A large number of nonintrusive laser-based techni-ques has been developed and applied to measure im-portant parameters, such as species concentrations,temperature, and flow velocities, in combustion aswell as fluid-dynamic problems; see, e.g., the booksby Eckbreth [1], Kohse-Höinghaus and Jeffries [2],and references therein. Although such a well-established technique as laser-induced fluorescence(LIF) today is a routine diagnostic, it still has to be ap-plied judiciously in order to deliver reliable data.Perturbing interferences are a well-known concern
that needs to be carefully addressed in the experi-mental design and data analysis. Common sourcesof interfering contributions in laser-based experi-
ments are different luminescence, particularly ifilluminating with UV light, and scattering from par-ticles, droplets, and surfaces. In most experimentsthe influence from these interferences may be dras-tically reduced using standard methods such asdetector gating, optical filters, and discriminationusing the polarization properties of the signal andinterfering radiation. A detailed discussion aboutinterferences common in laser-based combustion ex-periments is given in Eckbreth’s book [1] and inreferences therein.
Interfering radiation may constitute a particularlysevere obstacle in LIF measurements performedclose to surfaces or when particles or droplets arepresent in the probe volume. In combustion andfluid-mechanic research it is however of great inter-est to study phenomena in such environments. Forexample, investigation of thermal boundary layersat combustion chamber walls is of great importance
for the understanding of combustion processes incombustion engines. Furthermore, diagnostics inmultiphase (gas/liquid) environment are requiredin many practical combustion systems. For example,the atomization and evaporation of the fuel is a cri-tical step of utmost importance for a fundamentalunderstanding of the mechanisms leading to pollu-tant formation.Fuyuto et al.[3] used toluene-LIF thermometry to
measure a temperature gradient in nitrogen gas flowabove a heated wall and multiline NO-LIF thermo-metry to image temperature in the boundary layerclose to a metal wall positioned on a flat-flame bur-ner. Themultiline NO-LIF technique has been shownto be robust against the presence of particles, dro-plets, and surface scattering [4]. However, tuningthe laser wavelength across multiple NO absorptionlines results in long data acquisition times, whichprevents applications in unsteady combustion andflow systems.Schrewe and Ghandhi [5] performed near-wall
imaging of formaldehyde in a homogeneous chargecompression ignition (HCCI) engine using LIF. Theyused a through-the-wall arrangement to minimizethe effect of optical vignetting and allowed measure-ments to within 400 μm to the wall. Interfering sig-nals from the surface of the window providing opticalaccess to the combustion chamber were treated bysubtracting scaled background images recorded inmotored cycles.Illumination of particles and droplets give rise to
elastic scattering, i.e., the energy of the illuminatedparticle is conserved. Elastic scattering from parti-cles of sizes significantly smaller than the wave-length of the illuminating light, such as molecules,is termed Rayleigh scattering, while Mie scatteringoriginates from larger particles, e.g., liquid droplets.In practical LIF measurements usually an excita-tion/detection scheme where the wavelength of thedetected fluorescence is significantly shifted fromthe excitation wavelength is applied. With such anarrangement, elastic scattering is normally not an is-sue because it can be efficiently suppressed usingspectral filters. However, large particles can elasti-cally scatter the incident light with cross sectionsmuch larger than those associated with fluorescence[6]. Thus, when particles of size significantly largerthan the excitation wavelength are present, interfer-ence from Mie scattering can be a major problem inLIF imaging if the spectral filter does not havesufficient rejection capability outside the spectralpassband. For example, Edwards et al. [7] reportedthat Mie scattering interferences limit the applic-ability of LIF in high pressure solid propellantflames. They also found that the scattering was evenmore intense at measurement locations close tothe surface of the propellant strand, swamping theLIF signal and thereby preventing reliable datainterpretation.Although there are studies showing that good re-
sults can be achieved from LIF measurements close
to surfaces [3,5] and in volumes where particles arepresent [7] using traditional spectral filtering of thesignal, there are measurement situations wherespectral filtering may not suffice. For example, alarge amount of spuriously scattered light is commonwhen diagnostics is performed in practical combus-tion systems. The total contribution from interfer-ences may be large when this radiation is added tothe interferences discussed previously. The intensityof interfering signals is critically dependent on avariety of conditions, such as excitation wavelengthversus the wavelength of the fluorescence to be de-tected, detection angle, combustion chamber geome-try, surface material, droplet concentration, anddroplet size distribution.
The basic idea of the temporal filtering techniquepresented here is that interfering signals may be dis-criminated from the signal of interest if the two sig-nals have different temporal characteristics. Usingpicosecond laser pulses, together with fast gated de-tection, scattering and other short lived perturbingsignals may be discriminated from a fluorescence sig-nal, which often has a significantly longer lifetime.
Fuel visualization in fluid mechanics and enginecombustion studies is often performed by measuringthe LIF signal from a tracer species added to the fuel;see, e.g., [8,9] and references therein. Examples ofcommonly used tracers are acetone and toluene.Laser-induced fluorescence (LIF) of these species ty-pically has a lifetime on the nanosecond time scale.For example, using 266nm laser excitation thelifetime of acetone fluorescence in air is 1:1ns at323K and normal pressure [10] while the lifetime oftoluene fluorescence in pure nitrogen, using 248nmexcitation, is 45ns at ambient temperature and pres-sure [11]. When performing an experiment, detailedknowledge of tracers in the measurement environ-ment is the first and most important step in usingthe temporal filtering technique. Therefore we haveselected to demonstrate and evaluate the temporalfiltering technique by studying LIF signals fromthese relevant species under two different condi-tions, namely, for measurements close to a surfaceand measurements in a cloud of water droplets.Although this study is focused on combustion andfluid-dynamic applications, the temporal filteringtechnique might be useful in any imaging or spectro-scopic application where the signal of interest and in-terfering signals have different characteristics in thetime domain.
2. Concept and Theory
The concept of temporal filtering, which is schemati-cally illustrated in Fig. 1, takes advantage of the dif-ferent temporal characteristics of the interferingradiation and the signal of interest. Considering a si-tuation where the interference is due to scattering,which essentially is an instantaneous process, andthe signal of interest is fluorescence, then thefluorescence, which has a finite lifetime, may be se-parated from scattering using the different temporal
characteristics of the two signals. Obviously thefluorescing species must be excited with a laser pulseof duration much shorter than the fluorescence life-time and detected with high temporal resolution. Inimaging applications the signals are detected with atwo-dimensional detector, e.g., an intensified CCD(ICCD) camera. In order for the temporal filteringtechnique to be successful in this case the detectormust have a gate function with a rise time muchshorter than the fluorescence lifetime.Hence, the efficiency of the temporal filter is de-
pendent on the following properties: signal of inter-est (intensity and duration), interfering signal(intensity and duration), laser-pulse duration, andthe gate function of the detector (see Fig. 1). To accu-rately evaluate single-shot measurements, a time re-ference is needed to determine the exact delay timebetween the gate and the laser pulse. This problemarises due to time jitter between the laser pulse andthe gating of the detection system. In this study ac-cumulated recordings were analyzed, which makesthe jitter function yet another critical componentthat has to be accounted for in the evaluation.When detecting an optical signal, SðtÞ, with an
ICCD camera in time-gating mode, the CCD-chipintegrates the total amount of light that hits thedetector multiplied by the gate function of the photo-cathode in each pixel. This is schematically illu-strated in Fig. 2. The detected signal, whichdepends on the time delay between the gate andthe optical signal, may then be expressed as
InssðτÞ ¼Ztfti
½SðtÞGðt − τ − xÞ þ nðtÞ�dtþ nr: ð1Þ
Here InssðτÞ is the single-shot signal integrated (fromtime ti to tf ) by the CCD chip, τ is the time delay
between the laser pulse and the detector gate, SðtÞis the signal entering the photocathode of the detec-tor, Gðt − τ − xÞ is the gate function, and x is a sto-chastic variable, describing the temporal jitterbetween the optical signal and the detection. Thetemporal jitter is described by a probability densityfunction, JxðtÞ, which hereafter will be referred to asthe jitter function. Equation (1) includes contribu-tions from dark current, nðtÞ, and read-out noise,nr. After rearrangement it may be written as
InssðτÞ ¼Z∞−∞
½SðtÞGðt − τ − xÞ�dtþZtfti
nðtÞdtþ nr
¼ IssðτÞ þ ntotðtÞ; ð2Þ
where the integration boundaries for the short-livedsignal are set to infinity for mathematical reasons.Since both noise contributions are independent ofthe laser-induced signal, the noise term, ntotðtÞ, ishereafter neglected, resulting in the followingexpression:
IssðτÞ ¼Z∞−∞
½SðtÞGðt − τ − xÞ�dt: ð3Þ
It can be shown, see, e.g., [12], that the laser-induced signal, SðtÞ, is a convolution of the excitationfunction, i.e., the laser pulse, LðtÞ, and the intrinsicimpulse response function, RðtÞ:
SðtÞ ¼ LðtÞ ⊗ RðtÞ; ð4Þ
where the symbol ⊗ designates the convolution op-erator. The intrinsic impulse response function, RðtÞ,from now on called the response function for simpli-city, is what would be recorded as the observed signalin the ideal case of a δ-function excitation and a δ-function instrument response.
When accumulating data, Ntot number ofsingle-shot recordings are summed. In this case,
Fig. 1. Schematic illustration of the temporal filtering concept.The total signal is the sum of the signal of interest, e.g., a LIF-sig-nal, and an interfering signal, e.g., elastic scattering, of shorterduration. Using a detector that can be gated, such as an ICCD-camera, the interference may be suppressed by choosing an appro-priate time delay (τ) for the gate opening. The letter x is a stochas-tic variable corresponding to the temporal jitter between the laserfiring and the gate opening.
Fig. 2. Schematic picture of an ICCD-camera. The light enteringthe photo cathode (PC) is denoted SðtÞ. The photocathode is gated,i.e., the signal is multiplied by the gate function, Gðt − τ − xÞ. Fi-nally, this product is integrated over time, resulting in a detectedsignal intensity IssðτÞ, which is dependent on the delay time, τ.
substituting Eq. (4) into Eq. (3) results in thefollowing expression:
IaccðτÞ ¼XNtot
n¼1
IssðτÞ
¼Z∞−∞
�½LðtÞ ⊗ RðtÞ�
XNtot
n¼1
½Gðt − τ − xÞ��dt: ð5Þ
LðtÞ ⊗ RðtÞ has been moved outside the summationbased on the assumption that neither the laser pulsenor the response function vary during the accumula-tion. As discussed previously, the probability-densityfunction of the stochastic variable x, describing thetemporal jitter, is the jitter function JxðtÞ. The prob-ability of finding x in the interval [x0 < x ≤ ðx0 þ dxÞ],for small dx, is given by
P½x0 < x ≤ ðx0 þ dxÞ� ¼Z
x0þdx
x0
JxðtÞdt ≈ Jxðx0Þdx
≈N½x0 < x ≤ ðx0 þ dxÞ�
Ntot: ð6Þ
If Ntot would go to infinity, meaning an infinitenumber of accumulations, the first and last expres-sion in Eq. (6) would be equal. Instead of summariz-ing Eq. (5) over n, the summation is performed oversmall intervals dx:
IaccðτÞ ¼Z∞−∞
�½LðtÞ ⊗ RðtÞ�
×X∞i¼−∞
Nðidx < x ≤ ðiþ 1ÞdxÞGðt − τ − idxÞ�dt
≈
Z∞−∞
�½LðtÞ ⊗ RðtÞ�
×Ntot
X∞i¼−∞
JxðidxÞGðt − τ − idxÞdx�dt: ð7Þ
For small intervals dx, the expression may be rewrit-ten as continuous:
IaccðτÞ ≈ Ntot
Z∞−∞
�½LðtÞ ⊗ RðtÞ�
Z∞−∞
Gðt − τ − xÞJxðxÞdx�dt: ð8Þ
The second integral is a convolution between thejitter and the gate function. Finally, introducing
Hðt − τÞ ¼ ½G ⊗ Jx�ðt − τÞ ð9Þ
and using Eq. (4), the following expression can bewritten for the accumulated signal:
IaccðτÞ ≈ Ntot
Z∞−∞
SðtÞHðt − τÞdt: ð10Þ
3. Experimental Arrangement
In Fig. 3 a schematic picture of the experimental set-up is shown. The laser is a mode-locked Nd:YAG la-ser (Ekspla, PL2143C) generating laser pulses of30ps duration and 10Hz repetition rate with a wave-length of 1064nm. The laser light was frequencyquadrupled to 266nm. The laser-pulse energy was2–10mJ, depending on the measurement to be un-dertaken. The diameter of the laser beam wasaround 1 cm. Synchronization of laser firing and lightdetectors were accomplished using a pulse/delay gen-erator (SRS, DG535).
Three different optical setups for light focusingand collection were used. When examining the laserand camera properties a spherical quartz lens(f ¼ 200mm) was used to focus the laser beam.For the point measurements where the signals wereinvestigated with the streak camera, a cylindricalquartz lens (f ¼ 100mm) created an ∼1 cm highlaser sheet. When performing the imaging experi-ments, two quartz lenses were used [cylindrical lens(f ¼ −40mm) and spherical lens (f ¼ 150mm)],creating an ∼4 cm high laser sheet. For spectrally re-solved point measurement two lenses were used tocollect and focus the signal onto the entrance slitof a spectrometer (Digikröm DK 240). The spectro-meter has a focal length of 250mm, a grating with150 grooves=mm blazed at 500nm (first order), andwas mounted on a streak camera (Optronis, Opto-scope). The streak camera has UV-sensitive input op-tics, an S20 photocathode, a triggered sweep unit anda CCD camera (ANIMA-PX). The imaging experi-ments were performed using an ICCD camera(Princeton Instruments, PI-MAX2:512 (GEN II)), al-lowing a minimum time-gate width of 2ns.
Fig. 3. Schematic illustration of the experimental setup. The des-ignations are L1: spherical lens with focal length f ¼ 50mm anddiameter D ¼ 50mm, L2: UV achromatic spherical lens (B. Halle)with f ¼ 250mm and D ¼ 50mm, L3: spherical lens (B. Halle)with f ¼ 100mm and D ¼ 50mm mounted on the ICCD-camerausing a 31mm extension ring. Two different setups were usedin the measurement volume (see Fig. 4).
Two different measurement situations were inves-tigated; a toluene-seeded gas jet located close to analuminum surface and an acetone-seeded gas jet ina cloud of water droplets. The two measurementvolumes are seen in Figs. 4(a) and 4(b), respectively.In measurement volume A, a porous-plug burner(McKenna) was situated underneath the measure-ment volume, providing clean gas to minimize theMie scattering from airborne dust particles. A gasjet was placed in the middle of the burner, directinga toluene-seeded nitrogen gas flow onto an alumi-num plate. The toluene gas jet was surrounded bynitrogen gas delivered through the porous plug ofthe burner. The choice of nitrogen, instead of air,as bath gas is based on the fact that oxygen stronglyquenches the LIF-signal, which accordingly de-creases the fluorescence lifetime. The direction ofthe laser beam is indicated in Fig. 4, impinging onthe surface. In measurement volume B we usedthe same burner as in volume A. A water-filled nebu-lizer was placed above the burner. By running airthrough the nebulizer an aerosol of water dropletswas generated. A gas jet of acetone seeded air isissued into the water aerosol from a nozzle locatedin the center of the nebulizer.The acetone- and toluene-seeded gas jets were gen-
erated by bubbling air and nitrogen, respectively,through the corresponding species in liquid phase(at room temperature). All gas flows were controlledby mass-flow controllers (Bronkhorst), ensuringstable flow rates. In the measurement where volumeA was investigated, a 20mm liquid filter containingdimethylformamide was used to reduce elastic scat-tering, both in point measurements and imaging. Forthe same reason, a color filter (Schott filter, WG280,3mm thickness, which has ∼1% transmission at266nm) was used for measurement in volume B.
4. Measurements and Results
Measurements were performed in two differentsetups to demonstrate and evaluate the temporal
filtering technique. In measurement volume A [seeFig. 4(a)], the temporal filter is used to suppress in-terfering luminescence from an aluminum surface inLIF imaging of a toluene jet. Inmeasurement volumeB [see Fig. 4(b)], interfering Mie scattering from awater aerosol is suppressed in LIF imaging of anacetone jet.
A. LIF Measurements of Toluene Close toan Aluminum Surface
Measurements were performed in measurementvolume A, as shown in Fig. 4(a). Point measure-ments were performed with the streak camera/spectrograph combination to acquire both the spec-tral and the temporal characteristics of the toluene-LIF signal and the surface luminescence. The twosignals were acquired sequentially. The result of 400accumulated toluene-LIF signals is shown at right inFig. 5, while the result of 1200 accumulated record-ings of surface luminescence signal is shown at left inFig. 5. Fitting a single exponential function to the to-luene-LIF signal (integrated from 270 to 340nm) re-sults in a lifetime (1=e) of 5:2ns. As can be seen, thesurface luminescence signal is significantly shorter;the intensity has decreased to 1=e after ∼0:5ns.Thus, the surface luminescence is about 1 order ofmagnitude shorter than the toluene-LIF signal.
Spectrally, the toluene-LIF signal ranges from 275to 350nm. The upper limit of this range is in agree-ment with data reported by Koban et al. [13],whereas the lower limit value is slightly higher thanthe value reported by the same authors. The reasonfor this discrepancy is that the liquid filter (N,N-dimethyl formamide) used to reject 266nm radiationalso blocks a small part of the fluorescence on theblue side of the spectrum. The surface luminescencesignal is significantly broader than the toluene fluor-escence, ranging from 280 to 550nm. Hence, the sur-face luminescence spectrum almost entirely overlapsthe toluene fluorescence spectrum (275–350nm).This result clearly demonstrates a situation in whichinterference suppression using merely spectral filter-ing would be inadequate.
In order to make sure that the detected surfaceluminescence was not specific to excitation with
Fig. 4. Two different setups used in the measurement volume in-dicated in the overall experimental setup shown in Fig. 3. (a) Atoluene-seeded nitrogen gas jet impinging on an aluminum surfacewith a coflow of nitrogen gas. (b) An acetone-seeded air jet sur-rounded by a water aerosol generated by a nebulizer.
Fig. 5. (Color online) Spectrally and temporally resolved imagesof the aluminum surface luminescence (left) and the toluene-LIFsignal (right). Spectrally the signals initially overlap. Hence thesignificant difference in duration of the two signals indicates thattemporal filtering is applicable.
picosecond laser pulses, measurements were alsoperformed using laser pulses of 5ns duration withroughly the same pulse energy as the picosecondpulses. The surface luminescence signal appearedalso with the nanosecond pulses, showing the samespectral characteristic as for picosecond excitation.Moreover the lifetime of the interference signal didnot seem to change as the laser pulse energy was var-ied (though the laser energy was only shifted withina small range of energy on the mJ scale). This surfaceluminescence might be due to interband electrontransitions, also referred to as nonthermal metalglow [14], which has been reported for nano-, pico-,and non-pulsed radiation.Results from single-shot imaging of the toluene jet
close to the aluminum surface are shown in Fig. 6 forthree different gate delay times, τ. The same liquidfilter as was used in the point measurements was ap-plied for suppression of 266nm radiation. A 50nsgate width of the ICCD camera was used. For the re-sults shown in the upper picture series, both the to-luene jet and the surface were present in the probevolume, while for the images shown in the lower partthe toluene jet was turned off, showing only laser in-duced surface luminescence. The intensity of the lu-minescence signal is dependent on the orientation ofthe surface with regard to the laser beam, and theamount of absorbed laser light by the turbulenttoluene-gas jet. As can be seen, the toluene-LIFsignal is clearly visible for all three delay times,whereas the surface luminescence is hardly discern-
ible for a delay time of 8:9ns and completely gone fora delay time of 34:9ns.
In this particular measurement geometry, the half-width maximum of the surface-interference signalhas been evaluated to 700 μm from the single-shotimages in Fig. 6. Without using temporal filtering,the SSIR-value in the interference-signal area isevaluated to 0.8. However the SSIR value is closeto 1 when temporal filtering is applied with delaytimes around 35ns.
B. LIF Measurements of Acetone in a Water Aerosol
1. Single-Shot Imaging
Measurements were performed in measurementvolume B, as shown in Fig. 4(b). Planar laser-induced fluorescence measurements of the acetonejet and the water aerosol were performed for variousgate delays of the CCD camera. Figure 7 shows re-sults from single-shot measurements for three differ-ent gate-delay times, with both the acetone jet andthe aerosol present in the probe volume. For the re-sults shown in the upper picture series a 10ns gatewidth was used and for the lower picture series thegate width was 20ns. At τ ¼ −1:1ns the Mie scatter-ing signal from water droplets is significantlystronger than the acetone-LIF signal, which makesthe gas jet visible as a darker stripe in the centerof the images. At τ ¼ −0:1ns the total intensities ofthe respective signal are roughly equal, and the
Fig. 6. Single-shot images of measurement volume A for three different gate delays. The upper row images were acquired with thetoluene-seeded gas jet impinging on the aluminum surface. Bottom row: images acquired with the gas jet switched off. The signal visiblein the images in the bottom row is thus due to laser-induced luminescence from the aluminum surface.
two signals can still not be distinguished. At τ ¼0:9ns the LIF signal from the acetone jet is clearlyvisible in the image, whereas no Mie scattering sig-nal is visible. Two different ICCD-gate widths wereused (10 and 20ns), which does not seem to make adifference to the results of Fig. 7.
2. Experimental Characterization of theTemporal Filter
Two parameters are used to characterize the tempor-al filter: the filter transmission, TðτÞ, which is analo-gous to transmission for a spectral filter, and thesignal-to-signal-plus-interference ratio, SSIRðτÞ,which basically describes the cleanness of the signal.The parameters are defined by the following twoexpressions:
where Isignalacc ðτÞ and Iinterferenceacc ðτÞ are the accumulatedsignal and interference measured with a detectorgate delay τ. The reference signal, Isignalaccref , is the signalmeasured without any temporal filtering, i.e., using adetector gate wide enough to collect the entire signal
of interest. Thus, referring to Fig. 1, Isignalacc ðτÞ corre-sponds to the signal of interest multiplied by the gatefunction, i.e., the dark area labeled detected signal,similarly Iinterferenceacc ðτÞ corresponds to the curve la-beled interference multiplied by the gate function(which in the example presented in Fig. 1, resultsin no detected interference), and Isignalaccref is given bythe curve labeled signal of interest. The reason forusing SSIR instead of signal-to-interference ratio(SIR) or interference-to-signal ratio (ISR), is simplyto avoid large ratios as a result of division with num-bers close to zero. The SSIR ranges from 0 to 1, whereSSIR ¼ 1 corresponds to complete suppression of theinterfering signal.
In order to characterize the temporal filter, 100images were accumulated for a number of differentgate delays and for two different gate widths; 10and 20ns. The acetone jet and the water aerosol werestudied sequentially. After background subtraction, apixel area was defined (∼30 × 90pixels) where themaximum acetone LIF signal was found. The totalsignal within this pixel area was determined forthe acetone-LIF image and the aerosol image, respec-tively, yielding ILIFacc ðτÞ and IMie
accref , were measured (100 accumulations) usinga 100ns gate width and a delay set to −50ns in orderto get the signals roughly in the middle of the timewindow of the gate. The measurement results areshown as (×) and (∘) in Fig. 8. The curves presentedin Fig. 8 represent simulated results that will beexplained and discussed below.
Fig. 7. Single-shot images of measurement volume B for three different gate delays. The upper row images were acquired with a gatewidth of 10ns; the images in the lower row were recorded with a gate width of 20ns.
The graph corresponding to the 10ns gate window[Fig. 8(a)] shows that for delay times between −10and 0ns the SSIR is around 0.2, i.e., the interferingMie scattering signal is four times higher than theacetone-LIF signal, and the transmission parameteris high. In fact, for several delay times between −5and 0ns TðτÞ is higher than unity. This behavior isdue to the characteristics of the detector gate, whichshows an overshooting behavior when it opens (seeFig. 12). At τ ¼ 0ns the SSIR rises steeply to ∼1, re-flecting the transition from zero to maximum sup-pression of interfering Mie scattering signal. At thesame time, T decreases as the filter gradually blocksmore and more of the acetone-LIF signal. This de-crease is obviously much slower than the fast in-crease of SSIR since the LIF-signal is much longerthan the elastic scattering signal. The TðτÞ curvefor τ ≥ 0 basically reflects the fluorescence decaycurve of acetone.For 20ns gate width, see Fig. 8(b), the two para-
meters show essentially the same qualitative beha-
vior as for the 10ns gate width. Not surprisingly,the main difference is that the time period prior tothe onset of interference suppression at τ ¼ 0 nowis 20ns long instead of 10ns. The TðτÞ curve showsan overshooting transient at −17ns followed by a sec-ond oscillation with maximum intensity at −4ns.Again, this behavior is associated with the temporalcharacteristics of the detector gate (see Fig. 12).
3. Time-Resolved Measurements
Time-resolved measurements using the streak cam-era were carried out to characterize all the propertiesof the temporal filtering system necessary to makesimulations using the theory presented in Section 2.Besides the acetone-LIF and Mie-scattering signals,which were measured sequentially, the systemparameters: laser-pulse temporal characteristic,laser-pulse jitter, and ICCD-gate functions, weremeasured.
Since both the acetone-LIFand the interfering Miescattering signals are laser-induced, their temporalcharacteristics will be influenced by the temporalshape of the laser pulse. Therefore, the laser pulsetemporal characteristic was investigated by perform-ing Rayleigh scattering measurements in air. Toavoid interference due to Mie scattering from dustparticles, the probe volume was surrounded by cleanair flowing through the porous plug of the McKennaburner. The Rayleigh scattering signal was focusedonto the entrance slit of the streak camera. Thestreak rate was 50ps=mm, providing a temporal re-solution of 10ps. 200 accumulated recordings wereacquired using the jitter correction tool in the camerasoftware. The full width at half-maximum (FWHM)of the laser pulse is ∼30ps, which is in excellentagreement with the specification by the lasermanufacturer and the Mie-scattering signal seen inFig. 10.
For the acetone-LIF and Mie-scattering measure-ments, a spectrograph, with a grating having150 grooves=mm (blazed for 500nm), was positionedin front of the streak camera. This arrangement pro-vided a spectral resolution of 0:3nm, covering a
Fig. 8. (Color online) Simulated (solid and dashed curves) and experimental (× and ∘) results showing the efficiency of the temporal filter,when applied in measurement volume B [shown in Fig. 4(b)]. SSIRðτÞ is indicated by (∘) and solid curves, whereas TðτÞ is indicated by (×)and dashed curves. (a) Result using a 10ns gate. (b) Result using a 20ns gate.
Fig. 9. Temporally resolved acetone-LIF signal. The solid curvedesignates the measured data, while the dashed curve isSLIFðtÞ. SLIFðtÞ was determined by fitting a single-exponentialfunction to the decaying part of the measured curve, extrapolatingthe fit to t ¼ 0, and then convolving the fit with the temporal shapeof the laser pulse.
range of 300nm, and 50ps temporal resolution cover-ing a temporal range of 4:8ns. 500ð¼NtotÞ accumu-lated streak camera images were acquired withoutcorrecting for temporal jitter. The detected acetone-LIF signal was integrated over the full spectral rangecovered by the detector, i.e., 250–550nm. Thus, theentire acetone-LIF spectrum, which ranges from350 to 550nm, contributed to the temporally re-solved LIF signal shown as a solid curve in Fig. 9.Fitting a single exponential function to the decayingpart of the measured curve resulted in a lifetime(1=e) of 1:23ns, which agrees well with 1:2ns re-ported by Ossler and Aldén [10]. It should be men-tioned that the measurements presented here wereperformed at room temperature, while Ossler et al.conducted measurements at a somewhat higher tem-perature; 323K. The reason why only the latter partof the curve was used in the fit is because the shape ofthe early part of the signal is influenced by the in-strument function.Assuming an ideal detection system, the accumu-
lated LIF signal may be expressed as
ILIFðtÞ ¼XNtot
n¼1
Sðt − xÞ
¼X∞j¼−∞
Nðjdx < x ≤ ðjþ 1ÞdxÞSðt − xÞ
≈ Ntot
X∞j¼−∞
Sðt − jdxÞJxðjdxÞ ¼ Ntot½S ⊗ J�ðtÞ
¼ Ntot½RLIF ⊗ L ⊗ J�ðtÞ: ð13Þ
The measured LIF signal is hence a convolution ofthe response function RLIF, the laser pulse L, andthe jitter function J. The response function RLIFwas extracted by extrapolating the fitted curve to t ¼0 and multiplying it with a constant so that the areaunder the fitted curve is equal to the area under themeasured curve. Following Eq. (4), the LIF signal
was finally extracted by convolving RLIFðtÞ with thetemporal shape of the laser pulse, LðtÞ (seeFig. 10), i.e., SLIFðtÞ ¼ ½RLIF ⊗ L�ðtÞ. The result is dis-played as the dashed curve in Fig. 9.
The interfering signal, i.e., Mie scattering fromdroplets in the water aerosol, was investigated usingthe same experimental equipment as was used forthe LIF-signal measurement, except that the nebuli-zer was now switched on and the acetone turnedoff, generating the water aerosol, with a coflow ofclean air delivered through the porous plug of theMcKenna burner. Accumulated data (Ntot ¼ 200)was collected with a streak rate of 25ps=mm (provid-ing 5ps temporal resolution) and using jitter correc-tion in the streak camera software. The registeredsignal may be expressed as
IMieðtÞ ¼XNtot
n¼1
SðtÞ ¼ Ntot½RMie ⊗ L�ðtÞ: ð14Þ
Using this expression together with Eq. (4), SMieðtÞcan be extracted simply by dividing the measuredsignal,IMieðtÞ with Ntotð¼200Þ. The result is shownin Fig. 10. The curve shows a Gaussian shape witha width of 30ps (FWHM), which is in agreement withthe laser-pulse duration.
A measurement was conducted to estimate thetime-jitter function of the system. The same experi-mental setup was used as for the laser pulse charac-terization, except that no jitter correction wasperformed. The result of 10000 accumulated record-ings is shown in Fig. 11. The detected signal may beexpressed as
Fig. 11. Investigation of the jitter function using the Rayleigh-scattering signal of ambient air. The detected signal correspondsto the jitter function convolved with the laser pulse, i.e., ½J ⊗ L�ðtÞ.
Fig. 10. Temporally resolved Mie scattering signal, SMieðtÞ, re-corded in the water aerosol.
where x is the stochastic variable whose probabilitydistribution is described by the probability densityfunction jxðtÞ, i.e., the time-jitter function definedin Eq. (6). Hence the recorded signal reflects the jitterfunction convolved with the laser pulse, which isshown in Fig. 11. The temporal width of the curveis 130ps (FWHM).The efficiency of the temporal filter is critically de-
pendent on the rise time of the detector gate. As canbe seen in Fig. 1, a shorter rise time means that ashorter gate delay, τ, may be used than for a longerrise time, leading to higher filter transmission, T [seeEq. (11)], and thereby a stronger detected signal.Therefore, the gate function of the ICCD camerawas characterized by performing a Rayleigh-scattering measurement in ambient air. The sameexperimental setup was used as for the laser-pulseand jitter-function investigations, except that thestreak camera was replaced by the ICCD cameraas the detector system. The measurements were per-formed by acquiring a sequence of accumulated(hardware) images recorded at a number of differentdelay times, evenly distributed with a time separa-tion dt. After background subtraction, a pixel area(∼20 × 40 pixels) corresponding to the signal gener-ated in the vicinity of the focus of the laser beam
was integrated. Three different gate widths wereinvestigated; 10, 20, and 100ns.
Mathematically, the light reaching the CCD chipat time t and delay time τ may be expressed as
Bðt; τÞ ¼XNacc:
n¼1
Lðt − xnÞGðt − τÞ: ð16Þ
This signal integrated over time results in adetected signal IBðt − τÞ, which may be written as
The negative sign in front of τ is used only for math-ematical convenience. The sum to the right describesthe laser pulse convolved with the jitter function,which is given by KðtÞ defined in Eq. (15), meaningthat the expression may be rewritten:
IBð−τÞ ≈Z∞0
Gðtþ τÞKðtÞdt ¼ ½GðτÞ ⊗ KðtÞ�
¼ ½G ⊗ J|fflfflffl{zfflfflffl}¼HðτÞ
⊗ L�ðτÞ: ð18Þ
The data were deconvolved with the temporalcurve of the measured laser-pulse (shown in Fig. 10)using the Wiener deconvolution [15], leaving merelyHðτÞ ¼ ½G ⊗ J�ðτÞ. The resulting curves for gatewidths 10 and 20ns are shown in Fig. 12(a), whilethe curve corresponding to the 100ns gate width isdisplayed in Fig. 12(b).
Fig. 12. Characterization of the detector gate function by Rayleigh scattering measurements in ambient air. (a) Results of convolutionsbetween the gate and the jitter functions, i.e., HðτÞ ¼ ½G ⊗ J�ðτÞ, for the 10ns (solid curve) and 20ns gates (dotted curve), respectively, areshown in (a); the corresponding result for the 100ns gate is shown as the solid curve in (b). The dashed curve in (b) is the top-hat function fitto the data. The top-hat function was used to simulate the reference signal.
Equation (10), derived in Section 2, was used tocalculate the signal output from the temporal filterversus time delay of the camera gate:
IaccðτÞ ≈ Ntot
Z∞−∞
SðtÞHðt − τÞdt: ð10Þ
Input data to this equation are the measuredsignals described in the previous section, i.e., theacetone-LIF signal, SLIFðtÞ (see Fig. 9), the interfer-ing Mie-scattering signal, SMieðtÞ (see Fig. 10), thefunction corresponding to the gate function con-volved with the jitter, i.e., HðτÞ (see Fig. 12). Theacetone-LIF signals calculated for 10 and 20ns timegate are denoted ILIF10nsðτÞ and ILIF20nsðτÞ, respectively.Similarly, the corresponding Mie-scattering signalsare denoted IMie
10nsðτÞ and IMie20nsðτÞ. Using these signals
in Eq. (12) results in SSIRðτÞ-curves for 10 and 20nsgate widths, shown as the solid lines in Figs. 8(a) and8(b), respectively.In order to calculate the filter transmission, TðτÞ,
using Eq. (11), a reference intensity, corresponding toa situation with a completely open filter, has to becalculated. This intensity was determined using thedata collected with the 100ns gate. HðτÞ for the100ns gate is shown in Fig. 12(b). As can be seenin this figure, the intensity oscillates, particularlyright after the initial transient when the gate opens.Therefore, a top-hat function was fitted to the data[dashed curve in Fig. 12(b)], in order to make the in-tensity independent of the time delay. TheHðτÞ curvecorresponding to the fitted curve was then used to-gether with SLIFðtÞ in Eq. (10) to calculate the refer-ence signal ILIFaccref . Using the acetone-LIF signalscalculated for 10 and 20ns time gate, i.e., ILIF10nsðτÞand ILIF20nsðτÞ, together with ILIFaccref in Eq. (11), thefilter transmission, TðτÞ, was calculated for the 10and 20ns gates, respectively. The results are plottedwith dashed lines in Figs. 8(a) and 8(b), respectively.The calculated results based on input data from
the time-resolved measurements were comparedwith the experimental results from imaging withthe ICCD camera, plotted as symbols (×) and (∘) inFig. 8. In order to make a direct comparison, differ-ences in spectral sensitivity between the detectionsystems used for the time-resolved measurements(streak camera and spectrograph) and the imagingmeasurements (ICCD camera) have been taken intoaccount. This matter was dealt with by comparingthe ratio ILIFaccref=I
Mieaccref obtained in the time-resolved
measurements with the corresponding ratio for theimaging measurements and use this information tocorrect the calculated SSIRðτÞ. The calculated curvesagree well with the imaging data both for the 10 and20ns gate, showing that the model is able to accu-rately predict the characteristics of the temporalfilter.
5. Discussion
In this work two measurement situations have beeninvestigated, namely, toluene-LIF measurementclose to a surface and acetone-LIF measurement ina water aerosol. In both situations strong contribu-tions from interfering light are present. These casestudies were selected to illustrate how temporal fil-tering could be used to improve the signal to interfer-ence ratio.
In the first experiment, shown in Fig. 4(a), thetoluene-LIF signal and the surface luminescencespectrally partly overlap, as can be seen in Fig. 5.By using toluene as the tracer molecule in a nitrogenrich atmosphere, the toluene-LIF signal has asignificantly longer lifetime than the surface lumi-nescence, making the use of a temporal filteradvantageous. Using a spectral filter, transmittingwavelengths shorter than 350nm, would reducethe interfering signal significantly. However, a con-tribution ranging from 285 to 350nm will remain.This contribution significantly overlaps the toluene-LIF signal and can therefore not be suppressed witha spectral filter, without decreasing the LIF-signalsubstantially.
It should however be pointed out that, althoughthe two signals might have different lifetimes, asin Fig. 5, the efficiency of temporal filtering also de-pends on the relative intensities of the two signals.The ability to suppress interfering light with anICCD camera is dictated by the intensifier on/off ra-tio, i.e., the ratio of signal output when the intensifieris electrically turned on and off. Traditionally, ICCDcameras are gated by changing the voltage betweenthe photocathode and the input of the MCP (seeFig. 2). With the input of the MCP at 0V, a positiveelectrical potential on the photocathode means thatphotoelectrons will be attracted by the positivelybiased photocathode and they will therefore not en-ter the MCP, i.e., the intensifier is gated off. Never-theless, a small fraction of the photoelectrons mightbe attracted by the electric field of the MCP andthereby reach its input and get multiplied as theypass through. This leakage of photoelectrons limitsthe intensifier on/off ratio, which typically is 107∶1in the visible spectral range but drops significantly inthe UV region [16]. With the ICCD camera usedin the present experiments we estimate that the in-tensifier on/off ratio was ∼105 : 1 at 266nm.
The on/off ratio in the UV regime may be signifi-cantly improved, reaching the same level as in thevisible range, by gating both the photocathode andthe MCP. In fact, this gating concept can bring therejection ratio up to above 108∶1 [16]. Hence, themaximum rejection ratio that the temporal filteringtechnique can provide is ultimately set by the inten-sifier on/off ratio, which with state-of-the-art ICCDcameras may reach above 108∶1.
The rejection ratio has not been included in the si-mulations, since the experimental noise was largerthan the residual interference signal, i.e., the leak-age of photoelectrons when the detector gate is off.
To take the rejection ratio into account, one moreterm has to be introduced in the denominator ofSSIR, due to the fact that a closed gate still detectsincoming photons with a rejection ratio (or on/off-ratio, ron=off ) as stated above. The additional termwould be the interference signal that hits the photo-cathode as it is turned off divided by the rejectionratio:
Here ron=off is the rejection ratio and Iinterferenceaccref is theinterference signal integrated using a long camera-gate function (100ns). In most cases the contributionfrom the residual interference signal is insignificantmaking SSIR0 and SSIR approximately the same.By comparison, spectral filtering using color filters
or interference filters typically provides rejection ra-tios >105∶1. The most narrowband filters are thosebased on atomic/molecular absorption. Some of thesefilters may have extremely high rejection ratios, forexample, mercury (vapor) filters may reach rejectionratios >107∶1 [17]. A disadvantage with spectral fil-ters is that fluorescence may be generated from thefilter material if the intensity of the incident radia-tion is too high, particularly if it is located in the UVspectral regime [18].The second experimental setup, shown in Fig. 4(b),
was designed to study a situation with an interferingsignal from elastic scattering. The elastically scat-tered light has a temporal profile similar to the laserpulse, as can be seen in Fig. 10. From the single-shotimages shown in Fig. 7 it is clear that the temporalfilter is able to discriminate the elastic scattering sig-nal from the acetone-LIF signal with a delayed detec-tor gate. For a delay of 0:9ns there is no contributionfrom elastic scattering visible in the image, neitherfor the 10ns gate nor the 20ns gate. This observationis further confirmed in Fig. 8, where it can be seenthat SSIR ¼ 1, i.e., the interfering contribution iszero, for both gate widths at 0:9ns delay. Further-more, at the same delay TðτÞ ≈ 0:6, i.e., about 60%of the acetone-LIF signal is detected.As can be seen in Fig. 8, the filter characteristics
calculated based on input data from time-resolvedmeasurements (lines) agree well with the data mea-sured with the ICCD camera (symbols). There is scat-tering in the measured data points though, whichprimarily is due to variations in the acetone jet andthe water aerosol. This scattering would decrease if alarger number of images are accumulated. Also, de-tector noise makes the data analysis uncertain at lowsignal levels, which is evident for the SSIR data re-corded for delays longer than 7ns. For positive delaytimes, the calculated TðτÞ curve is lower than themeasured data points, which is more pronouncedfor the 20ns gate. This deviation is most likelydue to a systematic error originating from the analy-
sis of the time-resolved LIF-signal (see Fig. 9). In theanalysis of this signal, a single exponential functionwas fitted to the measured signal. Assuming a singleexponential decay is a good approximation, but it cer-tainly introduces a minor error in the latter part ofthe signal, since it has been reported in the literaturethat the acetone-LIF signal is best described by adouble-exponential function [10]. Furthermore, onlythe first four nanoseconds of the signal could be usedfor the fit.
The results from the filter simulations presentedhere are only strictly valid for the laser and detectionsystem used in the present work. However, the the-oretical model apply universally, meaning that thebehavior of any temporal filtering system may bepredicted for an arbitrary set of signals as long asthe time-jitter function, laser pulse, and gate func-tion are known
It should be emphasized that temporal filtering isa complementary technique to traditional spectralfiltering. In situations with an interfering signalfrom elastic scattering, a spectral filter should beused as long as its transmission curve is sharp en-ough that a sufficiently large fraction of the signalof interest is transmitted. Also, it should be empha-sized that a spectral filter should always be used insituations with extremely strong elastic scattering inorder to prevent damaging the photocathode of thedetector.
Using the model to evaluate experimental data re-quires that the measurement system as well as thetemporal characteristics of the detected signals areknown. This is important if signals with differentlifetimes are to be compared, which is done when sig-nal intensities are corrected for quenching. Quench-ing correction of LIF images acquired with a delayedcamera gate has to be compensated for the use of thetemporal filter as well. LIF data that are correctedfor quenching are multiplied with a factor Cq, the in-verse fluorescence quantum yield [1]:
Cq ¼ 1Φ ¼ A21 þQ
A21; ð19Þ
where A21 is the Einstein coefficient for spontaneousemission and Q is the quenching rate coefficient. Ifthe LIF signal is described by a single exponentiallydecaying function, the effective lifetime (τeff ¼ 1=½CqA21�) could be calculated. The correction termwhen using temporal filtering, (CTF), is a compensa-tion for the early signal losses, which is the inverse ofTðτÞ, seen in Eq. (11). In this expression thequenched LIF signal is evaluated.
This expression could be simplified, assuming anideal camera-gate (Heaviside step function), deltapeak time jitter and delta peak laser pulse. Thesesimplifications facilitate the integration, providingthe approximate correction factor
This means that a correction factor can easily be de-termined if the Einstein coefficient, the quenchingrate coefficient, and the delay time are known.However, it should be pointed out that this is an
approximation. The validity of this approximationis dependent on the deviation between actual laserpulse, time-jitter and camera-gate function andthe corresponding ideal functions mentioned above.Moreover quenching strongly affects the fluorescencequantum yield, which could result in weak signalstrength when the strongest part of the LIF signalis left undetected.Potential applications of the temporal filtering
technique could be experiments where a spectrallybroad interference whose lifetime is shorter thanthe laser pulse duration is present, like in the firstcase in this study, or experiments in which verystrong elastic scattering is an issue, like in thesecond case in this work. It could also be used in si-tuations where the interfering light occurs in a wave-length regime for which no efficient spectral filtersare available. The applicability of temporal filteringof LIF signals is obviously dependent on the detectedspecies, through its fluorescence lifetime (τeff ) andquantum yield (Φ), pressure, and temperature. Typi-cal excitation wavelength (λexc), emission wavelengthrange, (λem) fluorescence quantum yield, and effec-tive fluorescence lifetime for different species of in-terest in combustion research are listed in Table 1.The listedΦ and τeff values are given for room tem-
perature (295K) and normal pressure (1 atm), exceptfor OH where the reported data are the averagevalue obtained in the burnt gases of a premixedCH4=air flame (fuel equivalence ratio: ϕ ¼ 1:26)[19]. Data for toluene are given for two different bathgases; nitrogen and air. The fluorescence quantumyield is a factor of 75 times lower in air than in nitro-gen, which is due to strong quenching by oxygen. Inenvironments with insignificant oxygen concentra-tion, the very long τeff and the high Φ make toluenean attractive fuel tracer to use in diagnostics withtemporal filtering. Accordingly, due to the shortτeff in air, the usefulness of temporal filtering ontoluene-LIF signals in air is limited. Consideringsuitability for temporal filtering exclusively, 3-pentanone is a better alterative than acetone as afuel tracer since it has almost twice as long τeffand twice as high Φ than acetone.
In many practical applications of LIF, e.g., incombustion engines, substantial pressure and tem-perature variations have to be considered. To inves-tigate fuel/air mixing processes in engines, a fueltracer, e.g., acetone, toluene, or 3-pentanone, isadded to the fuel and the LIF signal from the traceris monitored. The tracer species is only present be-fore the fuel/air mixture is burned, i.e., before com-bustion. Therefore, in order to predict typicalacetone fluorescence lifetimes, we performed a sim-ple simulation of pressure and temperature curvesversus crank angle position in a typical pistonengine.
Based on a simple expression for the cylinder vo-lume versus crank position taken fromHeywood [20],an isentropic calculation of pressure and tempera-ture curves was performed. The compression ratiowas set to 10, which is typical for a spark-ignition en-gine, the ratio between rod and crank radius was setto 4, which is typical for a medium-sized engine, andthe isentropic coefficient of the fuel/air mixture wasfixed at 1.3, which is a value typical for an unburnedstoichiometric mixture of gasoline and air [20]. Withthe pressure and temperature at −180° (crank angle)set to 1 atm and 400K, respectively, a pressure curveranging from 2 atm at −90° to 20 atm at 0° and a tem-perature curve ranging from 465 to 800K wereobtained.
Using these data as input to an expression for thequantum yield of acetone LIF reported by Thurberet al. [21] Φ is rather constant, ranging between0.00046 and 0.00050, i.e., a variation of about 8%.The corresponding calculated lifetimes range from1.53 to 1:66ns, i.e., a variation of about 8%. The cal-culations were performed with nitrogen as bath gas.In air the fluorescence quantum yields are expectedto be slightly lower [22]. It is reasonable to assumethat the trend of fluorescence lifetimes for the enginecycle simulated here would be similar with air asbath gas. This investigation indicates that the cap-ability of temporal filtering of acetone-LIF signalswill not be degraded for pressure and temperatureconditions typical in combustion engines.
Relative fluorescence quantum yields for 3-pentanone and toluene have been measured using248nm excitation in a motored optical engine [23].For 3-pentanone, the relative fluorescence quantumyield ranges from 0.4, at the highest pressure andtemperature, to 1.1, at the lowest pressure and tem-perature. Hence, the relative fluorescence lifetimeswill vary accordingly. Despite this decrease in
Table 1. Photophysical Properties of Species of Interest in Combustion Research
Species λexc (nm) λem (nm) Φ τeff (ns) Bath Gas Reference
Acetone 266 300–550 0:55 × 10−3 1.1 Air Φ from [28] τeff from [10]Toluene 266 260–350 0.30 82 N2 Φ from [29] τeff from [30]Toluene 266 260–350 4 × 10−3 0.65 Air Φ from [29,31] τeff from our measurement3-Pentanone 266 300–550 1:0 × 10−3 1.9 Air Φ from [28] τeff from [10]OH 309 308–315 2:5 × 10−3 1.8 Flame Φ and τeff from [19]H2CO 355 350–600 7 × 10−3 33 N2 Φ from [27,32] τeff from [27]
lifetime, we judge that temporal filtering could be ef-ficient in 3-pentanone LIFmeasurements in engines.As mentioned previously, the LIF signal of toluene
in air is strongly quenched by the presence of oxygen,resulting in a relatively short fluorescence lifetime(0:65ns at ambient conditions, see Table 1). Hencethe decrease in fluorescence quantum yield withincreasing pressure and temperature for a motoredengine, reported by Koban et al. [23], will result ineven shorter lifetimes and consequently the applic-ability of temporal filtering is expected to be evenmore limited under these conditions.Formaldehyde (H2CO) is formed as an intermedi-
ate species in the preheating phase of hydrocarboncombustion (see, e.g., [24]). As it is consumed inthe reaction zone, it is well suited as an indicator ofcool-flame regions. As can be seen in Table 1, formal-dehyde has a long lifetime (33ns) at room tempera-ture and normal pressure with nitrogen as bath gas.Fluorescence lifetimes of formaldehyde have beenmeasured in an atmospheric pressure CH4=air flame[25]. It was found that the lifetimes range from 6 to18ns. Similar lifetimes were found in a DME/air la-minar diffusion flame studied by Brackmann et al.[26]. The fluorescence lifetime decreases with in-creasing pressure. Metz et al. [27] found that the life-time decreases from 9.1 to 5:9ns as the pressureincreases from 1 to 10 bar at 770K. The lifetime offluorescence from formaldehyde present in cool flameregions during engine combustion is therefore ex-pected to be at least several nanoseconds at engineconditions. Thus, formaldehyde LIF appears to bewell suited for temporal filtering.The data for OH given in Table 1 are from
resonance-LIF measurements, i.e., excitation at309nm (v0 ¼ 0←v00 ¼ 0) followed by detection of thefluorescence around 309nm (v0 ¼ 0 → v00 ¼ 0). Inpractical OH-LIF diagnostics it is common to exciteat 283nm (v0 ¼ 0←v00 ¼ 0) and detect the fluores-cence around 309nm (v0 ¼ 0 → v00 ¼ 0). This ap-proach results in lower fluorescence signalscompared to resonance LIF due to a lower Franck–Condon factor for the absorption transition and lowerfluorescence quantum yield due to quenching fromv0 ¼ 1 (significant when oxygen is present). The rea-son for using such excitation/detection schemes is tobe able to suppress scattered light at the excitationwavelength using a spectral filter. With the temporalfiltering technique it might be possible to use reso-nance LIF in practical applications. In resonanceLIF, the fluorescence is emitted from the directlypumped vibrational energy level, which means thatit appears spectrally close to the excitation wave-length. Such an approach would be beneficialsince the resonant-fluorescence signal is typicallysignificantly stronger than signals generated withexcitation/detection schemes in which the fluores-cence originates from energy levels other than thedirectly pumped.
6. Summary
A temporal filtering technique applicable in laser di-agnostics has been developed and characterized. Themethod is complementary to traditional spectral fil-tering. The method requires a laser system thatdelivers short laser pulses and a detector that canbe gated. In this work a setup based on 30ps laserpulses and an ICCD camera has been used to inves-tigate two measurement situations in which strongcontributions from interfering radiation are present,namely toluene-LIF measurement close to an alumi-num surface and acetone-LIF measurement in awater aerosol. A theoretical model was developed tosimulate and evaluate the temporal filter for a gen-eral measurement situation based on pulsed-laserexcitation together with time-gated detection. Thismodel allows LIF signals to be corrected for the sig-nal losses introduced by the temporal filter. Tempor-al filtering implies that quenching correction factorshave to be modified. A simplified correction term forsuch modification is derived. Simulations of the tem-poral filter were performed for the acetone-LIF ima-ging inside a water aerosol. System parameters, suchas the temporal shape of the laser pulse, temporaljitter, and the ICCD gate function, were determinedfrom time-resolved measurements using a streakcamera and then used as input data to the simula-tions. The simulated results agree well with the mea-sured data. Overall, the results show that thetemporal filter is capable of efficient suppression ofinterfering signal contributions, and we believe thatit will make an important tool in practical applica-tions of LIF. The ability to suppress interferences de-pends on the photophysical properties of the speciesto be probed. Therefore these properties have beenlisted and discussed for several species commonlystudied by LIF in combustion research, to provideguidelines for optimum use of the temporal filteringtechnique.
The authors thank Olof Johansson for technicalassistance and fruitful discussions. This work hasbeen financed by the Swedish Energy Agency(Energimyndigheten) and SSF (Swedish Foundationfor Strategic Research) through CECOST (Centre forCombustion Science and Technology).
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