Planar laser induced fluorescence in aqueous flows
Planar laser-induced fluorescence (PLIF) is a non-intrusive technique for measuring scalar concentrations in fluid flows. A fluorescent dye is used as a scalar proxy, and local fluorescence caused by excitation from a thin laser sheet can be related to dye concentration. This review covers quantitative PLIF in aqueous flows, with discussions of fluorescence theory, experimental methods and equipment, image processing and calibration, and applications of the technique.
The use of soluble dyes for aqueous flow visualization was already in evidence in the nineteenth century, when Osbourne Reynolds performed his famous experiments on laminar and turbulent flow in round pipes (Reynolds 1883). However, a quantitative extension to this visualization technique would not appear for another century, when laser-induced fluorescence (LIF) was pioneered by Dewey (1976), Owen (1976), and Liu et al. (1977). The technique was then adopted in earnest by Paul Dimotakis at Caltech who, along with his students Manoochehr Koochesfahani and Werner Dahm, published a number of early seminal LIF studies (e.g., Dimotakis et al. 1983; Koochesfahani and Dimotakis 1986; Dahm and Dimotakis 1987). Two excellent early tutorials on the topic are given by Walker (1987) and Ferrier et al. (1993). LIF can be used to measure scalar concentrations at a point (e.g., Sreenivasan and Prasad 1989; Komori et al. 1993), along a line (e.g., Koochesfahani and Dimotakis 1985; Hannoun and List 1988; Papantoniou and List 1989), in two-dimensional planes (Dahm and Dimotakis 1987), and in three-dimensional volumes (e.g., Tian and Roberts 2003; Van Vliet et al. 2004).
The most common application of LIF in fluid flows is two-dimensional planar laser-induced fluorescence (PLIF). The focus of this review article is on the quantitative application of PLIF to aqueous flows (for PLIF in gaseous flows, see Van Cruyningen et al. 1990). While three-dimensional LIF methodology is not extensively discussed in this review, the methodology is a simple extension of the two-dimensional techniques.
In all forms of LIF, a laser is used to excite a fluorescent species within the flow. Typically, the tracer is an organic fluorescent dye such as fluorescein or rhodamine. The dye absorbs a portion of the excitation energy and spontaneously re-emits a portion of the absorbed energy as fluorescence. The fluorescence is measured optically and used to infer the local concentration of the dye.
2 Theoretical background
2.1 General fluorescence theory
2.2 Theory as applied to PLIF
3 Experimental configurations
A PLIF system requires an appropriately paired laser and fluorescent dye combination, with at least part of the laser power within the absorption band of the dye. Continuous wave (CW) argon-ion lasers operating at 488 and/or 514.5 nm are used as the excitation source in approximately three-quarters of aqueous PLIF experiments reported in the fluid mechanics literature. Pulsed, frequency-doubled Nd:YAG lasers operating at 532 nm are used in most of the remaining experiments, and their use has become increasingly common in recent years. A few experiments have employed copper vapor lasers (Yoda et al. 1994; Karasso and Mungal 1996, 1997), and excimer lasers are sometimes used to initialize photoactivatable (“caged”) dyes, but not for the excitation itself (Guilkey et al. 1996; Hansen et al. 2000; Koochesfahani et al. 2000).
Ion lasers have the advantage of having superior beam quality and a continuous output that facilitates flow visualization. When operated in the TEM00 mode, ion lasers output a beam that is reasonably close to a Gaussian cross-section, and when operated in a closed-loop light-regulated mode, have a stable power output that simplifies calibration of the PLIF system. By comparison, Nd:YAG lasers have inferior beam quality, and the power and distribution of the beam can vary from pulse to pulse (Law and Wang 2000). The main advantage of Nd:YAG lasers is their high power output, typically on the order of 107 W during the pulse, as opposed to a continuous output of 10 W or less for an ion laser. Even though the pulse length of the Nd:YAG is only on the order of 10 ns, the energy per image exposure is typically much higher than that obtainable with an ion laser, since the exposure time in the latter case is limited by relevant timescales in the flow (Karasso and Mungal 1997).
Ironically, the high power of the Nd:YAG lasers can be problematic. If the laser excitation intensity is not small relative to the saturation intensity of the dye, the weak excitation assumption (Sect. 2.1) is violated, resulting in a non-linear relationship between F and I. This effect can be significant with pulsed lasers, since short pulse times can lead to exceptionally high intensities, even as compared to those produced by high-power CW lasers. A CW laser operating in the optimal TEM00 mode has a peak centerline intensity of 8P/πd2, where d is the beam diameter measured to the e−2 intensity contour. A typical light sheet formed by scanning a CW beam with a mirror has local peak intensities of order 107 W/m2 (e.g., Troy and Koseff 2005a), with intensities several orders of magnitude lower if a continuous sheet is formed by spreading the laser through a cylindrical lens. A typical light sheet formed with a pulsed Nd:YAG laser has intensities of order 1011 W/m2 (e.g., Karasso and Mungal 1996; Shan et al. 2004). Values of Isat have been estimated or inferred for both Rhodamine 6G (Shan et al. 2004) and Rhomdamine WT (Melton and Lipp 2003) to be of order 1010 W/m2, which is significantly above the peak intensity for typical ion lasers, but below that for pulsed lasers.
Nonetheless, accurate PLIF measurements can be made with excitation intensities above the weak excitation limit, so long as the system is optically thin (Melton and Lipp 2003; Shan et al. 2004). In this scenario, dye absorption does not produce variations in I, and the non-linear relationship between F and I becomes moot. Furthermore, linearity between F and C has been demonstrated to persist at high intensities (I > Isat) for fluorescein (Karasso and Mungal 1997), rhodamine WT (Melton and Lipp 2003), and rhodamine 6G (Shan et al. 2004), facilitating system calibration. An important caveat is that two studies (Karasso and Mungal 1997; Pan and Meng 2001) show seemingly anomalous behavior when fluorescein is used with Nd:YAG lasers. Both studies measured an initial increase in fluorescence along the direction of laser propagation in a uniform concentration of fluorescein, followed by the expected decay. Further studies are needed to determine if this is due to deviations from the Beer–Lambert law (determined by directly measuring the laser intensity attenuation) and/or due to fluorescence saturation effects.
3.2 Fluorescent dyes
Primary factors that govern the suitability of a particular dye include an absorption spectrum that is compatible with available laser excitation, a large separation between absorption and emission spectra, and high quantum efficiency to maximize signal strength (Arcoumanis et al. 1990). Other considerations include the degree of fluorescence sensitivity to temperature and pH (Smart and Laidlaw 1977; Walker 1987; Coppeta and Rogers 1998), susceptibility to photobleaching by the excitation source (Crimaldi 1997; Wang and Fiedler 2000a; Larsen and Crimaldi 2006), and fluorescence linearity with concentration (Karasso and Mungal 1997; Melton and Lipp 2003; Shan et al. 2004).
Properties of three common fluorescent dyes commonly used for aqueous PLIF
ε (cm M)−1
Percentage per °C
8.5E4b (488.0 nm)
1.1E5e (514.5 nm)
8.6E4a (514.5 nm)
Rhodamine 6G (a.k.a. Rhodamine 590) has peak absorption near 525 nm (enabling excitation with either the 514.5 nm line of an argon-ion laser or the 532 nm line from a Nd:YAG), and peak emission near 560 nm. The dye is highly resistant to photobleaching (Crimaldi 1997; Larsen and Crimaldi 2006). Temperature and pH dependence data for this dye are scarce.
Rhodamine B (a.k.a. Rhodamine 610) has a peak absorption near 555 nm, but the absorption spectrum is broad enough to permit excitation at either 514.5 or 532 nm. The fluorescence of Rhodamine B is sensitive to changes in temperature (Sakakibara et al. 1993; Lemoine et al. 1999; Unger and Muzzio 1999; Bruchhausen et al. 2005), but relatively insensitive to changes in pH. The temperature sensitivity can be exploited to use PLIF for temperature measurements, as reviewed later. Rhodamine B may have acute and chronic health effects in case of skin or eye contact, or inhalation or ingestion, and is considered to be by far the most toxic of the xanthene dyes (Smart and Laidlaw 1977). Rhodamine WT has similar spectral characteristics to Rhodamine B, has been used in a few PLIF experiments (e.g., Monismith et al. 1990; Melton and Lipp 2003; Wadley and Dawson 2005), and might be a safer alternative to Rhodamine B for many experiments.
Synthetic substitutes for common xanthene dyes have become available in recent years and have been occasionally used in aqueous PLIF experiments (e.g., Stohr et al. 2003). These water-soluble substitutes are brighter, less susceptible to photobleaching, and less pH-sensitive than the dyes they replace (Panchuk-Voloshina et al. 1999), but they are also more expensive. Current examples include the Alexa Fluor dyes from Molecular Probes (Invitrogen Corporation), Hilyte Fluor dyes from AnaSpec, and DyLight dyes from Pierce (Thermo Fischer Scientific).
3.3 Sheet optics
It should be noted that Eqs. 18–20 represent best-case focus scenarios that are often not realized in typical laboratory settings. For this reason, it is often desirable to directly measure the sheet thickness by imaging the focussed beam as it passes through the test section.
Traditional film cameras were used in the earliest PLIF experiments, with the resulting photographs used either in a qualitative sense (Dimotakis et al. 1983; Koochesfahani et al. 1985), or digitized for quantitative analysis (Shlien 1988). By the early 1990s, however, CCD digital cameras were used for PLIF (e.g., Prasad and Sreenivasan 1990; Koochesfahani and Mackinnon 1991), and their use has subsequently become the norm for acquiring fluorescence data. Since fluorescence occurs in a narrow wavelength band, color cameras are typically not used in favor of the higher performance available in grayscale cameras.
The choice of a digital camera for a particular PLIF application is typically a trade-off between maximizing pixel count, bit-depth, and framing rate. The pixel count influences spatial resolution, and ranges from as low as 256 × 256 (e.g., Van Vliet et al. 2004) to as high as 1,376 × 1,024 (e.g., Bruchhausen et al. 2005; Matsumoto et al. 2005). The bit-depth determines intensity resolution; a digital camera with a bit-depth N can resolve a maximum of 2N discrete grayscales. The majority of PLIF experiments use 8-bit cameras, but 10-bit (Diez et al. 2005) and 12-bit (e.g., Pan and Meng 2001; Matsumoto et al. 2005) cameras are used to capture more of the dynamic range of concentrations in a system. The framing rate sets the maximum rate at which images can be acquired (this rate may also be limited by the system used to store the images). For high-speed PLIF applications, framing rates as high as 955 frames per second have been used (Van Vliet et al. 2004). A final consideration is the spectral sensitivity of the camera. The sensitivity of the CCD chip at the wavelength of the fluorescence influences the required exposure time for a given image.
The use of a specialty flat-field lens is often warranted for PLIF imaging (e.g., Crimaldi and Koseff 2001). Flat-field lenses are designed to focus on planar surfaces, even with a small depth of field (large lens aperture). Most ordinary lenses have a spherical field characteristic, whereby the location of focussed objects is on a radial arc from the sensor. Since laser light sheets are flat, and limited fluorescence signal often dictates the use of large apertures, a flat-field lens can promote focal sharpness across the entire image.
A narrow-band optical filter is typically placed in front of the camera lens to allow only the fluorescence wavelengths to be imaged. Since many CCD sensors are sensitive to UV radiation, these filters often include blocking into the UV band.
4 Image processing
Raw PLIF images captured by the camera need to be post-processed for error correction and calibration. A robust form of image processing involves the use of a background image of a uniform, known concentration to implicitly determine the constants α(i, j) defined in Eq. 12. The background concentration is also present during the actual experiment. The description herein of this technique is an extension of processing algorithms used by Koochesfahani and Dimotakis (1985), Prasad and Sreenivasan (1990), Catrakis and Dimotakis (1996), Borg et al. (2001), Crimaldi and Koseff (2001), and others.
The requirement for Eq. 24 that In ≫ (Bn − D) can be in conflict with the desire to have Bn − D itself sufficiently large to avoid discretization and noise errors in the background image. This conflict is most easily resolved through the use of a camera with a large bit depth. For example, using a 12-bit camera (gray-scale values from 0 to 4,095) with typical pixel values of D = 50, Bn = 200, In = 2,000, and a(r, θ) = 0.9 the approximation error in Eq. 24 is less than 1%.
In Eq. 24, the dye concentration in the background image bn must be known a priori. This can be accomplished either with a fluorometric measurement, or by an explicit dose calculation. In most cases, the background concentration will be changing over time due to addition of additional dye during the experiment. In this case, multiple background images are usually used, and image interpolation in time can be used for intermediate images (Crimaldi and Koseff 2001). The calibration from pixel intensity to dimensional concentration can also be done with a calibration curve generated from multiple known concentrations mixed in the test apparatus (Karasso and Mungal 1996; Unger and Muzzio 1999).
Summary of error sources with corrections and/or mitigations
Fluorescence from background dye
Fluorescence sensitivity to pH and temperature
Fluorescence saturation (strong excitation)
Spatial variation in light sheet (optics, etc.)
Laser attenuation due to background dye
Laser attenuation due to instantaneous dye
Shot-to-shot laser power variation
Refraction through walls or interfaces
Pixel-to-pixel offsets (dark response)
Pixel-to-pixel gain variations
5.1 Scope of aqueous PLIF studies
LIF has been adapted for use with a wide range of flow types, with the principal requirement being that there is optical access to the measurement region for the laser sheet and fluorescence imaging. LIF studies have been done in open channels (Shiono and Feng 2003; Webster et al. 2003), pipes (Sakakibara et al. 1993; Pan and Meng 2001), microchannels (Matsumoto et al. 2005), stirred reactors (Houcine et al. 1996; Arratia and Muzzio 2004), rotating tanks (Horner-Devine 2006), and porous media (Rashidi et al. 1996; Stohr et al. 2003). The technique has been used to investigate scalar structure in boundary layers (Chen et al. 2007; Wagner et al. 2007), mixing layers (Koochesfahani et al. 1985; Koochesfahani and Mackinnon 1991; Karasso and Mungal 1996), stratified flows (Barrett and Van Atta 1991; Shy and Breidenthal 1991; Sakakibara et al. 1993; Nash et al. 1995; Atsavapranee and Gharib 1997; Daviero et al. 2001; Onishi and Komori 2006), internal waves (Troy and Koseff 2005a), gravity fronts (Parsons and Garcia 1998; Samothrakis and Cotel 2006), passive plumes (Crimaldi et al. 2002b; Webster et al. 2003), buoyant plumes (Johari 1992; Ai et al. 2006), jets (Dimotakis et al. 1983; Dahm and Dimotakis 1990; Bhat and Narasimha 1996; Catrakis and Dimotakis 1996; Webster et al. 2001; Westerweel et al. 2002), jets in cross-flows (Yoda and Fiedler 1996; Niederhaus et al. 1997; Davidson and Pun 1999), in vortices (Yu et al. 2007), and in biological flows (Monismith et al. 1990; Koehl et al. 2001; Crimaldi et al. 2002a; Mead et al. 2003).
The most general application of PLIF is for measurement of spatial and temporal scalar structure. PLIF images of instantaneous spatial structure can be obtained by ensuring that the image integration time is short compared to advective and straining timescales. Multiple images of instantaneous structure can be averaged to form images of concentration statistics (e.g., mean concentration, concentration variance).
5.2 Extensions of the technique
The basic PLIF technique has been extended to yield measurements beyond concentration statistics. When LIF is used simultaneously with a velocimetry technique, the scalar and velocity fluctuations can be correlated to calculate scalar fluxes (Papanicolaou and List 1988). To this end, PLIF has been paired with laser-Doppler velocimetry (LDV) (Hannoun and List 1988; Onishi and Komori 2006), particle image velocimetry (PIV) (Simoens and Ayrault 1994; Law and Wang 2000), particle tracking velocimetry (PTV) (Webster et al. 2001; Cowen et al. 2001; Chang and Cowen 2002), and molecular tagging velocimetry (MTV) (Koochesfahani et al. 2000). Because fluorescent dye moves passively within a flow, correlation techniques have been used to extract the velocity field directly from PLIF concentration images (e.g., Dahm et al. 1992; Tokumaru and Dimotakis 1995; Su and Dahm 1996).
The sensitivity of fluorescence to an independent scalar (typically temperature or pH) can be exploited to quantify the concentration of the independent scalar. In the simplest case, the entire flow has a uniform concentration of temperature-sensitive dye, but a heterogeneous temperature field. Using the temperature sensitivity of Rhodamine B (see Table 1), temperature statistics have been measured in thermally stratified pipes (Sakakibara et al. 1993), buoyant jets and plumes (Nash et al. 1995; Sakakibara et al. 1997; Lemoine et al. 1999), and convection-driven cavities (Coolen et al. 1999). In a more complicated approach (Coppeta and Rogers 1998; Sakakibara and Adrian 1999; Hishida and Sakakibara, 2000; Moghaddas et al. 2002), a second dye that is relatively insensitive to the independent scalar is also added to the flow, and is used to establish the local intensity of the excitation source (which has typically been modified by absorption from the two dyes). A hybrid version of these two approaches exploits the different temperature sensitivities of two spectral bands of a single dye to measure temperatures with a correction for local laser intensity (Bruchhausen et al. 2005). In an unrelated multi-dye PLIF technique, Stohr et al. (2003) studied the porous-media flow of two immiscible liquid phases using separate dyes to track each phase.
A relatively modern extension to the PLIF technique involves the use of “caged” dyes that are not fluorescent until they are permanently “uncaged” with a UV laser pulse. This permits small regions of the flow to be selectively rendered fluorescent and subsequently imaged using traditional PLIF with a second laser. The method has been used to track the evolution of small scalar features (Lempert et al. 1995), to measure velocities in a Poiseulle flow (Lempert et al. 1995) and to simultaneously measure concentrations and velocities in a turbulent shear layer (Koochesfahani et al. 2000).
The use of PLIF for non-invasive scalar measurements in aqueous flows has become widespread since its introduction over 25 years ago. Various refinements and correction procedures, combined with advances in digital imaging technology, have enabled the technique to evolve from a visualization tool to an accurate technique for quantifying scalar structure at high temporal and spatial resolution. PLIF has been employed in a wide range of experimental configurations, with the sole limitation being a requirement for optical access to the measurement region. Various extensions of the technique have been developed for measuring temperature, density, mixing rates, and scalar fluxes. PLIF is also easily extended for scalar measurements in three dimensions. Continuing advances in image acquisition, storage, and processing will likely result in volumetric laser-induced fluorescence (VLIF) replacing PLIF as the scalar measurement standard in aqueous flows.
The author would like to thank Jennifer Morin for extensive help in researching this article. This work was supported by the National Science Foundation under CAREER Grant No. 0348855.
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