Analysis of material collected on swipes usinglaser-induced breakdown spectroscopy

Rosemarie Chinni,1 David A. Cremers,2,* and Rosalie Multari2

1Alvernia University, Department of Math and Science, 400 St. Bernardine Street, Reading, Pennsylvania 19607, USA2Applied Research Associates, Inc., 4300 San Mateo Boulevard NE, Suite A-220, Albuquerque, New Mexico 87110, USA

*Corresponding author: dcremers@ara.com

Received 2 October 2009; revised 8 February 2010; accepted 12 February 2010;posted 17 February 2010 (Doc. ID 118065); published 16 March 2010

Laser-induced breakdown spectroscopy (LIBS) was evaluated to determine elements collected on swipesas surface contamination. A series of long laser plasmas formed along the swipe surface (Post-it paper)interrogated the collected contamination. LIBS detection limits, determined for the elements Ag, As, Ba,Be, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Sr, and Zn on swipes (2 cm2 area), ranged from 0:002 μg (Be) to 1:46 μg (Pb).The elements were introduced as constituents of synthetic silicate particles serving as a contaminantdust stimulant. The average predicted mass was within 16% of the actual mass on the swipe. The effi-ciency of collecting particles from surfaces including plastic, Formica, and Al metal was also evaluated.The ability to detect and differentiate two amino acids on a swipe from each other and from the swipeusing chemometric modeling techniques was also demonstrated. © 2010 Optical Society of America

OCIS codes: 300.6365, 300.6500, 300.2140.

1. Introduction

Theability to rapidly detect contaminants on surfacesis important to applications ranging from routineenvironmental surveillance to security monitoring.Examples include detection of beryllium particleson surfaces, explosive residues on luggage, lead inhouseholds, and confirmation of clean-up protocolsfollowing spills. [1–6]. Some applications require onlythe identification of a contaminant, whereas otherapplications require quantification of contaminantlevels.Most current methods of determining surface con-

tamination cannot directly interrogate the surface; amethod of introducing the contaminant into the ana-lyzing technique is required. A widely used protocolfor environmental and workplace surveillance is wip-ing a surface with a swipe to collect loose material forsubsequent analysis. A large number of standardizedsurface sampling methods have been developed spe-cifying the swipe material, sampling protocol, and

the analysis procedure [e.g., chemical digestion fol-lowed by inductively couple plasma analysis (ICP)].Examples of swipe methods include OSHA ID-125G,NIOSH 9100 (for lead), NIOSH 9102, NIOSH 9105(for lead), and others specified by the AmericanSociety for Testing and Materials. Studies have alsobeen conducted to determine some characteristicsof wiping procedures and to compare swipe materials[7,8].

Conventional methods of determining elementcontamination on swipes use ICP or atomic absorp-tion spectrometry (AAS) techniques. Both of thesemethods require that the swipe be chemically ashedto produce a solution that is then analyzed. Althoughdetection limits for ICP and AAS are very good, thesemethods are costly and time consuming, with analy-sis restricted to a laboratory environment [9,10]. Thetime period between preparing the swipe and obtain-ing analysis results may be hours or even days.

Methods that can analyze surfaces directly arelaser-induced breakdown spectroscopy (LIBS) andportable x-ray fluorescence (PXRF). In situ detection,though rapid, can compromise the analysis capabil-ities of either method under certain conditions. For

0003-6935/10/13C143-10$15.00/0© 2010 Optical Society of America

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example, the substrate material, which is interro-gated along with the surface contaminant of interest,may introduce spectral interferences that complicatethe ability to detect the emission feature of interest(atomic line or x-ray emission). In addition, the sur-face to be interrogatedmaybe inaccessible to the sam-plinghead of theLIBSorPXRF instrument and/or thein situ surface concentration (e.g., μg=cm2) may be be-low the instrument detection limit. The latter is amore serious issue with LIBS because of the smallarea sampled by each laser spark (<1mm2) comparedto the large area (e.g., 5 cm2, Ref. [11]) interrogated byPXRF over which the contaminant concentration canbe integrated.To overcome or minimize these complications with

either in situ detection technique, the contaminantcan be collected on a swipe as described above forlaboratory-based analysis techniques. Using LIBSor PXRF, the swipe can be analyzed immediatelyin the field. The use of a PXRF unit in the field todetermine contaminants collected on air sampling(Millipore) and swipe (Whatman) materials has beenevaluated and good results obtained [11], and it is aNIOSH method [12]. The use of LIBS to determineairborne particles collected on filters has been pre-viously reported [13–15], and LIBS has been investi-gated to identify biological hazards wiped fromvarious surfaces [16]. Although PXRF analysis ofswipes is an established method, advantages of LIBSover this method include lower detection limits formany elements and the ability of LIBS to detect lightelements (e.g., Be) [17,18], which is not feasibleusing PXRF.An advantage of preparing swipe samples rather

than direct analysis of the surface contaminant insitu lies in a reduction in spectral interferences fromthe substrate materials (e.g., painted and bare metalsurfaces, wood, plastic, etc.) underlying the contam-ination. Typically, swipe materials have a paperlikesubstrate composed mainly of the elements C, O, N,and H, which should not affect strongly LIBS orPXRF analysis. PXRF is not sensitive to these ele-ments, and these elements have few atomic emissionlines in a LIBS spectrum.Presented here are the results of a study of LIBS-

based swipe analysis. The use of LIBS to determineelements collected from a surface by a swipe is an ex-tension of prior work with air sampling filters withsome new issues to be addressed. In [16] the maingoal was the identification of biological surface con-tamination among confusant species collected on aswipe or on surfaces. The main goal here is to quan-tify LIBS-swipe monitoring capabilities with regardto the mass of metal that can be detected on a swipe.Quantification is important for use of the technologyfor environmental surveillance where certain levelsof contaminants are specified as being acceptableor not acceptable. We have also demonstrated theability to distinguish between two similar aminoacids and a swipe material using chemometric meth-ods as a preliminary investigation into the use of

LIBS as a method to monitor organic surface con-taminants. Issues addressed here include (1) theselection of a swipe material to provide efficient col-lection of the surface contamination, maximization ofthe contaminant LIBS signal, and minimization ofspectral interferences from the swipe; (2) developinga method to interrogate the collected material (e.g.,long spark); and (3) dealing with the potential loss ofparticles during analysis because of the strong acous-tic pressures produced on the swipe by the action ofthe focused laser beam.

2. Experimental

A. Benchtop LIBS Apparatus

Certainmeasurements were carried out using bench-top LIBS systems consisting of a Nd:YAG laser oper-ating at 5 or 10Hz (INDI, Spectra Physics or SureliteII, Continuum) and a 1=2m spectrograph/detectorsystem (Spex Industries, 0:5m Czerny–Turner) witha gated photodiode array (TN6500 controller andTN6132array, TracorNorthern) or an echelle spectro-graph (SE200, Catalina Scientific) with an ICCD(DH734-18F-03, I-Star, Andor Technology). Thesesystems allowed changes in laser pulse energy, focus-ing parameters, timing, etc., to determine optimumanalysis conditions. Laser pulses were focused on theswipes using a cylindrical lens (50mm focal length) toform a long spark [13,14] and the plasma light wascollected by a fiber optic placed above the sampleand connected to the spectrograph/detector system.Detector timing parameters were a 1 μs delay and agate width of 20 μs.B. LIBS Swipe Monitor

Additional measurements were carried out using atransportable LIBS swipe monitor diagrammed inFig. 1. This unit was built to provide rapid and auto-mated determination of metal contaminants onswipes. A Nd:YAG laser (YQL-102, Laser Photonics,Inc.) operating at 5Hz generated the laser pulses(120mJ) that were focused on the swipe using a cy-lindrical lens (50mm focal length) to form a alongspark. The spark was about 6mm long (vertically or-iented) on the swipe. With reference to Fig. 1, theswipe (0:64 cm × 3:2 cm) was loaded onto the holderby removing the end cap to the chamber, slidingthe swipe holder off the support rod, placing theadhesive backed swipe on the holder, replacing theholder on the rod, and then installing the end cap.A large number of swipe holders were machined (alu-minum) so that a series of swipes could be preloadedon the holders prior to analysis. The swipe wasmoved horizontally under the repetitive pulses dur-ing analysis in order to interrogate the collectedmaterial. The plasma light was collected by a fiberoptic placed next to the cylindrical lens and recordedusing a 0:125m spectrograph (Oriel) and CCD cam-era (ST-6, Santa Barbara Instrument Group, quartzwindow). The nongated CCD integrates all the lightfrom the plasma over the set exposure time (on-chip

C144 APPLIED OPTICS / Vol. 49, No. 13 / 1 May 2010

integration for 45 s). The swipe was interrogated in asealed acrylic chamber to contain ablated particles.During analysis, air was drawn from the chamberby an air pump, passed through a HEPA filter can-ister, and then directed back into the chamber. Thelaser was operated at 5Hz instead of the usual10Hz repetition rate to allow additional time forthe air flow system to remove ablated debris fromthe optical paths (laser pulse focusing and light col-lection) to the swipe surface. Instrument operationwas controlled by a series of switches on the frontof the instrument, and analysis of data was providedby a laptop computer connected to the instrument.This instrument provides complete automated op-eration and analysis of the collected data. A singlemeasurement required approximately 45 s, andabout 30 samples could be processed in 1 h. Becauseof the limited spectral coverage of the spectrograph,the wavelength drive was adjusted to monitor emis-sion lines of interest in different spectral regions.

C. Swipe Materials

A variety of swipe materials have been developed tocollect surface contamination for subsequent analy-sis by methods other than LIBS. These include GhostWipes, Pace Wipes, Whatman Smear Tabs, PalintestDust Wipes, G/O Swipes (G/O Corp.), and Whatmanfilter paper (e.g., type 41, 54, 541). These are used dryor with wetting agents including water, alcohol, sol-

vents, and detergents. These materials have somecharacteristics important for their use with LIBS in-cluding (1) toughness so the swipe does not tear as itis rubbed against a rough surface and (2) efficient col-lection of surface contamination. For LIBS analysis,additional properties are required. The materialmust (1) provide good coupling with the laser pulseto generate a robust spark, (2) exhibit few emissionlines from the elements composing the swipe to mini-mize spectral interferences with the contaminant(s)of interest, and (3) have a sufficiently smooth surfacesuch that collected particles are not trapped in deeplayers of thematerial precluding interrogation by thelaser plasma. Obviously, some of the properties im-portant for LIBS analysis are not important to con-ventional analysis of the swipe because the swipe ischemically digested to produce a solution that is thenanalyzed.

Rather than conduct an extensive study of the ap-propriateness of current swipe materials for use withLIBS, three candidate swipes materials were se-lected for testing. These materials were celluloseacetate/cellulose nitrate filters (Millipore type AA,0:8 μm), cellulose filter paper (Whatman 42), andPost-it paper (3M). The Millipore filters had beenused previously for LIBS analysis of particles trap-ped on the filter and these were shown to give goodresults [13,14]. Whatman 42 was a swipe materialeasily obtained and is commonly used for swiping[16]. Post-it paper was selected because initial workby us suggested it has the properties needed for aLIBS swipe material listed above, including an adhe-sive backing useful to secure the swipe during LIBSanalysis.

D. Sample Preparation

1. Analytes Deposited Directly on Swipes asSynthetic Silicate Particles

Synthetic silicate particles with trace elements(Brammer Standard Company) were used to preparesamples having known surface concentrations of spe-cific elements (μg=cm2) or total element mass depos-ited over a specific area (i.e., area of a swipe used inthe LIBS swipe monitor). The major components(e.g., SiO2, Al2O3, Fe2O3) of the synthetic sili-cates are at fixed concentrations, but minor ele-ments have a range of concentrations from 1 to5000 parts in 106 ðppmÞ. Minor elements in thesesamples include Ag, As, Ba, Be, Cd, Cr, Mn, Ni, Pb,Sr, and Zn. Aqueous suspensions of the silicate parti-cles having different concentrations were prepared.In order to analyze mercury, various concentrationsof aqueous suspensions of spiked soil were preparedusing a 100ppm Hg AAS (atomic absorption stan-dard) solution. Well-stirred aliquots were dropped di-rectly on the swipes, spread evenly, air dried, and thenanalyzed with either the benchtop LIBS apparatus orthe LIBS swipe monitor. Six replicate swipes of thelowest deposited mass were prepared and analyzedand the resulting signals were used to compute the

Fig. 1. LIBS portable swipe monitor. L ¼ laser, P ¼ air pump,S ¼ spectrograph, D ¼ detector, TS ¼ translation stage, TSC ¼translation stage controller, DC ¼ detector controller, F ¼ HEPAair filter, LPS ¼ laser power supply SC ¼ sample chamber, EC¼ end cap, SH ¼ swipe holder, and CL ¼ cylindrical lens. Theprocedure for loading the swipe into the instrument is also shown.

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standard deviation(s) for the detection limit calcula-tion. The lowest depositedmass represents the lowestmass used for each element from which a signal wasobserved; this varied depending on the element. Thismasswas determined by the synthetic silicate sampleused and the concentration of the element in thatsample.Three replicate swipes each of a series of higher

deposited masses were also prepared and analyzed.Calibration curves were constructed using the aver-age integrated area under the analyte emission peakfor each mass loading and the calculated surface con-centration or total mass deposited on a swipe. Thedetection limit (CL) was calculated from the linearcalibration curve (slope ¼ m) using CL ¼ 3 s=m.

2. Effect of Distance Between Pulses onElement Signals

The effect of distance between pulses on element sig-nals was studied in order to determine the minimumdistance between the laser pulses in which no adja-cent particles would be removed from the swipe be-fore the next laser pulse interrogated the sample.The samples for this test were prepared by coatingthe swipe with a visually uniform coating of syntheticsilicate particles. The particles were applied dryrather than as a suspension as wet particles showedan increased tendency to stick to the swipe even afterdrying. The goal here was to investigate the worstcase scenario of wiping a surface with a dry swipe.Several replicate samples were prepared that ap-peared visually to have approximately the sameloading of particles. The main parameter of interesthere was the change in element signal as a functionof spacing between shots on the swipe surface ratherthan the absolute signal values. The data were laternormalized for comparison of results for differentswipes. The swipe was affixed to a linear translationstage (MTS50 translational stage with TDC001 con-troller, Thorlabs) and analyzed using the benchtopLIBS apparatus. This translational stage was ad-justed to move the swipe in various increments sothe spacing between pulses on the swipe surfaceranged from 0:05mm to 0:50mm. The laser was op-erated at 100mJ=pluse and single shot analysis wasperformed for each step. There were a total of tensteps taken for each increment. For example, usingthe 0:05mm increment, the swipe was interrogatedby one laser pulse, moved 0:05mm, and then inter-rogated by a second pulse; this process was continuedfor a total of 10 interrogations. The elements moni-tored were Ba, Be, Fe, Li, Mg, Mn, Sr, and Ti. Eachelement signal in the 10 shot interrogation sequencewas normalized to the largest signal (integrated areaunder the emission peak) for that element. The nor-malized area for each element was then averagedover all of the elements monitored correspondingto each increment.

3. Determination of Collection Efficiency forSynthetic Silicate Particles Swiped from ThreeDifferent Surfaces

Barium (0:1 μg) and manganese (1:0 μg) from suspen-sions of synthetic silicate particles were dropped onsquare pieces (100 cm2) of plastic, aluminum metalwith the surface roughened up by sanding with em-ery cloth, and Formica. The deposited suspensionswere air-dried. Dry and wet (with water) Post-it pa-per was used to swipe over the surface in separateexperiments. The swipes were then analyzed usingthe swipe monitor. Six replicate measurements werecarried out for each case. Calibration curves for Baand Mn deposited on Post-it paper were used to de-termine the mass swiped from each surface using theaverage integrated areas under the emission peaks.

4. Determination of Measurement AccuracyUsing Swipes

Known masses of synthetic silicate particles (as sus-pensions) were placed on Post-it paper swipes andthen analyzed. Six replicate measurements weremade of each mass of the elements As, Ba, Be, Mn,and Pb. Two different mass loadings were used foreach element. The Post-it paper containing the ele-ments As, Be, and Pb were analyzed using the LIBSbenchtop setup at an energy of 100mJ, while thePost-it papers containing the Ba and Mn were anal-yzed using the swipe monitor at an energy of 120mJ.The benchtop system was used for As and Be detec-tion because the ICCD provides greater sensitivity torecord the strong UV lines of these elements. Theaverage integrated area under the emission peakof interest was determined for each swipe and wasused along with previously prepared calibrationcurves to predict the mass placed on the Post-itpaper.

5. Identification of Amino Acids on Swipes

Swipes containing the amino acids L-asparagine andL-leucine were prepared by manually rubbing theamino acids into the Post-it paper to simulate wipinga contaminated surface. Loose, residual powder wasnot removed from the swipe. LIBS spectra were thencollected by forming a series of laser plasmas acrossthe swipe as described above using the benchtop ap-paratus. The laser was operated at 24mJ=pulse and10Hz. Each spectrum recordedwas the accumulationof 10 individual spectra (1 s detector accumulationtime, 1 μs delay time, and a 20 μs gate window.L-asparagine ðC4H8N2O3Þ andL-leucine ðC6H13NO2Þwere used here because of their very similar struc-tures and chemical formulas, allowing a test of theability to distinguish between these compounds inthe presence of a swipe material.

For each sample (amino acids on Post-it paper, andclean Post-it paper), approximately 100 accumulatedspectra were collected and subsequently screened toeliminate spectra having low counts (<30% of the

C146 APPLIED OPTICS / Vol. 49, No. 13 / 1 May 2010

maximum intensity observed over all 100 spectra).Once screened, the spectra for each sample were ran-domly divided into two groups: a classification group(50 spectra) to be used to build the chemometric iden-tification model for differentiating the three samplesand a verification group (20 spectra) to be used to testthe model performance.

3. Results and Discussion

A. Selection of Analytical Lines

The best analyte emission line(s) to use for swipeanalysis depend(s) on the strength of the line, thefreedom from interferences due to lines from theswipe material, and a large dynamic range for cali-bration. The best primary and secondary analyticallines determined here are listed in Table 1. Second-ary lines would be used if there were spectral inter-ferences between contaminants collected on theswipe, for example, interference of the strong Be (II)lines at 313:04=313:10nm by Hg (I) at 313:16=313:18nm.

B. Selection of Swipe Material

As noted above, the criteria for a good swipe materialinclude ruggedness for swiping a surface, the ab-sence of strong emission lines, good coupling withthe laser pulse to generate a strong plasma, and alow density of spectral interferences. The LIBS spec-tra of three swipe candidate materials were recordedin the region 220–800nm and then compared. Thecolor of the Post-it paper was related to the numberof observed emission lines, and several colors wereevaluated. The strong emission lines observed fromclean candidate swipe materials are listed in Table 2.The Millipore filter showed the fewest number ofemission lines. Both the Whatman filters and Post-it paper have similar emission lines with a greaternumber of calcium lines observed from the Post-itpaper and two titanium lines apparent from theWhatman filter paper.Millipore filters are commonly used for collection

of airborne particles. These filters have a smooth sur-face and couple efficiently with the laser pulse. Thesmooth surface and few spectral lines observed fromthese filters are desirable for LIBS analysis. Thesmooth surface maximizes the amount of collected

contaminant that resides on the surface and is avail-able for interrogation by the laser sparks. On theother hand, the smoother surface resulted in col-lected particles being more easily ejected from the fil-ter surface in areas adjacent to the area directlysampled by the laser spark. Also, Millipore and simi-lar filter materials (made of cellulose nitrate or cel-lulose acetate) are fragile and were prone to tearingwhen used to wipe a surface. An adhesive backing,such as adhesive labels available from Avery, are con-venient to reinforce the filter but some tearing of thefilter was still observed following vigorous rubbing ofa contaminated surface. In comparison, Whatmanfilter paper, although being very rugged, has a fairlycoarse surface that may trap the collected dusts deepwithin the filter, precluding analysis by the lasersparks that are formed mainly on the filter surface.Increasing the laser pulse energy ablates more of thefilter surface, but the goal was to keep laser pulse en-ergies to reasonable values, and at the higher ener-gies collected particles were ejected from the filter onpieces of the filter material removed as small chunks.If the mass of collected surface contamination is suf-ficiently above the element detection limit, ejection ofsome material during analysis is not important if thegoal is only identification of the collected material.

Table 2. Strong Emission Lines (nm) Observed from LIBS Analysis of Three Swipe Materials

Species Millipore Filter Post-it Paper Whatman Filter

C 247.86 247.86 247.86Ca 393.37, 396.85, 422.67 315.89, 317.93, 370.60, 373.69, 393.37, 396.85,

422.67, 430.25, 445.48, 487.81393.37, 396.85, 422.67, 430.25, 445.48

Al 394.40, 396.15 308.22, 309.27, 394.40, 396.15 308.22, 309.27, 394.40, 396.15Mg none 279.55, 280.27, 285.21 279.55, 280.27, 285.21Ti none none 334.94, 359.35Si none 251.61, 288.16 251.61, 288.16CN bands a 385.34, 421.60 359.04, 385.34, 421.60 359.04, 385.34, 421.60, 457.80C2

a none 473.71 473.71, 515.52aListed wavelength refers to band head position.

Table 1. Analytical Emission Lines for Analytes of Interest

ElementPrimary

Wavelength (nm)Secondary

Wavelengths (nm)

Ag 328.07 338.29As 234.98 228.81Ba 455.40 493.41Be 313.04/313.10 a 234.86Ca 393.36 396.84, 422.67Cd 508.58 228.02Cr 425.44 427.48, 428.97Cu 324.75 327.40Hg 253.65 312.57, 313.16/13.18 a

Mg 285.21 279.55, 280.27Mn 403.08/403.31/403.45 a 279.83, 279.48Ni 341.48 352.45, 361.94Pb 405.78 368.35Sr 407.77 421.55Zn 334.5 328.33, 330.26aLines separated by solidus ð=Þ are not resolved by the spectro-

graphs used here.

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For environmental surveillance, however, somedegree of quantification is needed, and this capabil-ity increases the utility of the analysis method. ThePost-it paper appeared to be a good compromise be-tween the Millipore and Whatman filters; this papernot only has a smoother surface than the Whatmanfilters, but the paper also stood up to vigorous rub-bing of a surface without tearing. In addition, thePost-it paper comes with an adhesive backing stripthat can be used to secure the paper to a flat surfaceduring LIBS analysis. Based on this evaluation,Post-it paper was chosen as a swipe material for sur-face sampling in the measurements reported here.Post-it paper comes in different colors ranging frompastels to bright colors. LIBS analysis of the brightand darker colored Post-it paper showed a greaternumber of emission lines from these colors than frompastel shades. For this reason, we used pastel coloredPost-it paper.

C. Elemental Signal Versus IncrementalMovement of the Swipe

During analyses, repetitive, closely spaced laserpulses are focused on the swipe surface. The actionof the laser pulse creates a strong pressure wave thatcan dislodge loosely held particles adjacent to the fo-cal area on the swipe. The extent of the ejection ofparticles will depend on the power density of the la-ser pulses on the swipe and characteristics of theswipe surface (i.e., smooth versus rough finish). Toevaluate the effect of the spacing of the laser pulseson the element signals, Post-it paper swipe sampleswere prepared having synthetic silicate particlesdeposited on the surface as described in Subsec-tion 2.D.2. These samples were then placed on anadjustable-speed linear translation stage. Five dif-ferent increments or spacings between adjacent laserpulses focused on the swipe surface were tested(0:05mm, 0:10mm, 0:20mm, 0:35mm, and0:50mm), and the results are presented in Fig. 2.For increment spacings between pulses of 0.05 and

0:10mm there is a strong decrease in the elementsignals as the step number or number of laser pulsesincreased. For the other increments (≥0:35mm) thesignals remained fairly uniform as the swipe surfacewas interrogated. Measurement under a microscopeof the damage spot on the swipe showed the averagewidth of the spot was about 0:31mm. This indicatesthat the loss of particles from adjacent areas of thePost-it paper swipe that do not overlap is minimal.In the case of significant overlap between pulses(<0:2mm increment) the decrease in signal occursbecause each laser pulse is interrogating an areafromwhich some particles have been removed by pre-vious pulses. The results show that an increment sizeof 0:35mm or greater between each pulse would besufficient for this type of analysis given the charac-teristics of the focusing system and the laser.

D. Detection Limits for Elements on Swipesas Synthetic Silicates

Using the samples and methods described in Subsec-tion 2.D.1, known masses of elements in syntheticsilicate particles were deposited on Post-It paperswipes over a range of masses. The swipes were thenanalyzed using the LIBS swipe monitor or benchtopsystem, and detection limits were determined. Theresults and analyzed mass ranges are listed inTable 3, and a sample calibration curve is shownin Fig. 3. The detection limits for elements on theswipes ranged from 0.0021 to 1:46 μg. For some ele-ments the mass range used to construct the calibra-tion curves was only a factor of two. This was due tothe masses of these elements in the available syn-thetic silicate samples and the minimum detectableconcentrations of these elements that permitted theuse of only two samples. These detection limitsshould be considered as approximate. The approxi-mate area over which the analytes were depositedand which was interrogated by the laser pulses ofthe swipe monitor was about 2 cm2 (swipe size ¼0:64 cm × 3:2 cm). In the case of Be, the minimum

Fig. 2. Comparison of the average of normalized emission lines for a series of elements using a translation stage to move the swipe withsynthetic silicate particles over different increments between shots. A single shot analysis was performed on each spot before moving to anadjacent area, and a total of 10 steps were carried out for each increment.

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detectable surface concentration was on the order of1ng=cm2 (SNR ¼ 3), which agrees well with a pre-viously determined limit of 0:45ng=cm2 (SNR ¼ 6)for Be on a filter material [13]. The differences canbe related to the different forms of the Be contamina-tion between measurements and different instru-mental parameters.In Table 3 the mass detection limits obtained here

using the LIBS swipe monitor are compared withlower limits of detection determined using a PXRFunit from a prior study [11]. Comparison reveals thatLIBS mass detection limits are lower by factors ran-ging from 3.8 to 38, depending on the element.Regulatory limits have been established for a wide

range of airborne contaminants in the form of thresh-old limit values (TLVs) specified by the AmericanConference of Industrial Hygienists or permissableexposure limits (PELs) mandated by OSHA. In many

cases the TLV and PEL are similar or identical invalue. Unlike air monitoring, regulatory limits forthe maximum surface concentration level (MSCL)of many contaminants have not been established.Limits for Be and Pb have been specified, and theseare presented in Fig. 4. For contaminants for whichlevels have not been established, some industrialhygiene groups have established facility surface con-centration limits based on the DOE mandated re-lease (nonregulated area) or housekeeping criteria(A) for Be (10CFR850) and the OSHA airbornePEL for Be (B) according to the formula [19]

Release of housekeeping criteria formetal

¼ A=B ½TLV orOSHAPEL forMetal�:

The limits based on this criterion are also dis-played in Fig. 4 for several elements. Also shownare LIBS mass detection limits determined herefor the elements on a swipe (Table 3). Comparison

Table 3. Detection Limits (CL) from Synthetic Silicate Particles onPost-it Paper (Area ~0:64 cm × 3:2 cm) and Comparison with Portable

XRF [11]

Element (massrange used)

CL (LIBS) a

(μg)CL (PXRS) b

(μg)CL (PXRS) b/CL (LIBS) a

Ag (0:01–0:1 μg) 0.053 – –

As (0:5–5:0 μg) 0.14 1.9 14Ba (0:01−0:1 μg) 0.024 – –

Be (0:001−0:01 μg) 0.0021 – –

Cd (1:0−2:0 μg) 0.97 14 14Cr (5:0−10 μg) 0.5 1.9 3.8Cu (0:07−0:13 μg) 0.034 1.2 35Hg c (0:1−1:0 μg) 0.050 –

Mn (0:7−1:3 μg) 0.37 2.5 6.7Ni (0:07−0:13 μg) 0.60 2.7 4.5Pb (10−20 μg) 1.46 16 11Sr (0:01−0:1 μg) 0.013 0.5 38Zn (1:0−10 μg) 0.43 3.7 8.6aUnless otherwise stated, measurements were carried out using

the LIBS swipe monitor.bValues from Ref. [11] and refer to micrograms of element on

25mm diameter filter.cThese measurements were carried out using the LIBS benchtop

apparatus. Mercury was analyzed by using spiked clean soil ratherthan the synthetic silicate samples because of the low concentra-tions of Hg in the silicate samples.

Table 4. Measurement Accuracy Using Swipes (Synthetic SilicateParticles on Post-it Paper)

Actual MassPlaced on

Post-it Paper (μg)

Predicted Mass(Average of Six Replicate

Measurements) (μg) % RSD a % Diff. b

0.30 (Mn) c 0.29 21 −31.0 (Mn) c 1.1 13 140.070 (Ba) c 0.070 6.0 00.040 (Ba) c 0.038 5.7 −50.094 (Pb) d 0.099 29 50.19 (Pb) d 0.19 12 10.0090 (Be) d 0.013 21 440.019 (Be) d 0.018 4.7 50.16 (As) d 0.19 11 190.063 (As) d 0.11 17 75

a% RSD is the % relative standard deviation from the six repli-cate measurements.

bHere % Diff. is the average percent difference between the ac-tual and predicted masses from six replicate measurements.

cMeasurements were taken using the LIBS swipe monitor.dMeasurements were taken using the LIBS benchtop apparatus.

Fig. 3. Typical calibration curve; the curve shown is forberyllium.

Fig. 4. Comparison of LIBS detection limit values (μg/swipe fromTable 3 with different mass limits collected over a 100 cm2 area(regulatory and facility specified) for metals used in this study.

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of the MSCL values with the LIBS CL values showsthat, except for the “release to non-regulated area”values for Cd and Cr, LIBS should have sufficientsensitivity as provided by the LIBS swipe monitoror benchtop system used here, to analyze swipesfor the elements within the MSCL limits even ifthe collection efficiency was 30%.

E. Accuracy of Analysis and Measurement Precision

Results relating to the accuracy of determining theanalyte mass on a swipe are presented in Table 4.Deposited masses were determined using previouslyprepared calibration curves for the elements As, Ba,Be, Mn, and Pb. To eliminate the uncertainty andnonreproducibility in the mass collected by wipinga surface, known masses of the silicates weredropped directly on the paper and then analyzed.In this way, the data indicate the accuracy of LIBSmeasurements for determining the mass of particleswithout an efficiency factor for collection of the con-tamination by wiping. As the data show, the accuracywas generally good with the average difference be-tween actual and predicted mass on the order of16%. Three samples yielded high percentage differ-ences, however, between the actual deposited massand predicted values. These samples were one Beswipe and two swipes of As. The large values canbe explained as follows. First, the Be mass measuredin the sample that gave a 44% difference corre-sponded to a low mass of Be deposited on the Post-it paper, 9ng, which is approaching the detectionlimit of Be (i.e., 2ng from Table 3). Similarly, the high

percentage differences obtained for As are, we be-lieve, due to the weak signals observed from As be-cause the deposited masses were again near thedetection limits for this element as seen from Table 3.

F. Collection of Synthetic Silicate Particles Swipedfrom a Surface

The collection of contamination from a surface usinga swipe is characterized by some nonreproducibilityin the mass of collected material and uncertainty inthe fraction of the total contamination collected. Allmethods of swiping a surface will have similar uncer-tainties. The results obtained by repeatedly swipingcontaminated smooth and rough surfaces are shownin Fig. 5. The analyte monitored was Mn, and thesame total mass of Mn was placed on each surface.Initially, dry swipes were used to collect the material.Then swipe number six for the smooth surface andswipe number nine for the rough surface were wettedwith water. It can be seen that the initial dry swipecollected about 6× as much contamination from thesmooth surface as compared to the rough surface.The rough surface has irregularities that can trapthe particles, reducing collection efficiency especiallyusing a dry swipe. The Mn signals from swipes thatwere wetted to collect particles from both the roughand smooth surfaces increased compared to dryswipes. For the smooth surface, this increase wasmuch less in comparison to the Mn signals observedfrom the first dry swipe. On the other hand, for therough surface, the increase observed using thewetted swipe was approximately twice as great incomparison to the first dry swipe.

In a subsequent experiment, the actual collectionefficiencies were measured by swiping a surface con-taminated with a known mass of analyte and thenanalyzing the swipe and measuring the collected ma-terial. The results are listed in Table 5. The surfacesranged from very smooth (acrylic plastic) to moder-ately rough (Formica with a satin finish/nonglareand rough aluminum). As the data show, the collec-tion efficiency of about 50% (that is, 50% of the par-ticle mass deposited on the surface) was determinedfor the rough aluminum and Formica surfaces. Forthe smooth plastic, the collection efficiency increased

Table 5. Collection Efficiency for Synthetic SilicateSamples Swiped from Surface a

Surface

Mass of AnalyteDeposited onSurface (μg)

Predicted Massof CollectedAnalyte b (μg)

CollectionEfficiency

(%)

%RSD c

Acrylic plastic 0.10 (Ba) 0.090 90 16Acrylic plastic 1.0 (Mn) 0.80 80 8.4Rough Al 0.10 (Ba) 0.040 40 16Rough Al 1.0 (Mn) 0.48 48 36Formica 0.10 (Ba) 0.050 50 16Formica 1.0 (Mn) 0.69 69 17

aThese measurements were carried out using the LIBS swipemonitor.

bAverage of six replicate measurements.cCalculated from six replicate measurements.

Fig. 5. Comparison of the collection efficiency of the swipe deter-mined using manganese deposited on smooth and rough plasticsurfaces. A new swipe was used each time and swiped over thesame area. After and including swipe number 6 on the smoothplastic surface and swipe number 9 on the rough plastic surface,wet swipes were used and allowed to air dry before they wereanalyzed.

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significantly to about 80–90%. Again, this is expectedsince rough surfaces would have a greater chance oftrapping the contamination. The reproducibility ofthe measurements, determined by performing six re-plicate measurements, had an average of about 18%.

G. Differentiation of Amino Acids on a Swipe

To investigate the ability to detect and differentiateamino acids on Post-it paper from each other andfrom the Post-it paper, chemometric modeling wasundertaken. For the chemometric analysis, partialleast squares regression in combination with princi-pal component analysis (PLS2) was used over thewavelength range of 200–860nm [] using commer-cially available software (The Unscrambler, CamoSoftware, Inc.). Prior to modeling, the spectra foreach sample were visually screened to ensure allspectra appeared representative of the sample. Nodata pretreatments were applied to the spectra.For the PLS2 regression modeling, the 50 highest in-tensity spectra were included in the modeling. Thespectral wavelength data (37,220 intensity measure-ments) were treated as the “x” variables and the sam-ple types were treated as “y” variables (three types).The model was then tested on the 20 spectra (not in-cluded in the modeling) having the lowest intensityof those collected for each sample. The model scorespace for the first three principal components andthe prediction results of the model when tested onthe 20 lowest intensity spectra for each sample areshown in Fig. 6. From the score space for the firstthree principal components, it can be seen that thereis overlap between the sample scores, especially forL-leucine on a Post-it paper and the clean Post-itpaper. This overlap does not appear to have a signif-icant impact on the predictive power of the model. Bychoosing prediction values of >0:8 for L-asparagineon a Post-it paper, <0:35 for a clean Post-it paper,and between 0.35 and 0.8 for L-leucine on a Post-it paper, it is possible to differentiate between

L-asparagine and both L-leucine on a Post-it paperand a clean Post-it paper for all spectra tested. Incomparing, L-leucine on a Post-it paper and a cleanPost-it paper, it was found that L-leucine could onlybe differentiated for 90% of the spectra tested (10% ofthe L-leucine are misidentified as clean). The abilityto differentiate between the samples by carefulchoice of the model prediction values indicatesthat it is possible to differentiate between both theorganic samples on the swipe and the swipematerial.This is an important result for consideration whendesigning of LIBS-based instruments.

For comparison, the prediction capability of regres-sion analysis on samples of pure amino acids inpressed form was also investigated using the samemodeling methodology and the LIBS chemometricpredictive capability was found to be comparable tothe results obtained when samples on Post-it paperwere used.

4. Conclusions

The data presented here demonstrate the capabi-lities of LIBS to determine the presence of metal-containing dusts on surfaces by analyzing a swipeused to collect the contamination by wiping. Quanti-tative analysis is possible if the method is calibrated.The results also indicate that LIBS should have suf-ficient sensitivity to detect Be and Pb on swipes atlevels needed to meet current regulatory require-ments for maximum surface contamination levels.Although regulatory limits for surface contaminationfor many other toxic metals have not been specified,based on TLV and PEL values for these metals andextrapolating using regulatory surface concentra-tions levels for Be, LIBS will also have useful detec-tion capabilities for many other metals. Also, byapplying chemometric analysis to LIBS spectraldata, detection and differentiation of organic materi-als of interest (e.g., biological species) on swipesshould be possible with appropriate definition and

Fig. 6. PLS2 Regression Model built using “best” (highest intensity) 50 LIBS spectra collected from two amino acids on Post-it paper andclean Post-It paper. The model score space for the first three principal components is plotted on the left (a). From the score space, it can beseen that there is overlap between the sample scores, especially for L-leucine on a Post-it paper and a clean Post-it paper. When the modelwas tested on 20 of the “worst” (lowest count) spectra (b), however, it was found that the samples could be well separated by choosingprediction values of >0:8 for L-asparagine on a Post-it paper, <0:35 for a clean Post-it paper, and between 0.35 and 0.8 for L-leucine on aPost-it paper.

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modeling of samples to be differentiated. This is animportant result when considering the need todevelop detection and identification algorithms fordeployment on LIBS-based instruments.In summary, this work shows that LIBS instru-

mentation has the potential to provide on site analy-sis of swipes, thereby providing enhanced detectioncapabilities over currently accepted field-basedinstruments such as PXRF. To be used for routinesurveillance in a health monitoring program,however, LIBS must undergo extensive testing andcomparison with currently deployed monitoringmethods and be accepted by the appropriate regula-tory institutions.

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