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Paints and coatings monitored by laser-induced breakdown spectroscopy.

Abstract Two algorithms--peak picking and peaks correlation--have been compiled in a portable laser-induced breakdown spectroscopy (LIBS) system and used specifically for spectral fingerprinting of paints and coatings, which contain multiple ingredients and require several application steps. The LIBS technique starts with a laser shot on the specimen surface, detection of the emission of the elements present, and analysis of the sample compositions. The LIBS system has been successfully illustrated for the identification and analysis of coating substrates, surface pretreatments, and primer and topcoat paints obtained in the lab and at field sites. The results indicate that, despite the compositional complexity in organic metal finishing, the spectral fingerprint of paints and coatings an be effectively determined by the LIBS technique. The advantages of LIBS technique over other conventional methods, such as EDX, are that it is quasinondestructive (<100 [micro]m of sample size), requires no sample preparation, is fast (within minutes), is user-friendly (for nontechnical personnel), and is capable of application both online and at the field sites.

Keywords Surface analysis, Laser spectral fingerprinting, Pigments, Quality control, Correlation algorithms, Chromate, Phosphate, Aluminum, Coating-substrate interface, Galvanized steel, Alloy-coated steel


Materials and techniques associated with paints and coatings require an appropriate verification process to achieve the desired property of the protective process to achieve the desired property of the protective finish. The organic coating involves a multistep process, in which the quality if the metal finish required for an industrial product determines the number and the type of steps in a given process. (1) These multistep coating processes include the selection and composition verification of substrates, surface cleaning, surface pretreatment, primer, topcoat, and the application of paint curing methods. The paint formulation is a mixture of multiple ingredients, composing resins, solvents, pigments, fillers, corrosion inhibitors, and other rheological additives. The organic coating in metal finishing practice is extremely complex. It is critical to have versatlie microanalytical system at the paint application site for providing quality control (QC)/quality analysis (QA) guidelines and obtaining the desired quality of metal finishing.

The complexities of paint compositions, paint types, and painting processes make their chemical analysis very difficult. Despite some elemental analysis methods that have been well established for general purpose use in chemistry, the determination of metallic components in paint has relived upon indirect analytical methods. For example, the metallic zinc dust in the Zn-rich epoxy primer was determined by differential scanning calorimetry (DSC). (2) The DSC method measured the apparent heat of fusion of the paint sample and compared this value to the standard value of pure Zinc as an indirect measurement of zinc composition in paint. IR absorption spectroscopy is useful sometimes for composition analysis if the paint ingredients contain and specific functional groups the t are spectroscopically active, (3) such as the isocyanate group in the urethane. The direct analysis of these functional groups may be possible only if the paint sample is uncured, and contained a relatively simple composition. In practice, there is no direct way for identifying a cured paint film. Once the paint (e.g., epoxy or urethane) is applied and fully cured, no more epoxy or isocyano functional group would remain in the paint film. Researchers continue to attempt to characterize the fully cured paint products by identifying the hydroxyl or amino groups, and use them for differentiating the epoxy paint or urethane paint. The results are generally inconclusive because the majority of other cured paints also have those functional groups as reaction products. Due to these difficulties, the using the indirect analytical methods, such as the analysis of catalysts, pigments, additives, or other ingredients for a cured paint film.

Laser-induced breakdown spectroscopy (LIBS) has been used for materials detection and analysis in various applications, such as steel and alloys, (4-11) paints and coatings, (12-18) materials pretreatment, (19) polymers, (20) bacteria,(21) molds, pollens, proteins, (22), (23) and space exploration. (24) A lab unit of LIBS at Northern IIIinois University was also recently used in compositional mapping of copper conductor patterns from a printed circuit board (25) and spectral fingerprints of bacterial strains. (26) In this paper, a small and versatile LIBS system is developed specifically for monitoring paints and coatings, including the measurement of LIBS spectra and the characterization of metal substrates, pretreatment layers, paints, and formulation ingredients. LIBS software is programmed to establish the correlation parameter among fingerprints of the paints of the paints the t are capable for distinguishing paints of the same color and have similar composition properties. The quality control, quality assurance, and trouble-shooting at the paint manufacturing facilities and coating field sires will also be illustrated.

Experimental procedure

Construction of a laser-induced materials analyzer

A small LIBS unit for monitoring paints and coatings is shown in Fig.1.A Q-switched Nd-YAG laser (Continuum, Minilite II), operating at a wavelength of 1064 nm, was employed as the excitation source. The pulse laser had a power of 50 mJ per pulse and a pulse width of 8 ns. The laser beam was focused onto the sample with a 5 cm focal length lens. A fiber optic cable collected the breakdown plasma emissions at the sample surface and directed them t a portable, miniature, CCD array fixed-grating spectrometer. The operating program analysis were carried out by suing an operating program (CoatID, ChemNova Technologies, Inc., DeKalb, IL) on a Microsoft Windows-based computer. The breakdown of emission data van be compared of those of a standard sample, the literature spectral values for carious elements, or the calibrated atomic line spectra that are already well known. (27) In Fig.1, the library files include the LIBS spectra of many known metals, metal oxides, inorganic elements, and compounds, as well as standard costing substrates, pretreated layers on substrates, and paint samples.


Two different algorithms--peak picking and peaks correlation--have been established for spectral analysis and materials charaterization. In peak-picking algorithms, the LIBS spectra captured from the unknown samples are compared to the peak positions and peak heights of those of reference samples in the library files A graph is displayed to show the degree of spectral peak matching and superposition between the unknown and library samples. The peck-picking method is primarily used for the identification of metallic elements in the paint sample, which have well-defined and relatively strong LIBS spectral peaks. For paint and coating, the sample is generally a complex mixture of multi-ingredients, and thus displayed a LIBS spectrum with overlapping peaks and a broad spectral back ground. In this case, the peaks correlation algorithm is used to compare the spectral finger prints of the unknown sample with those of the library control. The spectral fingerprinting procedure is done by adjusting the spectral intensity to a suiable level and obtaining the standard deviation between testing sample and library spectra. This procedure is repeated until the best peaks correlation is achieved. The larger library files can offer better fingerprint matching, where the best-fitted correlation curve is re[resented by the highest value of R coefficient.

Materials of paints and coatings

The quality of organic metal finishing may depend on (1) the selection and identification of substrates to be painted, (2) the degree of substrate cleaning and possible contaminations, and (3) the classification and applications of surface pretreatment, primer, and topcoat. In this paper, the substrates selected for spectral fingerprinting by LIBS are: (i) aluminum alloys (2024-T3, 3003, T6 from Advanced Coating Technologies, Inc. (ACT), Hillsdale, MI) and pure aluminum foil (Aldrich Fine Chemicals), and (ii) cold-rolled steel (CRS from Q-PANEL, Cleveland, OH and Caterpillar's OEM facility) and pure iron piece (Aldrich). The surface-pretreated substrates used for LIBS studies are: (i) Al 2024-T3/Clad (an ultra thin layer of pure aluminum treated on 2024-T3 aluminum alloy), (ii) Al 2024-T3 Bare/Alodine 1200 (the surface of 2024-T3 aluminum alloy is treated with Alodine 1200 solution, which contains chromates such as hexavalent chromium), (iii) phosphated (Bonderite 1000 or B-1000) and phosphated/chromated (B-1000/ P-60) from ACT, and (iv) galvanized (electroplated and hot-dipped) and galvalume steel plates that have a treated surface layer of Zn and Zn/Al, respectively.

Eleven heavy-machine OEM paint samples (four urethane, three epoxy, and four alkyd) from Caterpillar, Inc. were used for the spectral fingerprinting by LIBS. All paints were the same yellow color for different protective applications consisting of primers or topcoats with different resins. The paints were applied on 2 x 4-in. steel panels using a spray coating method and cured thermally or by air-dry as directed by the paint manufacturer. In addition, two cases of paint failure were investigated by LIBS at the industrial field sites where the painted samples were peeled off from Caterpillar's tractor bodies or machine parts. In one case, a misuse of paint products--i.e., a yellow epoxy primer, instead of the intended yellow direct-to-metal (DTM) urethane--was elucidated successfully. In the second case, a surface contamination (grease, oil, lubricant, or tar) was identified on the painted substrate, where the substrate was painted with an Al-PU primer and a topcoat of polyester PU enamel. The capability of LIBS in depth-profile analysis was also demonstrated for spectral fingerprinting of successive paint layers, composing a contaminant layer, Al-PU primer layer, and polyester PU enamel top layer.

Results and discussion

LIBS: an in-situ and quasi-nondestructive analytical technique

The need has become apparent for developing an in-situ and microsize (quasi-nondestructive) analytical method to characterize paint and coatings of antique, artifact, and historical objects, such as precious artwork. The LIBS technique can offer high sensitivity and selectivity, and can be performed on the art piece in-situ--thereby eliminating the need for the removal of paint from the sample, which may damage the original painting. In a LIBS analysis, only a minute amount of sample is consumed during the process of laser-induced atomization, which is accomplished by tightly focusing a pulsed laser beam onto the surface of the part to be tested. The OEM machine and its parts are normally very large with irregular and complex structures. Thus, the in-situ materials analysis is very important for OEM metal manufacturers, because the LIBS system can directly access the surface of an actual machine body in the field--a situation that is nearly impossible with a conventional surface analysis method such as SEM/EDX system.

The LIBS technique is capable of carrying out a depth profile analysis of successive surface layers by controlling and calibrating the working parameters of the LIBS system. Figure 2 shows the optical micro-scope images of some LIBS-measured sites on a painted steel panel with (a) the paint surface before analysis, (b) the surface with one laser pulse applied, (c) the surface with two laser pulses applied, and (d) the surface with five laser pulses applied. The scale bars are 50 urn in length. The first shot of the focused laser beam (70 mJ/pulse) made a burn pattern on the paint surface (see Fig. 2b). The successive laser pulses penetrated into the coating layers and eventually reached the metal substrate (see Fig. 2d). In principle, the LIBS spectrum recorded after each laser pulse, or for each layer of the multilayer paint samples, should generate the characteristic spectral peaks of the corresponding chemical compositions. The coating area affected by the laser pulse is limited to less than 100 urn in diameter (see Figs. 2b, 2c, and 2d). The layer thickness of materials that each laser pulse can penetrate is a function of laser fluent at the focal point, optical geometry, and material type. It is important to mention that a well-established elemental analysis method, such as EDX, can also perform a similar analysis. However, the sample used in EDX analysis must be cut into a few millimeter sizes for fitting inside the detection stage in a vacuum chamber. Also, the cut samples need to be covered with a conductive coating for EDX analysis, because paints are the dielectric materials. This film deposition of conductive layer is again done under another vacuum facility. These complicated sampling processes are eliminated in the LIBS analysis.


LIBS characterization of substrates

A less trivial experiment was performed to determine whether the LIBS system could be used to distinguish between different alloys of the same main metal content, or between the same metal alloys obtained from different manufacturing sources. Aluminum has many alloys in common use, and these alloys frequently need specific protective coatings for aerospace applications. The 2024-T3 Al alloy contains copper as the main dopant (i.e., 4.4% Cu, 0.6% Mn, and 1.5% Mg). The 7075-T6 Al alloy contains zinc as the main dopant (i.e., 5.6% Zn, 1.6% Cu, 2.5% Mg, and 0.23% Cr). The 3003 Al alloy contains no specific main dopant (0.0%-0.6% Si., 0.0%-0.7% Fe, 0.05%-0.20% Cu, and 0.0%-0.10% Zn). The Al alloys 2024-T3 and 7075-T6 have high surface protection strength, while Al alloy 3003 displays good pitting corrosion resistance. All three alloys should show aluminum peaks in LIBS spectra, 7075-T6 Al should display zinc and magnesium peaks, and 2024-T3 Al should display copper and manganese peaks, in their breakdown spectra. Figure 3 compares (he LIBS spectra recording from 250 nm to 450 nm for pure aluminum foil (Spectrum a) and three Al alloys (Spectra b, c, and d). As expected, Spectrum 3a gives only aluminum peaks at 281.6 nm, 306.3 nm, 308.2/309.3 nm, 358.0 nm, and 394.4/396.1 nm. Spectrum 3d shows that, in addition to the aluminum peaks, three spectral peaks at 328.2 nm, 330.2 nm, and 334.8 nm are due to zinc (I) ionic states. The 7075-T6 Al alloy also provides LIBS peaks at 278.6 nm, 285.2 nm, and 383.5 nm for Mg, and at 325.0 nm, 327.7 nm, and 423.0 nm for Cu emission. The copper peaks at 325.0 nm and 327.7 nm, and manganese peak at 293.3 nm, are also clearly seen in spectrum 3c for the A1 2024-T3 alloy sample. The LIBS technique is not only able to identify the chemical compositions of alloys, but is also capable of differentiating the possible contaminants in those alloys. For example, the contamination of Mn has been detected in the A1 7075-T6 sample as illustrated in Spectrum 3d. The contaminants of Mn and Mg are observed in Spectrum 3b for the A1 3003 sample.


The qualitative LIBS spectral assignment is also carried out for pure iron strips, cold-rolled steel, and industrial steel coupons used in the Caterpillar's OEM facility (referred to as CAT machine steel). The bare cold-rolled steel (CRS, SAE 1010) has a composition of 0.08%-0.13% C, 0.3%-0.6% Mn, 0.04% P(max), and 0.05% S(max). The LIBS spectra recorded from 250 nm to 400 nm are shown in Fig. 4: (a) pure iron strip, (b) cold-rolled steel, and (c) CAT machine steel. Spectrum 4a shows LIBS peaks for the pure iron piece at 259.9 nm, 262.6 nm, 275,0 nm, 358.1 nm, 373.4 nm, and 373.7 nm. The laser break-down emission for CRS, as shown in Spectrum 4b, is almost identical to that of the pure iron strip, except an additional peak at 344.3 nm that may be assigned to Mn as incorporated in the cold-rolled steel. Spectrum 4c indicates that CAT machine steel is not a pure iron piece or a standard CRS sample, but rather is a surface-pretreated CRS. The surface layer of CAT machine steel contains, Ca, Mg, Al, Mn, and P (at 589.1 nm), in addition to Fe. The results indicate that CAT machine steel is an iron phosphate-treated CRS, containing a substantial quantity of Ca and Mg, and some small amounts of Al and Mn in the phosphating bath.


LIBS characterization of surface pretreatment layer on substrates

Another important part of this research is to establish the effectiveness of LIBS' spectral fingerprinting technique for characterizing the composition of any metal surface pretreatment that may have been applied on the substrates. The common metal surface pretreatment used on aluminum alloys today is a chromium-based pretreatment (such as Alodine 1200 or Alodine 1000), which usually contains the chromates (i.e., the compounds contain hexavalent chromium). There are different processes used for surface pretreatment on aluminum alloys. Some processes cause the color of the metal surface to change to a yellowish color, and some cause no color change at all. In the latter case, it is almost impossible to tell visually whether the metal alloy has been pretreated. In this work, the different panels analyzed by LIBS are aluminum alloys of 2024-T3 bare, and 2024-T3 Clad (clad = a thin layer of pure aluminum on 2024-T3 substrate). The surface pretreatment layer on 2024-T3 bare panel is Alodine 1200. The main active ingredient of Alodine solution potassium dichromate or strontium chromate. Figure 5 shows a comparison of LIBS spectra recorded from 300 nm to 600 nm for (a) A1 2024-T3 bare, (b) A1 2024-T3/clad, and (c) A1 2024-T3/Alodine 1200. The spectral analysis of Fig. 5 is quite straightforward. Spectrum 5a is the same as Spectrum 3c for A12024-T3 bare, in addition to those peaks for A1, the spectral peaks at 325.0 nm and 327.7 nm Cu, and 358.0 nm and 518.7 nm for Mg, are also observed. Upon the deposition of a thin layer of pure aluminum on A1 2024-T3/clad should give only the pure aluminum peaks that are the same as Spectrum 3a for pure aluminum foil. The Alondine 1200 treatment on A12024-T3 bare has resulted in the formation of a yellowish surface layer, which leads to the appearance of several strong chromium LIBS peaks at 336.7 nm, 342.4 nm, 427.6 nm, 435.1 nm, 520.7 nm, and 534.7 nm, as shown in Fig. 5c. The LIBS system is designed for determining the thickness and uniformity of the pretreatment layer. The results of this quantitative analysis will be reported in Part II of this series.


The surface pretreatment of metal prior to the application of a coating or adhesive is a conventional industrial practice to improve coating adhesion and inhibit substrate corrosion. For cold-rolled steel, the phosphate conversion coating (e.g., Bonderite [R] B-1000) and phosphating/chromating (using parcolene 60) pretreatment (e.g., B-1000/P60) are commonly used. The LIBS technique is used to fingerprint the differences in chemical compositions of the surface-pretreated layer. The LIBS spectra were taken at the first laser shot spot on (a) untreated CRS panel, (b) B-1000 CRS panel, and (c) B-1000/P60 CRS panel. The laser-induced breakdown spectra of untreated and different chemically treated CRS panels are clearly identifiable, and their spectral assignments are marked in Fig. 6. The LIBS peaks in Spectrum 6a are assigned to Fe and Mn, and are similar to those in Spectrum 4b. The phosphate-treated B-1000 panel gives a few additional LIBS peaks in Spectrum 6b, such as P at 589.1 nm, and Ca at 315.8 nm, 318.2 nm, 358.3 nm, 394.0 nm, and 527.1 nm. In Spectrum 6c, the additional P60 treatment on B-1000 CRS is evident by the appearance of chromium peaks at 373.9 nm, 396.8 nm, and 527.1 nm. When these LIBS spectra are compiled in the software system as a standard library file, they can be used to determine if the surface pretreatment processes (including composition, uniformity, and thickness) have been done in accordance with the products' specification.


Zinc-coated steel (such as Zn/B-1000) is known to inhibit iron corrosion, similar to the effect of zinc anodes. The addition of aluminum to zinc is highly beneficial in improving its corrosion resistance and has resulted in the development of coatings with aluminum contents between 5% and 55% (i.e., galvalume zinc-coated steel). Zinc coatings may be applied to steel panels by hot dipping (i.e., hot-dipped galvanized steel, or HDG) and eletroplating (i.e., eletrogalvanized steel, or EZG). Due to the high degree of variations in the processing of EZG, HDG, and galvalume, it is critically important to have a versatile materials characterization technique, such as LIBS CoatID, to verify the manufacturing conditions of zinc-coated steel at different factory sites. For a simple illustration, we use LIBS to test two EZG panels (ACT Laboratories, Inc. vs China Steel Corp., Taiwan), two HDG panels (ACT vs Valspar Corp.), and two galvalume panels (Valspar Corp. vs China Steel Corp.). Figure 7 compares the breakdown emission spectra (recorded from 250 nm to 450 nm) for (a) an EZG panel from ACT, (b) and EZG panel from China Steel Corp., (c) a pure Zn metal piece, and (d) a B-1000 CRS panel from ACT. The LIBS spectra of EZG panels (Spectra 7a and 7b) should resemble those of the combined spectra of pure Zn (Spectrum 7c) and B-1000 CRS (Spectrum 7d), depending on the thickness of both a phosphate layer on bare CRS and a Zn-galvanized layer on a B-1000 CRS panel. The LIBS emission peaks for B-1000 CRS displayed in Spectrum 7d are the same as those recorded in Fig. 6b, where the phosphorous (P) emission is given by a doublet at 392.5 nm and 396.1 nm. The emission peaks of Zn in Spectrum 7c are easily identified at 255.2 nm, 259.1 nm, 273.8 nm, 275.8 nm, 302.7 nm, 306.9 nm, 329.4 nm, and 333.6 nm. By comparing the EZG panels processed at ACT Laboratories, Inc. (Spectrum 7a) and those processed at China Steel Corp. (Spectrum 7b), it shows that both EZG panels were subjected to the electrogalvanizing process as stated in their products' data sheet. However, the LIBS was able to distinguish a thinner Zn-galvanized layer in Taiwanese sample because the steel plate was not covered fully by the Zn-layer. Thus, the B-1000 steel peaks were still quite visible--from 350 nm to 450 nm--as shown in Spectrum 7b. On the other hand, both Zn-galvanized layers and B-1000 phosphate layers in the ACT sample (Spectrum 7a) are thicker than those in the Taiwanese sample, as indicated by the appearance of a strong P-emission doublet and several intense Zn peaks. In the ACT sample, the thicker Zn and phosphate layers give a higher coverage on the steel panel, so almost no steel peak is observed in Fig. 7a.


Figure 8 lists the breakdown of emission spectra (recorded from 250 nm to 450 nm) for two HDG panels from (a) Valspar Corp. and (b) ACT, and two galvalume panels from (c) Valspar Corp. and (d) China Steel Corp. sample. Both HDG samples gave quite similar LIBS spectrum (Spectra 8a and 8b), displaying strong Zn peaks (similar to Fig. 7c) and several weal Al peaks at 308.0 nm, 358.1 nm, and 395.2 nm. The result indicated that a small amount of Al had been formulated in the HDG bath. The spectral analysis and comparison of Spectra 8a and 8b suggested that (1) the hot dipping process for zinc coating used in both Valspar Corp. and ACT Laboratories, Inc. were quite similar, and (2) the hot dipping bath used in the Valspar Corp sample (Spectrum 8a) was found to contain a trace amount of others elements as evidence by the observed weak LIBS peaks at 265.2 nm, 278.8 nm, 296.3 nm, and 311.1 nm. On the other hand, spectra 8c and 8d displayed strong Al peaks over the Zn peaks, indicating that a large percent of AI was incorporated in the galvalume bath. In the Taiwanese galvalume sample, the Spectrum 8d shows only Al and Zn peaks, while some contaminants (or intentionally added elements) were detected for the galvalume sample obtained from Valspar Corp. as observed in Spectrum 8c at 297.4 nm, 311.1 nm, 421.4 nm, and 433.1 nm. These results gave the proof of capability that the LIBS technique with a peak-picking algorithm is a suitable QA/QC method for characterizing the metal substrates and surface pretreatment layers in paints and coatings.


LIBS identification of paints and coating ingredients

Eleven paints from Caterpillar's OEM coating facility were selected for the identification test using the LIBS technique, and are listed in Table 1. It is noted that all paint samples had the same color (i.e., Caterpillar yellow) with only slightly different tints. The differences were hardly distinguishable by the naked eye. Samples 1-4 were two-pack urethane paints, 5-7 were two-pack epoxy paints, and 8-11 were one-pack alkyd paints. The paint samples 1 and 5-9 are primers, while 2-4 and 10-11 are topcoats. The processing methods used in coating applications, such as drying and thermal curing conditions are specified in the remark column of Table 1. The paint systems used in Cater-pillar's OEM facility were specifically formulated by the paint manufacturers that have been successfully tested and verified for the required protection of heavy-duty machines. Once paint formulations were established, the manufacture strictly maintains the composition of point ingredients in an effort to achieve good quality control. This is the reason that the LIBS technique may be effective for fingerprinting a specific brand of paint. Figure 9 displays the LIBS spectra for the 11 paint samples listed in Table 1. The topcoat paints (Samples 2-4 and 10-11) display a relatively simpler LIBS spectrum than that of the primer paints (Samples 1 and 5-9). In all spectra, the LIBS peaks grouped around 250 nm may be attributed to iron oxide as a dispersed pigment. The peaks originated from calcium at 393.3 nm and 396.8 nm are predominantly shown in the primer type paints. Calcium carbonate has been used at high levels for certain paints because of its low oil absorption. Calcium compound imparts some film structure to the wet paint by improving the stability to sedimentation of other heavier pigments in paint. It is not surprising that primer paint for CRS coating contains a rich calcium ingredient. The primer paints (Samples 1, 6, 8, and 9) contain calcium carbonate and magnesium silicate, as their corresponding LIBS peaks displayed at 279.8 nm and 83.5 nm in Fig. 9.

Table 1: The sample paints obtained from Caterpillar, Inc

Sample Resin Type of Remark
no. paint

1 Urethane Primer 2-part system, cured at 66 [degrees] C
2 Urethane Topcoat 2-part system, low-temperature curing
3 Urethane Topcoat 2-part system, high-temperature curing
4 Urethane Topcoat 2-part system, cured at 66 [degrees] C
5 Epoxy Primer Low-temperature curing (55 [degrees] C
6 Epoxy Primer Medium-temperature curing (66 [degrees] C)
7 Epoxy Primer High-temperature curing (82 [degrees] C)
8 Alkyd Primer Air-dry system
9 Alkyd Primer Baking system
10 Alkyd Topcoat Air-dry system
11 Alkyd Topcoat Baking system

In the previous section, the peak-picking algorithm was successfully used for characterizing substrates and surface pretreatment layers that contained only a few elements and had the well-characterized LIBS peaks. Since paint formulation contains a rather complex mixture of multi-ingredients, the decisions for paint identification can best be made by a peak-correlation algorithm. Table 2 shows the correlation values between each pair of testing and reference paint samples. The S1 through S11 in the abscissa of Table 2 represent the standard paint samples whose LIBS spectra have been complied in the reference spectral library. Sample 1 through Sample 11 represent the testing samples whose LIBS spectra are taken and used to compare to those of the reference spectra. Any spectral pair of identical samples, between S1 and Sample 1 for example, must show a 100% correlation value. Due to the possible fluctuation in laser power density, the inhomogeneity of paint film compositions. and the variation in thickness of the paint film, the LIBS spectra for both testing and reference samples were measured at ten (10) different spots for each painted panel. A statistical average spectrum was created to achieve the reproducibility for the identification of a paint sample. The correlation values of identical samples listed in the diagonal matrix elements of Table 2 show 96%-99% reproducibility. On the other hand, the correlation values between two different types of pains, such as urethane and epoxy, show to be around 86.8% [+ or -] 0.7% (an average of the off-diagonal correlation values between urethane and epoxy blocks). These correlation values give a clear discrimination between types of paints. Based on the correlation values obtained in Table 2, we can say that the test sample is a good match to the reference sample if the correlation values are greater then 95%. We estimate from the use of the peaks correlation algorithm, the LIBS Coat ID system is capable of correlating the test paint samples to the standard paint films to give a 90% - 95% perfect match. the remaining 5% - 10% near match or no match may be due to the complex nature of paints and coatings, including possible surface contaminations. In this case, a careful spectroscopic analysis is also required to achieve the proper paint sample identifications.
Table 2: The correlations of eleven testing and reference paint samples

 S1 S2 S3 S4 S5 S6

Sample 1 98.0 86.6 80.0 82.5 86.8 83.4
Sample 2 86.8 99.1 96.9 97.6 79.7 57.1
Sample 3 80.1 96.8 99.4 98.8 74.4 49.8
Sample 4 81.9 97.4 98.8 99.4 74.2 51.9
Sample 5 87.4 79.8 74.5 74.6 97.4 80.1
Sample 6 82.9 57.0 49.8 51.9 78.8 95.8
Sample 7 90.8 83.7 80.9 82.7 86.4 83.7
Sample 8 88.0 64.2 58.5 60.7 80.6 94.8
Sample 9 96.3 80.1 71.7 73.7 86.0 84.9
Sample 10 88.9 97.8 93.5 94.9 80.3 60.3
Sample 11 89.7 96.4 90.6 92.1 83.1 62.5

 S7 S8 S9 S10 S11

Sample 1 90.2 87.6 96.1 89.3 89.9
Sample 2 83.8 64.2 80.1 98.2 96.7
Sample 3 80.9 58.4 71.3 93.7 90.8
Sample 4 82.5 60.4 73.5 95.1 92.2
Sample 5 86.4 81.0 86.5 80.9 83.6
Sample 6 82.5 93.5 84.4 60.8 62.9
Sample 7 97.7 87.9 84.9 84.3 83.6
Sample 8 87.2 96.2 88.1 67.2 68.5
Sample 9 84.3 87.7 97.7 83.8 85.9
Sample 10 83.7 66.5 83.3 99.1 98.2
Sample 11 83.1 67.8 85.4 98.3 98.9

Paint failure analysis for the on-site field samples: two cases

Case one: a misuse of paint product

The LIBS technique was used to analyze a paint failure case that occurred on a painted Caterpillar tractor (CAT 928G), as shown on the right-hand side of Fig. 10. The cause of paint failure was unknown and called for an investigation and analysis. Before the LIBS spectrum was taken of the peeled-off paint, we were told that the intended paint for the CAT 928G tractor was Caterpillar yellow DTM urethane. The LIBS spectrum of this standard yellow DTM urethane is shown in the bottom half of the left side of Fig. 10, while that of the suspected peeled-off paint is compared in the top half. It is clear that on match is observed for the top and bottom spectra in Fig. 10. In fact, they represent two different yellow paints. When the Coat ID program files, containing peak-picking and peaks-correlation algorithms, were used to search for a match to the type of failure paint, the results show that there is a good match with Caterpillar yellow epoxy primer. The LIBS spectrum of this yellow epoxy primer is displayed in the middle of Fig. 10 for comparison. the results suggested that the yellow paint chip that produced the peeling experience a misuse of yellow epoxy primer paint, instead of the intended yellow DTM urethane paint. This conclusion is also supported by the detailed analysis of LIBS spectra in Fig. 10. According to the Materials Safety Data Sheet (MSDS) provided by the manufacturers, the yellow DTM urethane paint contains about 20-30 wt% of iron oxide. The intense LIBS peaks observed in the bottom spectrum of Fig. 10 originated from Fe. at 259-8 nm. 273.8 nm, 307.0 nm, 322.3 nm, 333.0 nm, and 374.7 nm, On the other hand, the yellow epoxy primer contains not only 8--13 wt% of iron oxide but also 20-30 wt% of calcium carbonate, and 1.5-4 wt% of magnesium silicate. Therefore, the peeled-off paint (top spectrum) and the reference yellow epoxy primer (middle spectrum) show the additional LIBS peaks at 278.7 nm for Mg, and at 317.3 nm, 372.0 nm, 390.0 nm, 394.7 nm, 420.2 nm, and 427.7 nm for Ca.


Case two: a surface contamination due to the improper cleaning of substrate and an illustration of LIBS depth profile analysis of a multilayer coating, contamination layer/primer/topcoat

We received several failure paint chips from a field site at Caterpillar Inc. The peeled-off paint chips were made up of two coats: an AI-PU primer (MCU-100) and a polyester PU enamel (CT-352S) as a topcoat. The primer side of the paint chips was a sliver (aluminum) color with various visible dark brown areas (due possibly to the substrate contamination), and the topcoat side was a brownish-yellow color. The control paints of MCU-100 and CT-352S were also received for comparison. The texture of the failure paint chips was analyzed by using an optimal microscope (Nikon Optiphot -M fluorescence microscope), as shown on the right-hand portion of Fig. 11--CT-352S (top) and MCU-100 primer (bottom).

The LIBS technique was used to investigate the cause of peeled-off paint. When a laser beam was focused on the silver color spot (noncontaminated primer paint), the LIBS spectra showed a normal aluminum layer. Then the sample was subjected on one laser pulse and three laser pulses, as shown in the left-hand portion of Fig. 11. After the sample was subjected to five laser pulses, the LIBS plasma emission was shown to originate from the interface paint layer containing both AI-PU primer and polyester PU enamel. After 15 laser pulses, the laser beam penetrated the MCU-100 primer layer, so only the topcoat of CT-352S part showed up in the top spectrum of Fig. 11. The LIBS spectra of control paints--AI-PU primer (MCU-199) and polyester PU enamel--were recorded as references. The LIBS spectrum of the control MCU-100 primer and CT-352S topcoat was identical to that of the bottom and top spectrum of Fig. 11, respectively. Under a given laser fluent and optimal geometry, the primer layer is thinner because it required only four or five laser pulses to penetrate through. The topcoat was thicker and needed 9-10 laser pulses.


When a laser beam was focused on the dark brown contaminated area in the bottom side of AI-PU primer (circles in Fig. 11), the LIBS spectra showed mainly the layer of contaminants (e.g., grease, oil, lubricant, or tar). When LIBS spectrum was taken after one laser pulses, only the contaminant peak was detected at 350-390 nm, as shown in the bottom spectrum of Fig. 12. After three laser pulses were applied, the aluminum layer of AI-PU primer started to show up (i.e., the top spectrum of Fig. 12). The LIBS spectral correlations between the controlled sample (MCU-100 primer and CT-352S topcoat) and field sample gave an excellent match. The results illustrate that the paint failure in this case was not due to a misuse of paint products, but rather resulted from an improper cleaning of the substrate surface. A LIBS depth profile analysis was also qualitatively demonstrated for a multilayer coating--i.e., contamination layer/primer/topcoat. The number of laser pulses needed for penetrating through the contamination layers, primer layers, and topcoat layer are 2-3, 4-5, and 9-10 pulses, respectively.


The LIPS system shown in Fig. 1 is small, but not yet truly portable for online analysis of paints and coating at field sites. A lightweight, backpack type of LIBS unit is currently under development in our lab, where a laser gun will be separated from the laser head and a bundle of optimal fibers (28) will be used to deliver the laser pulse to, and collect the breakdown emission from, the paint film target. Moreover, quantitative analysis capability will be added to the software file (i.e., CoatID) for determining the concentration (thickness depth profiling or % distribution of elements) in paints and coating, by constructing a calibration curve and breakdown emission intensity vs concentration for each ingredient in a sample.


Laser-induced break down spectroscopy is a quick tool for the detection of mental alloys, surface pretreatment layers, and/or coating compositions. Although there is a considerable operator skill involved, once the LIBS system is set up and tested, it can be easily used at the technician level to qualitatively determine the presence of metals and other elements in a short time--usually within minutes. A versatile and small LIBS system has been developed, with CoatID software that compiled two different algorithms--peak picking, and peaks correlation. Using the peak-picking algorithm, the qualitative spectral matching for metal substrate, metal alloys, and substrate surface pretreatment layers is excellent, with a 100% match. Using the peaks correlation algorithm the qualitative spectral fingerprinting for paints and coatings gives a 90%-95% match. A detailed spectroscopic analysis can further assist in achieving the proper paint sample identifications.

The LIBS technique has also been used successfully for identifying two cases of paint failure at field sites. In one case, the paint failure was identified as due to a misuse of paint products, where a yellow epoxy primer was applied instead of the intended yellow DTM urethane paint. In the second case, the paint failure was resulted from surface contamination caused by the improper cleaning of the substrate prior to coating.

Acknowledgements This work was supported partially by a research contract form Caterpillar, Inc. The authors would like to thank Mr. B. McCanne, Mr. David Chisari, and Mr. Chien-Chung Teng for their assistance in the CoatID software development.


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T.Kim, C-T. Lin

Department of Chemistry and Biochemistry,

Northern Ilinois University,

DeKalb, IL 60115-2862, USA


B.T. Nguyen, V. Minassian

Caterpillar Inc., Techbical Center, Bldg.K.

14009 Old Galena Road, Mossville, IL 61552.USA
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Author:Kim, Taesam; Nguyen, Binh T.; Minassian, Vari; Lin, Chhiu-Tsu
Publication:JCT Research
Date:Sep 1, 2007
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