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eal-time control of ultrafast laser micromachiningy laser-induced breakdown spectroscopy

ao Tong, Jinggao Li, and Jon P. Longtin

Ultrafast laser micromachining provides many advantages for precision micromachining. One chal-lenging problem, however, particularly for multilayer and heterogeneous materials, is how to prevent agiven material from being ablated, as ultrafast laser micromachining is generally material insensitive.We present a real-time feedback control system for an ultrafast laser micromachining system based onlaser-induced breakdown spectroscopy �LIBS�. The characteristics of ultrafast LIBS are reviewed anddiscussed so as to demonstrate the feasibility of the technique. Comparison methods to identify thematerial emission patterns are developed, and several of the resulting algorithms were implemented intoa real-time computer control system. LIBS-controlled micromachining is demonstrated for the fabrica-tion of microheater structures on thermal sprayed materials. Compared with a strictly passive ma-chining process without any such feedback control, the LIBS-based system provides several advantagesincluding less damage to the substrate layer, reduced machining time, and more-uniform machiningfeatures. © 2004 Optical Society of America

OCIS codes: 120.0120, 120.6200, 140.7090, 300.2140, 320.7150, 350.3390.

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. Introduction

ltrafast laser systems for material processing haveeen gaining increasing popularity in the past fewears. Compared with conventional long-pulse la-ers, ultrafast laser pulses �less than or equal to pi-oseconds� make it easy to achieve extremely higheak irradiance intensities ��1015 W�cm2� with lowulse energies �less than or equal to millijoules�.hese extreme pulse parameters have resulted in

undamentally new laser–material interaction mech-nisms, which result in considerable material versa-ility, extremely fine-feature patterning, and aegligible heat-affected zone. These features lead toetter quality, more-reproducible machining resultsnd increased machining efficiency and have thuspened up new possibilities for laser machining, es-ecially for precision machining with micrometer-cale feature sizes.1–3 However, a significantbstacle in ultrafast laser micromachining of multi-ayer or heterogeneous microstructure materials is

The authors are with the Department of Mechanical Engineer-ng, State University of New York at Stony Brook, Stony Brook,ew York 11794-2300. The e-mail address for J. P. Longtin is

longtin@ms.cc.sunysb.edu.Received 25 June 2003; revised manuscript received 25 Novem-

er 2003; accepted 2 January 2004.0003-6935�04�091971-10$15.00�0© 2004 Optical Society of America

he lack of an on-line diagnostic method to determinehich material is being ablated during the removalrocess. For example, to fabricate precision struc-ures in thermal sprayed nichrome on alumina sub-trates for sensor applications,4 the laser often cutsoo deep into the alumina substrate, while only elec-ric isolation in the nichrome coating pattern isought �Fig. 1�. This problem arises because ultra-ast laser pulses are generally insensitive to the ma-erial they remove.

Traditionally, the status of a machining operations obtained by manual inspection after processing,hich limits efficiency and throughput. Feedback

rom the workpiece under ablation to the laser sys-em is thus desirable to precisely control the machin-ng process at the process level. One promisingechnique to address this problem is the use of laser-nduced breakdown spectroscopy �LIBS� by which thelasma emission generated during the laser–aterial interaction can be collected and analyzed to

dentify the elemental composition of the materialeing ablated, which can then be used to control theachining process.5–9

During laser-induced material breakdown, the in-ense laser pulses generate an expanding plasmalume, which emits light as ionized particles recom-ine. The spectrally resolved detection of thelasma emission provides the elemental compositionf the material being ablated. LIBS has several at-ractive features for sample analysis including min-

20 March 2004 � Vol. 43, No. 9 � APPLIED OPTICS 1971

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mal sample preparation, the capability to analyzeaterials regardless of their physical form and

ggregate state, local microanalysis capability, andperational simplicity.10–13 LIBS based on conven-ional nanosecond laser systems, however, has notet become a mainstream analytical method foruantitative purposes because of its relatively poorccuracy, stability, and detection limits comparedith other atomic spectroscopy techniques.10–14

hese problems are caused by a variety of factors,uch as laser irradiance variation, the sample matrixffect, strong continuum emission, spectral line shift-ng, and broadening effects. Because ultrafast LIBSs a relatively new topic, its quantitative analysisapability has not yet been extensively studied.owever, increased stability and accuracy for ultra-

ast LIBS has been demonstrated by some research-rs because of the distinctive features of ultrafastaser-pulse generation and material interaction,15–18

hich suggests that LIBS could be a reliable, quan-itative technique for real-time control of ultrafastaser micromachining processes.

LIBS has been used in a variety of applications foraterial identification.19–23 The idea of controlling

aser ablation by use of LIBS is an emerging areaith considerable research to be done. LIBS haseen used to control Nd:YAG and UV lasers to cleanimestone,5 marble,7 sandstone,8 cobalt binder fromungsten carbide,9 and even artwork.6 Kim et al.24

iscuss LIBS used with ultrafast lasers in surgicalpplications for selective tissue removal. In most ofhese applications, however, the spectral compari-ons are rudimentary, e.g., they consider only theresence or absence of a single material, and detailsf the laser control are not provided. Furthermore,n laser micromachining applications, the laser con-rol must be more sophisticated. Simply shuttinghe laser off when a given material is detected, forxample, is insufficient because stopping the laserlso stops the detection capability and hence the pro-essing itself. In this paper we extend use of LIBS in

ig. 1. Scanning electron microscope graph of an overcut groovey femtosecond laser ablation showing electrical isolation of theoating layer.

972 APPLIED OPTICS � Vol. 43, No. 9 � 20 March 2004

everal respects: �1� a discussion of the implemen-ation of LIBS associated with ultrafast lasers is pre-ented, �2� several algorithms for spectral detectionnd comparison of multiple species are presented, �3�ssues associated with implementing a real-time la-er control system are discussed, and �4� the tech-ique is used to fabricate actual engineeringicrostructures. Furthermore, a key objective of

his study is to develop an inexpensive and practicalystem that can be easily implemented in a variety ofaser systems.

. Experimental Setup

he ultrafast laser micromachining system, shown inig. 2, consists of a Ti:sapphire femtosecond regener-tive amplified laser system, a three-dimensionalontrollable motion stage on which the target samples mounted, a fiber-based spectrometer, and a com-uter for analysis and control. Output pulses fromhe regenerative amplifier have a pulse duration ofpproximately 150 fs, with a nominal wavelength of00 nm, a maximum pulse energy of 1.1 mJ, and aariable pulse repetition rate ranging from singlehot to 1000 Hz. After passing through the focusingenses, the femtosecond laser pulses strike the targetample, which is mounted on the three-dimensionalotorized positioning stage �Labmotion Series-640

0-mm linear stage system�. The three translationxes, x, y, and z, are perpendicular to each other, andach axis has a resolution of 0.5 �m over a 50-mmange. The stage velocity can be continuously ad-usted up to 10 mm�s. Desired machining patternsan be programmed by use of a script language in theontroller. Digital input–output ports from the con-roller are used to synchronize external events andommunicate with other equipment, e.g., the laserystem and the spectrometer, during motion control.The plasma emission during the laser ablation,hich occurs in air at ambient temperature and pres-

ure, is collected by a PC-based spectrometerSD2000 Miniature Fiber Optic Spectrometer, Oceanptics Inc.�. This is a two-channel spectrometerith only the master channel used in this study.he master channel has a 200–850-nm spectral

ig. 2. LIBS-controlled ultrafast laser processing system sche-atics.

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ange, 25-�m entrance slit, 2048-element silicon lin-ar CCD array, and provides an optical resolution1.3 nm. The shortest integration time �or gate

ime�, tint, of the spectrometer, which is the durationhe spectrometer detector collects incoming photons,s �3 ms. The plasma is imaged into the entranceber of the spectrometer through a plano–convex

ens with a focal length of 50 mm and a bandpasslter �Melles-Griot, nominal transmission range00–685 nm, typical rejection range 720–930 nm� tolter the reflection of the residual laser light at 800m. The bandpass filter reduces the spectrum win-ow from 200 to 850 nm to �350 to 650 nm and it issed in all the collections unless otherwise noted.he spectrally resolved plasma signal is collected by

he spectrometer and then sent to a PC for furthernalysis.Compared with many spectrometers used for ana-

ytical purposes, the spectrometer used in this studyas relatively low optical resolution ��1.3 nm� andoes not provide any gating capability, which couldllow for improved emission line detection. How-ver, from a practical point of view, this spectrometers small, lightweight, fiber coupled, and inexpensive,hich makes it easily integratable and well suited forany experiment setups. Furthermore, as demon-

trated in this study, after appropriate postprocess-ng of collected spectra, the spectral monitoringystem works well in identifying different materialsnder ablation.In this study, five materials �alumina, thermal

prayed nichrome alloy,25,26 copper, glass, and steel�ere investigated for the study of ultrafast LIBS

haracteristics and appropriate comparison methods.igure 3 shows the typical wavelength intensity spec-

ra of the five materials produced by the femtosecondaser pulses with pulse energies of �1 mJ and a pulseepetition rate of �1000 Hz.

. Characteristics of Ultrafast Laser-Inducedreakdown Spectroscopy

o use LIBS for feedback in an ultrafast laser micro-achining application, the LIBS signal should be

ensitive to the ablated material’s elemental compo-ition, while being generally insensitive to other fac-ors, such as laser irradiance parameters, spatialonfiguration of the spectrometer detector, and theaser–material interaction environment.

For conventional nanosecond-scale LIBS imple-entations, major limitations that have hindered theIBS technique in those applications requiring pre-ise quantitative information include large variationsn the detected plasma signal; the sample matrixffect, which refers to the inconsistency between thelemental emission line intensity ratios and thectual elemental composition in the sample ma-rix14,28–30; continuum emission, which occurs athe beginning of plasma formation during which theharacteristic emission lines are overshadowed by atrong, broad, and featureless continuum emis-ion11,31; and spectral line shifting and broadening,hich is the shifting and broadening effect of the

haracteristic emission lines due to particles andadiation dynamics in the plasma.13,14

In contrast, fundamentally new laser–material in-eraction mechanisms due to the ultrafast laserulses provide better characteristics for the LIBS sig-al. Because material breakdown associated withltrafast lasers is highly repeatable, even for dielec-ric materials, the plasma signal variation is reduced.he matrix effect, caused by a variety of mechanismsnd relying heavily on the sample structure, is notell understood. To our knowledge, the matrix ef-

ect with ultrafast LIBS has not yet been extensivelyiscussed in the literature, although it is expectedhat the effect will be less significant than that withanosecond lasers because of the absence of a liquidhase and selective ablation in the ablated area forltrafast laser ablation.14,28–30,32 Results from Mar-etic et al.,17 Le Drogoff et al.,33 Eland et al.,15 andthers suggest that the continuum emission of theltrafast LIBS is lower and decays much faster, andhe spectral line-broadening effect is also less signif-cant than that of nanosecond LIBS.15 Their resultslso suggest that femtosecond LIBS laser-inducedlasma lifetime is around several microseconds oronger, which is comparable to nanosecond LIBS.ognoni et al.31 and Mao et al.34 showed that thelasma shielding effect is also lower for femtosecondaser ablation because of the extremely short laser-ulse durations.For the Ocean Optics spectrometer, the shortest

ntegration time �gate time� is of the order of 2–3 ms,hich is far longer than the temporal evolution of theltrafast LIBS spectra. As a consequence, all spec-ra measured in this study are actually integratedver the entire plasma emission history and, in manyases, represent the integration of several pulsesather than a single pulse because the integrationime is long enough to include multiple pulses. Al-hough continuum emission in the characteristicmission spectra can be undesirable for precise quan-itative analysis, it is not a significant problem in thistudy, as we wish only to differentiate between dif-erent materials. As long as the plasma emissionpectrum remains stable and corresponds closely tohe specific sample material, it can be used as a sig-ature to identify a given material. Furthermore,ppropriate postprocessing of the spectra is used toinimize these problems, as discussed in Section 4.It is well known that the plasma emission is spa-

ially heterogeneous in nature and that the plasmalume expands preferentially normal to the sampleurface.31,35 With on-axis plasma light collectionperpendicular to sample surface�, any vertical dis-lacement in the plasma, which occurs when a craterr groove is formed, has a minimal perturbation onhe LIBS signal.28,31 As the off-axis collection anglencreases, this effect becomes more pronounced. Inhe experiment, the collection angle, measured fromhe incident laser beam, is chosen to be as close asossible to the on-axis direction within geometric con-traints. A plano–convex collection lens with a focalength of 50 mm is optionally used to increase the

20 March 2004 � Vol. 43, No. 9 � APPLIED OPTICS 1973

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lasma light intensity while suppressing the spatialeterogeneity of the plasma emission. Figure 4hows spectra acquired with different collection an-les �the distance from the sample remains the same�ith the collection lens for angles of 30°, 50°, 70°, and0° and without the collection lens for angles of 20°,0°, 50°, 70°, and 90°. It can be seen that after nor-alization, these spectra match one another well.ithout the collection lens, as shown in Fig. 4�b�, the

pectral variation is also insignificant, although it isarger than the data collected with a lens.

Fig. 3. Measured LIBS spectra of five materials u

974 APPLIED OPTICS � Vol. 43, No. 9 � 20 March 2004

The influence of the ultrafast laser pulse itself onhe LIBS spectra is also investigated. For the fem-osecond laser system in this study, only the pulseepetition rate and the pulse energy are readily ad-ustable. The effect of the pulse repetition rate onhe plasma signal is simply additive in nature be-ause the plasma lifetime is so short �microseconds�ompared with the interval between laser pulsesmilliseconds�. In practice, the combination of pulseepetition rate and motion stage velocity will produceifferent ablation depths and may have some effect

n this study. Spectral line data are from Ref. 27.

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n the LIBS signal because of the different depthrofiles. The pulse energy determines how muchaterial is ablated by a single pulse with all other

arameters being fixed and thus determines the spec-ral emission intensity. In our experiment the di-meter of the laser focus point is 40–50 �m, and theelation between laser fluence and emission intensitys linear. Normalized spectra for a nichrome samplet several laser fluences are shown in Fig. 5. Whenhe fluences are high ��10 J�cm2�, as in Fig. 5�a�, theormalized spectra match one another well; when theuences are relatively low ��10 J�cm2�, as in Fig.�b�, there is a noticeable deviation in the lower flu-nce spectrum, which may be due to the reducedlasma signal-to-noise ratio at lower fluences.

. Spectra Comparison Algorithms

o develop algorithms that can efficiently recognizearious sample materials in real time, several spec-ra processing methods and comparison algorithmsre studied. Because of the large number of pa-ameters involved, the absolute intensities of spec-ra can vary considerably. Normalization of the

pectra to a common standard is thus necessary foromparison. In this study, a root-mean-squarerms� mean is used as the normalization standardnd is chosen for two reasons. First, the rms meanavors higher intensities because of the quadraticerm; this serves to emphasize characteristic lineshile suppressing background emission. Second,

pectra normalized by the rms mean are conveniento compare with each other in terms of linear cor-elation algorithms.To reduce the effects of continuum emission and

ackground noise, a threshold treatment is per-ormed. The spectra are first rms normalized. Ahreshold is then applied such that any intensity be-ow the threshold is considered noise and discarded,nd intensities above the threshold remain un-hanged. The threshold-treated spectra are againormalized by their new rms and submitted to theomparison algorithms.

The comparison algorithms fall into two categories:pecific line-matching methods, which compare themission intensities at a few specific wavelengths;nd spectrum-wide comparison methods, which com-

ig. 4. Alumina spectra with different spectrometer detector an-les measured from the laser incident axis: �a� with a collection

ig. 5. Nichrome spectra with different laser fluences: �a�igher fluences, normalized spectra stay close; �b� lower fluences,oticeable difference in the normalized spectra, higher background

20 March 2004 � Vol. 43, No. 9 � APPLIED OPTICS 1975

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are two spectra by use of all available data in thepectrum.

. Five Largest Peaks Method

ne straightforward and easy to implement specificine-matching approach is the five largest peaks

ethod, in which the five largest wavelength inten-ity pairs of each reference material spectrum areetermined after normalization. The sample spec-rum is compared with each of the reference materialpectra on the basis of the differences of the intensi-ies at five specific wavelengths. The smaller theifferences, the higher the resemblance. A refer-nce database based on the five materials in thistudy is assembled, and the same five materials aresed as sample spectra for testing. Results are nor-alized to a range between zero and unity, with unity

ndicating the maximum resemblance. The con-rast, which is the difference between comparisonesults for the same material and that for two differ-nt materials, is not high, as shown in Table 1.

. Linear Correlation Method

or improved accuracy, a spectrum-wide comparisons desirable. One popular approach is use of theinear correlation method to compare two spectra.or a two-point data series �xi, yi�, i � 1 . . . N, the

inear correlation coefficient between the two series rs defined as36

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here x� and y� are the averages of the two series,espectively. In this paper x represents the wave-ength and y represents the intensity from the spec-rometer at that wavelength. A correlation valuelose to unity means that the resemblance betweenhe two spectra is high, a value near zero impliesittle resemblance, and a negative correlation resultas no significance. By calculating the linear corre-

ation directly, we obtain only relatively low-contrastomparison results. This is because the continuummission is too strong and overshadows the charac-eristic emissions in the spectra. Anzano et al.23 dis-ussed use of a linear correlation method to identify

Table 1. Comparison of a Set of Sample Spectra with Five ReferenceMaterials by Use of the Five Largest Peaks Method

with a Threshold of 2.0

Sample Material

Reference Material

Alumina Copper Glass Nichrome Steel

Alumina 0.99 0.19 0.28 0.29 0.12Copper 0.13 0.99 0.00 0.39 0.04Glass 0.09 0.00 1.00 0.00 0.11Nichrome 0.13 0.36 0.07 1.00 0.53Steel 0.10 0.16 0.00 0.30 0.99

976 APPLIED OPTICS � Vol. 43, No. 9 � 20 March 2004

ifferent plastic materials’ LIBS signal. Their studyhows good discriminating capability among the plas-ic materials they tested.

To increase the contrast, a threshold treatment iserformed, and a modified correlation formula, as inq. �2�, is adopted to avoid negative correlation re-ults and increase calculation efficiency.

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In Eq. �2� the averages of the series are omitted,nd as a result the modified correlation values arehifted slightly positive. The emission characteris-ics of each material are enhanced, and the contrastetween the results is high as shown in Table 2.ote that in Table 2 there still exists a relatively

arge correlation value between copper and nichrome.he reason is that copper and nichrome have closemission lines at �521 nm, which are further blurredecause of the line-broadening effect.

. Characteristic Lines Correlation Method

he example of being unable to differentiate the521-nm lines between copper and nichrome sug-

ests that this contribution to the correlation shouldot be counted because it is caused by the line-roadening effect of two sets of close emission linesrom two different elements. It is thus insightful toxtract the characteristic emission lines during thereprocessing of the spectra. We can extract theharacteristic lines by identifying local peaks, whichre those spectral intensities larger than their imme-iate neighbors. In the threshold treatment of thepectra, instead of keeping all the intensities abovehreshold unchanged, we keep only the identifiedocal peaks unchanged, while all others are set toero. An error tolerance is included to account forhe spectral line-shifting effect. The spectra arehen renormalized. Comparison results with goodonsistency and high contrast are obtained ashown in Table 3, and the inability to resolve be-ween copper and nichrome spectra disappears.he correlation value between alumina and glass is.16, which is relatively high. This is attributed tohe 396.15-nm Al I �I stands for atomic emission�

Table 2. Comparison of a Set of Sample Spectra with Five ReferenceMaterials by Use of the Modified Linear Correlation Method

with a Threshold of 2.0

Sample Material

Reference Material

Alumina Copper Glass Nichrome Steel

Alumina 1.00 0.00 0.24 0.00 0.00Copper 0.00 1.00 0.00 0.49 0.00Glass 0.24 0.00 1.00 0.00 0.00Nichrome 0.00 0.49 0.00 1.00 0.00Steel 0.00 0.00 0.00 0.00 1.00

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. Comparison of Algorithms

pecific line-matching methods are straightforward,ast, and easy to implement; however, only a smallumber of spectral lines are examined. Spectrum-ide comparison methods, although more complexnd slower, take the entire spectrum into accountnd thus are a better quantitative tool to use to re-olve unique materials. A comparison of theseethods is shown in Table 4. From the discussion

bove, the characteristic lines correlation methodnd the modified linear correlation method have goodesolving and contrast performance. In particular,he characteristic lines correlation method combineshe advantages of both the correlation-based methodsnd the characteristic lines-matching methods androvides the best quantitative meaning and contrast.e can increase the contrast of the comparison re-

ults considerably by screening out background con-inuum emission interference using thresholdpectra, especially for correlation-based methods.

. Real-Time Control System

e implemented a real-time control system for mi-romachining thermal sprayed multilayer materi-ls.25,26 Thermal sprayed sample materialsprovided from the Center for Thermal Spray Re-earch at Stony Brook� are patterned with the ultra-ast laser system. A typical material combination isn alumina substrate sprayed with a layer ofichrome alloy �20–50-�m thick. During the laseratterning process, electrical isolation is essentialFig. 6�. However, the laser sometimes cuts too deepnto the dielectric substrate material, which is unde-irable if the samples are later subjected to hightress or temperature. The LIBS technique was im-

Table 3. Comparison of a Set of Sample Spectra with Five ReferenceMaterials by Use of the Characteristics Lines Correlation Method

with a Threshold of 1.5

Sample Material

Reference Material

Alumina Copper Glass Nichrome Steel

Alumina 1.00 0.08 0.16 0.09 0.00Copper 0.08 1.00 0.00 0.00 0.00Glass 0.16 0.00 1.00 0.00 0.00Nichrome 0.09 0.00 0.00 1.00 0.06Steel 0.00 0.00 0.00 0.06 1.00

Table 4. LIBS Spect

CharacteristicsFive Largest

Peaks Method

Resolving capability LowContrast AverageStability GoodImplementation EasiestCPU speed Fastest

lemented to assess its effectiveness in minimizinghis effect.

During the patterning process, the laser pulses cuthrough the coating material and then into the sub-trate layer. The acquired spectra gradually transi-ion from the coating material spectrum �nichrome�o the substrate material spectrum �alumina�. Apectrum at the transitional interface betweenichrome coating and alumina substrate is shown inig. 7. This spectrum has characteristics of bothichrome and alumina. When electrical isolation is

ust reached, the spectra from the pattern groovesften still have some fraction of the coating material,.g., due to further ablation of the sidewalls, henceome experience is required to set the appropriatehreshold to stop the processing.

. Real-Time Control System

he algorithms discussed above were implemented inreal-time computer-controlled system we call SPE-omp. The program collects sample spectra contin-ously from the spectrometer during laser ablationnd compares them to reference spectra in a databasehat is collected before hand. The program drives aTL on–off signal to control the pulse repetition ratef the ultrafast laser. A two-state pulse repetitionate is chosen—rather than completely shutting offhe laser—because the real-time control techniqueequires some plasma emission for detection. Dur-ng the logic ON position, the laser runs at a pulseepetition rate of 1000 Hz, which is the normal abla-ion state; during the logic OFF position, the laser

ig. 6. Measured LIBS spectrum at nichrome–alumina transi-ional interface.

omparison Methods

ModifiedCorrelation Method

Characteristic LinesCorrelation Method

High Very highHigh Very highVery good GoodEasy ModerateFaster Fast

rum C

20 March 2004 � Vol. 43, No. 9 � APPLIED OPTICS 1977

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uns at a reduced pulse repetition rate, e.g., 100 Hz,hich is the probing state. The probing-state pulse

epetition rate is chosen to maintain a reliable LIBSignal for detection and still minimize sample dam-ge.

. Control Delay

he total time delay tdelay from the initial spectrumollection to the output of the control signal dependsn two factors: �1� the spectrum acquisition timeint, which is determined by the integration time ofhe spectrometer; and �2� the signal processing timeproc required by the comparison algorithms. Theeal-time control delay is thus determined by the sum

tdelay � tint � tproc. (3)

or the spectrum acquisition, there are two differentcquisition times, which correspond to the two work-ng states of the system. During the normal abla-ion state at 1000 Hz, an integration time of �5 ms isnough to obtain a high signal-to-noise ratio spectra;his is also near the acquisition speed limit of thepectrometer. During the 100-Hz probing state, a0-ms integration time is the shortest possible inte-ration time, as only one pulse will be available to thepectrometer during this period. The signal-to-

ig. 7. Real-time comparison results by the modified correlationethod during a horizontal scan of a multilayer sample �nichrome

oating, �25 �m in thickness, on alumina substrate� with foureep vertical grooves. Stage velocity is 4000 �m�s, integrationime is 15 ms.

978 APPLIED OPTICS � Vol. 43, No. 9 � 20 March 2004

oise ratio of the single-pulse spectrum is enough foruccessful recognition of the material. The signalrocessing time required by the control software is5 ms on a Pentium 4 PC. Thus the total controlelay is �10–15 ms.Figure 8 shows a simple real-time control experi-ent. The test is conducted on a nichrome coating

hermal sprayed onto an alumina substrate. Theichrome coating is approximately 25 �m thick after

t is polished. Prior to the test, four vertical groovesre fabricated into the nichrome that protrude com-letely to the alumina substrate. The widths of therooves, from left to right, are roughly 40, 80, 120,nd 160 �m, respectively. The ultrafast laser beams first scanned across the surface horizontally fromeft to right at a stage velocity of 4000 �m�s withouthe LIBS control enabled. The laser spot diameters �40–50 �m and the integration time in the testas 15 ms. Thus the integration distance dint was0 �m, which we calculated by multiplying the inte-ration time by the stage velocity as in Eq. �4�:

dint � tint, (4)

here tint is the integration time of the spectrometernd is the velocity of the motion stage. The corre-ation between the collected spectrum and the refer-nce material spectra versus distance traveled isecorded in Fig. 7. The four dips and peaks in theichrome and alumina correlation series correspondo the position of the four grooves. When the grooveidth is two times greater than the integration dis-

ance, a clear material distinction is ensured, ashown in the correlation values at the third andourth grooves. The first two grooves are thinnerhan the critical width, so the correlation values at

ig. 8. �a� Microheater structure on thermal sprayed materialicromachined by the LIBS-controlled ultrafast laser system; �b�

canning electron microscope graph of the heater spiral pattern.

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hese two grooves are less distinctive than the twoidest grooves.Next, the LIBS control signal was added to the

xperiment. The control criteria were set to turn offhe laser when the correlation between the samplepectrum and the nichrome reference spectrum dropselow a certain value, say 0.2, and the correlationetween the sample spectrum and the alumina ref-rence spectrum exceeds a certain value, say 0.6, athe same time. The experiment confirmed that aroove wider than twice the integration distance en-ures a clear distinction between materials to turnhe laser off when the alumina substrate has beeneached.

It is found that after the SPEComp generates an offignal, the laser cut will extend a small distance pasthe edge of the groove because the system requiresome time to recognize the change in substrate ma-erial. We can approximate this response distancey multiplying the signal processing time by thetage velocity:

dres � tproc. (5)

he response distance is less than 40 �m for stageelocities less than 8000 �m�s.

. Application

he real-time controlled ultrafast laser micromach-ning system was tested to machine microheatertructures on thermal sprayed materials, as shown inig. 8. First, the sample materials undergo severalasses of laser machining without LIBS control at aedium-to-fast stage velocity, e.g., 4000 �m�s.nce electrical isolation is imminent, the LIBS feed-ack control is enabled. The stage speed is reducedo 500 �m�s to reduce dres to less than 5 �m, com-ared with �50 �m without the control. In thisay, the total laser micromachining time is mini-ized.Compared with passive machining processes with-

ut any feedback control, the SPEComp-controlledicromachining approach provides several impor-

ant advantages including less damage to the sub-trate layer, reduced machining time, more-uniformachining features, and reduced failure due to stress

racking in the alumina substrate at high tempera-ures.

. Conclusion

n this paper an on-line diagnostic method based onltrafast LIBS for real-time control of ultrafast lasericromachining is developed. A fiber-coupled CCD

pectrometer is used to collect the plasma emissionuring laser micromachining, from which the mate-ial being ablated can be determined and appropriateontrol applied to the laser, e.g., stopping once a spec-fied material has been reached in a multilayer struc-ure. Spectral, temporal, spatial, and laser-pulsessues associated with ultrafast LIBS were discussed,nd the development of the comparison algorithmsequired to identify different materials was pre-

ented. It was shown that after proper processing ofhe spectra, the presented comparison methods canrovide reliable and repeatable results. Aomputer-based control system based on the materialetection algorithms was implemented, and issuesssociated with the real-time control system wereiscussed. The technique was demonstrated for theicromachining of microheater structures on ther-al sprayed materials. Advantages of the ultrafastIBS-controlled micromachining technique include

ess damage to the substrate layer, reduced machin-ng time, more-uniform machining features, and re-uced failure of micromachined devices at highemperatures.

ppendix A: Nomenclature

dint, integration distance ��m�.dres, response distance ��m�.

r, linear correlation coefficient.delay, total real-time control delay �ms�.tint, integration time �gate time� of the spectrometer

�ms�.tproc, signal processing time �ms�.

, motion stage velocity ��m�s�.

ubscripts

od, modified.p, pulse.

The authors gratefully acknowledge financial sup-ort for this research from the National Scienceoundation under contract CTS-0121122 and the De-

ense Advanced Research Projects Agency under con-ract N000140010654. The authors thank J.utleber at the Center for Thermal Spray Researcht Stony Brook for the thermal spray samples.

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