaller than 50 mm are present in the analyzed surface.
4. Conclusions
Large area compositional mapping using an automated
system based on laser ablation has been employed to
characterize and quantify inclusionary material in pro-
cess steel samples. High quality large area compositional
LIPS maps with good lateral resolution (50 mm between
adjacent microlines and 4.8 mm along the microline) of
the steel products presenting two types of inclusions
have been performed. The maps, which cover areas of
approximately 6 mm2, were acquired in less than 1 min
and provide information on the morphology, and distribution of inclusions during rolling of stainless steel. By
applying image processing techniques to the maps, the
percentage of area occupied by a single inclusion type
in steel can be determined. The results indicate that the
automated microline imaging LIPS technique allows the
steel manufacturers to obtain a complete overview of
the quality of their products. This method applied to
different steel grades provides crucial information on
steel cleanness. This fact is especially outstanding when
the characterization of large areas is required.
Acknowledgments
One of the authors (M.P.M.) acknowledges the fel´ de Estado de Universilowship provided by Secretarıa
´
dades, Investigacion y Desarrollo of Spain. This work
was supported by Project BQU2001-1854 of the Min´ Secretarıa
´ de Estado de
isterio de Ciencia y Tecnologıa,
´
´
´
Polıtica Cientıfica y Tecnologica of Spain and by the
ECSC under the contract 7210.PDy230. The authors
´
also acknowledge Acerinox S.A. (Los Barrios, Cadiz,
Spain) for providing the stainless steel samples and for
sample characterization by EDX and optical microscopy.
References
w1x R. Kiessling, N. Lange, Non-metallic Inclusions in Steel,
Metals Society, London, 1978.
w2x R. Kiessling, Non-metallic Inclusions in Steel. Part IV, The
Institute of Materials, London, 1989.
w3x N.A. Mcpherson, A. Mclean, Continuous casting, Non-metallic
Inclusions in Continuously Cast Steel, 7,, The Iron and Steel
Society, Hill Road, 1995.
w4x C. Gatellier, H. Gaye, J. Lehmann, J.N. Pontoire, P.V. Riboud,
Physicochemical aspects of the behavior of inclusions in steels,
Steel Res. 6 (1993) 87.
w5x M. Wintz, M. Bobadilla, J. Lehmann, H. Gaye, Experimental
study and modeling of the precipitation of non-metallic inclusions during solidification of steel, ISIJ Int. 35 (1995) 715.
w6x H.V. Atkinson, G. Shi, Characterization of inclusions in clean
steels: a review including the statistics of extremes methods,
Prog. Mater. Sci. 48 (2003) 457.
w7x A. Gonzalez,
´
M. Ortiz, J. Campos, Determination of sulfur
content in steel by laser-produced plasma atomic emission
spectroscopy, Appl. Spectrosc. 49 (1995) 1632.
w8x R. Sattmann, V. Sturm, R. Noll, Laser-induced breakdown
spectroscopy of steel samples using multiple Q-switch Nd:YAG
laser pulses, J. Phys. D: Appl. Phys. 28 (1995) 2181.
w9x M. Hemmerlin, R. Meilland, H. Falk, P. Wintjens, L. Paulard,
Applications of vacuum ultraviolet laser-induced breakdown
spectrometry for steel analysis – comparison with spark-optical
emission spectrometry figures of merit, Spectrochim. Acta Part
B 56 (2001) 661.
´ et al. / Spectrochimica Acta Part B 59 (2004) 567–575
L.M. Cabalın
w10x V. Sturm, L. Peter, R. Noll, Steel analysis with laser-induced
breakdown spectrometry in the vacuum ultraviolet, Appl. Spectrosc. 54 (2000) 1275.
w11x C. Chaleard,
´
P. Mauchien, N. Andre, J. Uebbing, J.L. Lacour,
C. Geertsen, Correction of matrix effects in quantitative elemental analysis with laser-ablation optical-emission spectrometry, J. Anal. Atom. Spectrom. 12 (1997) 183.
w12x C. Aragon,
´ J.A. Aguilera, F. Penalba,
˜
Improvements in quantitative analysis of steel composition by laser-induced breakdown spectroscopy at atmospheric pressure using an infrared
Nd:YAG laser, Appl. Spectrosc. 53 (1999) 1259.
w13x I. Bassiotis, A. Diamantopoulou, A. Giannoudakos, F. RoubaniKalantzopoulou, M. Kompitsas, Effects of experimental parameters in quantitative analysis of steel alloy by laser-induced
breakdown spectroscopy, Spectrochim. Acta Part B 56 (2001)
671.
w14x L.M. Cabalın,
´ D. Romero, C.C. Garcıa,
´ J.M. Baena, J.J.
Laserna, Time-resolved laser-induced plasma spectrometry for
determination of minor elements in steelmaking process samples, Anal. Bioanal. Chem. 372 (2002) 352.
w15x J. Gruber, J. Heitz, H. Strasser, D. Bauerle,
¨
N. Ramaseder,
Rapid in-situ analysis of liquid steel by laser-induced breakdown spectroscopy, Spectrochim. Acta Part B 56 (2001) 685.
w16x C.J. Lorenzen, C. Carlhoff, U. Hahn, M. Jogwich, Applications
of laser-induced emission spectral-analysis for industrial-process and quality-control, J. Anal. Atom. Spectrom. 7 (1992)
1029.
w17x S. Palanco, L.M. Cabalın,
´ D. Romero, J.J. Laserna, Infrared
laser ablation and atomic emission spectrometry of stainless
steel at high temperatures, J. Anal. Atom. Spectrom. 14 (1999)
1883.
w18x L.M. Cabalın,
´ D. Romero, J.M. Baena, J.J. Laserna, Effect of
surface topography in the characterization of stainless steel
using laser-induced breakdown spectrometry, Surf. Interface
Anal. 27 (1999) 805.
w19x X. Mao, W.T. Chan, R.E. Russo, Influence of sample surface
condition on chemical-analysis using laser-ablation inductivelycoupled plasma-atomic emission-spectroscopy, Appl. Spectrosc. 51 (1997) 1047.
w20x C.C. Garcıa,
´ M. Corral, J.M. Vadillo, J.J. Laserna, Angleresolved laser-induced breakdown spectrometry for depth profiling of coated materials, Appl. Spectrosc. 54 (2000) 1027.
w21x D.R. Anderson, C.W. McLeod, T. English, A.T. Smith, Depth
profile studies using laser-induced plasma emission spectrometry, Appl. Spectrosc. 49 (1995) 691.
w22x J.M. Vadillo, J.J. Laserna, Depth-resolved analysis of multilayered samples by laser-induced breakdown spectrometry, J.
Anal. Atom. Spectrom. 12 (1997) 859.
575
w23x J.M. Vadillo, C.C. Garcıa,
´ S. Palanco, J.J. Laserna, Nanometric
range depth-resolved analysis of coated-steels using laserinduced breakdown spectrometry with a 308 nm collimated
beam, J. Anal. Atom. Spectrom. 13 (1998) 793.
w24x L. St-Onge, M. Sabsabi, Towards quantitative depth-profile
analysis using laser-induced plasma spectroscopy: investigation
of galvannealed coatings on steel, Spectrochim. Acta Part B
55 (2000) 299.
w25x S. Palanco, J.J. Laserna, Full automation of a laser-induced
breakdown spectrometer for quality assessment in the steel
industry with sample handling, surface preparation and quantitative analysis capabilities, J. Anal. Atom. Spectrom. 15
(2000) 1321.
w26x I.B. Gornushkin, B.W. Smith, H. Nasajpour, J.D. Winefordner,
Identification of solid materials by correlation-analysis using a
microscopic laser-induced plasma spectrometer, Anal. Chem.
71 (1999) 5157.
w27x R. Noll, H. Bette, A. Brysch, M. Kraushaar, I. Monch,
¨
L.
Peter, V. Sturm, Laser-induced breakdown spectrometry –
applications for production control and quality assurance in the
steel industry, Spectrochim. Acta Part B 56 (2001) 637.
w28x S. Palanco, J.M. Baena, J.J. Laserna, Open-path laser-induced
plasma spectrometry for remote analytical measurements on
solid surfaces, Spectrochim. Acta Part B 57 (2002) 591.
w29x D.A. Cremers, J.E. Barefield, A.C. Kostelo, Remote elemental
analysis by laser-induced breakdown spectroscopy using a
fiber-optic cable, Appl. Spectrosc. 49 (1995) 857.
w30x C.M. Davies, H.H. Telle, D.J. Montgomery, R.E. Corbett,
Quantitative-analysis using remote laser-induced breakdown
spectroscopy (LIBS), Spectrochim. Acta Part B 50 (1995)
1059.
w31x J.M. Vadillo, P.L. Garcıa,
´ S. Palanco, D. Romero, J.M. Baena,
J.J. Laserna, Remote, real-time, on-line monitoring of hightemperature simples by non-invasive open-path laser plasma
spectrometry, Anal. Bioanal. Chem. 375 (2003) 1144.
w32x M.P. Mateo, L.M. Cabalın,
´ J.M. Baena, J.J. Laserna, Surface
interaction and chemical imaging spectrometry induced with a
line-focused laser beam, Spectrochim. Acta B 57 (2002) 601.
w33x L.M. Cabalın,
´ M.P. Mateo, J.J. Laserna, Chemical maps of
patterned samples by microline-imaging laser-induced plasma
spectrometry, Surf. Interface Anal. 35 (2003) 263.
w34x M.P. Mateo, L.M. Cabalın,
´ J.J. Laserna, Chemical imaging
using microline laser ablation: performance comparison of
gaussian and flat top lasers, Appl. Spectrosc. 57 (2003) 343.
w35x M.P. Mateo, L.M. Cabalın,
´ J.J. Laserna, Automated linefocused laser ablation for tomographic analysis of inclusions
in stainless steel, Appl. Spectrosc. 57 (2003) 1461.