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1
LED Induced Fluorescence using microscale visualization
methods
Jorge Arromba
Centre for Innovation, Technology and Policy Research (IN+), Department of Mechanical Engineering, Instituto
Superior Técnico, P1049001 Lisboa, Portugal
Abstract
A non-intrusive LED Induced Fluorescence Temperature measurement technique is tuned and applied using
microscale visualization techniques. Whole field temperature measurements in a volume-illuminated microfluidic
setup were performed with a good spatial and temporal resolutions, being applied to practical cases such as to a
training benchmark test, often imposed to CPU chips and to the thermal mixing of two fluid streams in a T-junction.
Two different techniques are addressed: Normalized Induced Fluorescence Temperature (N-LED-IFT) and Normalized
Ratiometric Induced Fluorescence Temperature (NR-LED-IFT), using one and two dyes, respectively. Parameters
influencing the results and the feasibility of these techniques at the microscale using a Leica illumination system LED
SFL100 530 𝑛𝑚 were also addressed. Rhodamine B and Rhodamine 110 are used as temperature sensitive and
insensitive dyes, respectively. The single-dye technique (N-LED-IFT) proved most advantageous, obtaining a
sensitivity of 1.68 %. ℃−1. The N-LED-IFT results present errors lower than 3.8 % in fluorescence intensity and lower
than 0.71 % in temperature measurements. The capability of this technique to be applied to low and high velocity
microscale flows using a LED illumination source was proved and 2D fluid temperature profiles where obtained with
high spatial (1.54 𝑚) and temporal (5 𝑚𝑠) resolutions.
Keywords: LED Induced Fluorescence Thermometry, LED illumination, Flow temperature measurement, Microfluidics,
2D fluid temperature profiles.
1. Introduction
Faster and smaller electronic parts are consistently being
developed at the same time the number of transistors
per chip is increasing and consequently the heat flux
dissipated, which can exceed 100 W.cm-2. In order to
remove such high heat rates, air cooling or single-phase
liquid cooling in plain channels in contact with the chip
are becoming insufficient [1]. The need to explore the
use of microchannel heat sinks to achieve high cooling
rates emerged, and Tuckerman & Pease in 1981 [2]
developed and tested the first VLSI (Very Large Scale
Integration systems) system. Fluid flow, transport and
heat transfer in microchannel heat sinks for both, single
and two-phase regimes represent one of the most
challenging aspects of experimentation in microfluids
due to very small temperature gradients associated with
the short heat dissipation timescales since heat transfer
rates are very high [3].
In line with this, temperature measurements in
microscale field of research gained some highlight and
preponderance due to the lack of knowledge and the
need to control small scale transport and heat transfer
phenomena in different areas of interest, such as
biochemistry [4] and electronics [5], [6]. Widely-used
methods for measurement of fluid temperature at
macroscale cannot be directly applied to the microscale.
Well known contacting measurement devices like high-
precision thermocouple probes are not the ideal
solution [7]. Besides being intrusive, these probes have
poor spatial and temporal resolution since most of them
have a characteristic size comparable to the cross
section of the microchannels. Embedded thermocouples
along the microchannel base [8] or inside its walls [9],
[10] have also been used, however, the spatial resolution
remains low.
Microfluidic devices fabricated with integrated
resistance temperature detectors (RTDs) are a viable
alternative, which allows surface temperature
2
monitoring and, although presenting a better spatial
resolution, do not provide information on the local fluid
temperature [11]. Infrared thermography can also be
used but is limited to its sole application in surfaces,
requiring an accurate value of the emissivity of the
medium [12], [13] and, thus, increasing its complexity.
On the other hand, thermochromic liquid crystals (TLCs)
[14] can be used in solution to measure fluid flow
temperature with a maximum spatial resolution of
approximately 1 m, while encapsulated TLCs can range
from 10 to 150 𝑚 [7] but limitations related with
temperature range still exist, from ~1 ℃ for narrow-
band TLCs and from 5 to 20 ℃ for wide-band TLCs [15].
Laser Induced Fluorescence Temperature (LIFT)
emerged, among other options, as a non-intrusive
method able to make whole-field temperature
measurements, first used by Omenetto et al. in 1972 [16]
to measure the temperature of reacting species or dyes
in flames, followed by and Chan & Daily in 1980 [17] in
the same research area.
In the early stages of the Laser Induced Fluorescence,
late 90’s, a temperature dependent dye was dissolved
within the flowing fluid of interest in order to apply the
technique and be able to perform temperature
measurements in macroscale [18]–[20].
A new two-color LIFT technique was then proposed by
Sakakibara & Adrian in 1999 [21] introducing a second
fluorescent dye, which, being temperature-insensitive,
can be used as reference to compensate for the
fluctuations at illumination. Performing the ratio of
fluorescence signal obtained from the temperature-
dependent dye at different spectral frequencies
represents an alternative, also called the single dye, two
color LIFT method, first applied by Bruchhausen et al. in
2004 [22] using a pulsed Nd:YAG laser.
The first temperature measurements via volume
illumination in microscale were reported by Ross et al. in
2001 [23] with a claimed accuracy of ±1.5 ℃, with spatial
and temporal resolutions of 1 𝜇𝑚 and 33 ms,
respectively. Natrajan and Christensen [3] highlighted, in
2008, the importance of the illumination intensity and
the need to illuminate over timescales much shorter
than those of the microscale thermal transport.
Therefore, they used a pulsed Nd:YAG laser applying the
two-color LIFT technique yielding uncertainties of
±0.55 ℃ and ±0.45 ℃ for dyes combination in ethanol
and water, respectively. Chamarty et al. in 2010 [7]
designed a setup to perform experiments using two
fluorescent dyes, with a single camera, capturing
sequential images using a filter wheel with two filters,
one for each dye. This procedure is only appropriate to
study steady flows as there is necessarily a time delay
between captured images, being found uncertainties of
±1.25 ℃ and of ±2.68 ℃ for traditional single-dye and
two-dye LIFT, respectively. Sakakibara & Adrian in 2004
[24] claimed an uncertainty of ±0.2 ℃ using the two-dye
LIFT.
Moreover, the standard light source of LIF used at
microscale is a continuous, usually Argon laser, which
does not provide sufficient illumination intensity over
the much shorter thermal transport at the microscale
and, therefore, does not allow obtain accurate
instantaneous measurements of temperature. Pulsed
lasers, such as the Nd:YAG laser, can provide higher peak
power than the continuous-wave lasers at the same time
that the short pulse time is useful for good temporal
resolution [3]. However, these lasers can be very
expensive.
More recently, laser diodes emitting in the ultraviolet
region of the spectrum provided compact solutions for
fluorescence emission from blue to near-infrared [25].
However, though compact, they can provide low output
power and are expensive. High-power LEDs emitting in
the ultraviolet became commercially available and,
though both LED and LDs are small in size, LEDs have
longer operating lifetimes, are stable, have reasonable
Nomenclature
𝐼 fluorescence intensity of the dye 𝐼𝑅ℎ𝐵 intensity of Rhodamine B dye at measurement
temperature
𝐼0 light incident flux 𝐼𝑅ℎ110 intensity of Rhodamine B dye at measurement
temperature
𝐶 dye concentration I0,RhB intensity of Rhodamine B dye at reference temperature
𝛷 quantum yield 𝐼0,𝑅ℎ110 intensity of Rhodamine 110 dye at reference
temperature
𝜀 absorption coefficient 𝐵 bias accuracy of the measurement device
βC collection efficiency 𝜎 standard deviation of the parameter measurements
𝑏 absorption path length
3
input power requirements and are of low cost and
accessible [26]. The use of LED, emitting in the visible
region, are then considered as a viable and more
affordable alternative light source.
In the present work, Rhodamine B and Rhodamine 110
are used as the temperature sensitive and insensitive
dye, respectively. The single-dye N-LED-IFT technique is
compared with the two-dye NR-LED-IFT technique for
microfluidic temperature measurement and tests to
different parameters influencing the technique are
performed. The method is then applied to a practical
example, often used for CPU chips, to evaluate
quantitatively the results from the technique and after
to some cases where the present technique can be
crucial for scientific enhancements such as turbulent
flow in microscale heat transfer experiments.
2. Experimental Setup
Fig. 1 – Schematics of the microchannel experimental
setup.
The experiments were conducted in an existing standard
𝜇𝑃𝐼𝑉 setup, shown in Fig. 1, which consists of an inverted
fluorescence microscope Leica DM IL LED and two high
speed cameras, the HighSpeedStar from LaVision and
the Phantom V4.2 from Vision Research, using Davis8
and Phantom Camera Control software for image
acquisition, respectively. A Leica LED SFL100 530 𝑛𝑚 was
used as the illumination source. Rhodamine B and
Rhodamine 110 fluorescent dyes dissolved in deionized
(DI) water were used in all experiments. Images were
captured with the help of a LED SFL100 530 𝑛𝑚 set of
filters for RhB and a Melles Griot laser filter 514.5 𝑛𝑚 for
Rh110.
A glass microchannel with square cross section (𝛬𝑖 =
318.107 𝜇𝑚, 𝛬0 = 631.614 𝜇𝑚) with a thin film of indium
oxide deposited on the outer wall as in Silvério et al. [27]
was used, which allows the heat input through Joule
effect at the same time it provides optical access to the
flow. A Gen 150-5 power supply from TDK-Lambda
(accuracy of ±0.05 V) regulated with GenesysControl
software was used for this purpose. Applying a known
voltage on the desired distance for heating, the heat flux
can be regulated. Despite adjustable, the distance
between electric contacts on the microchannel wall was
of 23.96 𝑚𝑚, kept constant throughout all experiments.
The wall and liquid temperatures are measured with
precision fine wire type K thermocouples (Omega
Engineering) with 25 𝜇𝑚 tip diameter placed in contact
with the solution and onto the microchannel wall. An 8-
channel isolated thermocouple DAQ module, DT9828,
from Data Translation® was used to convert
thermocouples signal to temperature through
Quick DAQ software.
3. LED-IFT measurements
The fluorescent intensity emitted per unit of volume,
𝐼 [𝑊. 𝑚−3] [21] is dependent on the light incident flux
𝐼0 [𝑊. 𝑚−2], the dye concentration 𝐶 [𝑘𝑔. 𝑚−3], the
quantum yield 𝛷 [−] (ratio of photons emitted and
absorbed by the molecule and depends on molecule
temperature) and the absorption coefficient 𝜀 [𝑚2/𝑘𝑔]
according to (1)
For low dye concentrations, Chamarty et al. [7] state (1)
becomes
where βC is Collection efficiency [−] and 𝑏 is the
absorption path length [−].
Since LED-IFT converts fluorescent intensity to
temperature, factors such as the optical setup, non-
uniform illumination, photo-bleaching, chemical
reactions and Auto-absorption and reemission effects
due to Beer-Lambert law, among others, can modify dye
fluorescence response or even destroy dye molecules
and must be taken into account.
By performing the ratio of the dyes fluorescence
intensities the technique becomes needless of extra
calibrations for different setups and independent of
background illumination, as can be seen in Eq. (3)
𝐼𝑅ℎ𝐵
𝐼𝑅ℎ110
=𝐶𝑅ℎ𝐵Φ𝑅ℎ𝐵𝜀𝑅ℎ𝐵
𝐶𝑅ℎ110Φ𝑅ℎ110𝜀𝑅ℎ110
(3)
Two methods to evaluate normalized images are the
Normalized image for Ratiometric LED Induced
𝐼 = 𝐼0𝐶Φ𝜀 (1)
𝐼 = βCΦ𝐼0𝜀𝑏𝐶 (2)
4
Fluorescence Temperature (NR-LED-IFT), in which both
dyes, RhB and Rh110, are used, and the Normalized
image for LED Induced Fluorescence Temperature (N-
LED-IFT), where only RhB is used.
NR-LED-IFT method is based on Eq. (4), requiring the
processing of four images in order to obtain a single
value of temperature, which turns out to be a heavy
method with high computational costs.
Looking closely, if the intensity ratio of both dyes at
ambient temperature, I0,A/I0,B, is known (which is a
constant), the previous expression can be simplified,
requiring only the acquisition of two simultaneous
images (α and β).
On the other hand, being Rh110 the dye that is
approximately temperature independent, it is expected
that the ratio IRh110/I0,Rh110 is close to the unit. Hence,
simplifying the previous expression, it yields
However, there are some constraints related with this
method, such as the fact that it is only valid if both
images used are identical and if there are no changes in
the optical path length during the experiment, which
means it is invalid for two-phase flows.
Test experiments were performed in a fully developed
region of an aqueous flow inside a microchannel with a
constant heat flux at the wall aiming at optimizing the
performance of the technique.
Fig. 2 – Fluorescence intensities of the dyes for different
Rhodamine B concentrations.
Seven different concentrations of Rhodamine B were
prepared in order to infer about dye concentration
influence in the fluorescent signal retrieved. The results
are depicted in Fig. 2 and show the expected decrease
of the fluorescence intensity as the dye concentration
decreases and temperature increases.
The 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 [%. ℃−1] of the technique is given by the
gradient of the fluorescence intensity 𝑑𝐼 𝑑𝑇⁄ and can be
written as a function of image intensity, 𝐼0, as
𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 =1
𝐼0
(𝑑𝐼
𝑑𝑇) × 100 (6)
As Rhodamine B concentration increases, the
fluorescence signal also increases and with it the
temperature sensitivity. Fig. 3 shows that the sensitivity
increases almost linearly from 0.83 to a maximum of
1.68 %. ℃−1 as dye concentration increases from 1.4 to
25 mg.L-1, after which it starts to decrease. Thus, RhB
solution with a concentration of 25 𝑚𝑔. 𝐿−1 was chosen
for all the subsequent experiments. A concentration of
15 𝑚𝑔. 𝐿−1 was chosen for Rhodamine 110 and a
sensitivity of 0.011% was found
Fig. 3 – Influence of solution concentration in fluorescence
signal sensitivity.
Two set of experiments were performed to quantify
background influence: the first consists in comparing
images collected with and without room illumination
(Fig. 4); the second consists in subtracting an image
obtained with the LED illumination source turned off to
the images collected with both, room and the LED
illuminations on (Fig. 5). The last one will not be used
with the Phantom camera since its acquisition software
always requires a current session reference.
0 5 10 15 20 25 30 350.0
0.5
1.0
1.5
2.0
Sensitiv
ity [%
.ºC
-1]
Concentration [mg.L-1]
INR−LED−IFT =IRhB/IRh110
I0,RhB/I0,Rh110
(4)
IN−LED−IFT =IRhB
I0,RhB
(5)
5
Fig. 4 – Fluorescent signal from both dyes, with and without
room illumination.
From Fig. 4, fluorescent signal show no significant
dependence of the room illumination and, therefore, of
the background light. The results of the second set of
experiments are summarized in Fig. 5 and show that
subtracting the image obtained with the LED
illumination source turned off only offsets the original
curve, and do not add any improvement
Fig. 5 – Rhodamine B fluorescent signal with and without
background image removal.
The influence of the auto-absorption and reemission
was also addressed, performing experiments with each
dye separately and the corresponding fluorescence
signals were simultaneously captured with both
cameras, being the results summarized in Fig. 6. It shows
the fluorescence signal emitted by both Rh110 and RhB
aqueous solutions obtained at the same temperature
conditions and captured with the HSS camera. At
ambient temperature, the signal obtained from Rh110 is
about 50 times smaller than that from RhB particles. This
difference, however, decreases for higher solution
temperatures, reaching a 4 times ratio around 67ºC . The
presence of Rh110 dye particles in the solution has no
significant impact in the signal retrieved from the RhB
dye particles at ambient temperature but turns out more
important as temperature increases, even for a single
degree increment, where a reduction from 50 to only a
10 times ratio between the signals is observed, leading
to a decrease in temperature sensitivity in fluorescence
response obtained in the HSS camera.
Fig. 6 – Fluorescent signal on HSS image for both
particles.
Calibration experiments require precision for
temperature control and measure, so a specific setup
was needed. As shown in Fig. 7, it consists on a thermally
insulated reservoir on top of a microscope slide (76 ×
26 𝑚𝑚2 × 1 ± 0.05 𝑚𝑚 thick) with a deposited indium
oxide layer on the slide bottom in order to vary the
temperature of the dye solution by Joule effect the same
time it allows optical access from the bottom.
Fig. 7 – Schematics of the thermally insulated pool.
The temperature was monitored using two precision fine
wire type K thermocouples (25 𝜇𝑚 tip diameter) placed
in the solution, on the focal plane to assure the
temperature measured corresponds to the temperature
of the dye solution emitting fluorescence information.
20 30 40 50 60 70 80 900
200
400
600
800
1000
1200
1400
1600
Inte
nsity [A
.U.]
Temperature [°C]
RhB with room illumination
Rh110 with room illumination
RhB without room illumination
Rh110 without room illumination
20 30 40 50 60 70 80 900
200
400
600
800
1000
1200
1400
1600
Inte
nsity [A
.U.]
Temperature [°C]
RhB
Rh110
Pool
Glass
slide
InOx thin film
6
To compare both normalization methods presented
above, an experiment is performed in which they are
applied.
Fig. 8 – LED-IFT techniques comparison: NR-LED-IFT in solid
squares and N-LED-IFT in hollow triangles.
The normalized curve (inverse of the calibration curve,
which shows solution Temperature as a function of
Normalized Intensity) applying the NR-LED-IFT
technique, is obtained and represented in solid squares
on Fig. 8. On the same figure is also represented the N-
LED-IFT curve, which is the fluorescence intensity
emitted by the RhB (hollow triangles). The difference
between the curves of both techniques is rather small
(1.2% maximum deviation between curves), being NR-
LED-IFT computationally more demanding since it
involves operations with four different images,
increasing the numerical error of the results (round-off
errors). Therefore, N-LED-IFT was selected to perform all
subsequent experiments.
Fig. 9 – RhB fluorescence signal collected in the Pool
Calibration system.
Fig. 9 shows the fluorescence signal obtained with the
intensity (green) and temperature (red) error bars,
determined according to Eq. (7). For the temperature
acquisition, the bias of the acquisition board was 0.09 ℃,
0.1 ℃ noise for thermocouples, claimed by the
manufacturer, and the highest standard deviation
verified across all measurements was 0.1 % of the
temperature measured. As for the intensity information,
the standard deviation for each set of 50 images was
determined. The error obtained for intensity
measurements is of 1.5 % for solution at ambient
temperature and increases up to 3.8 % for 92 ℃, as for
temperature the error goes from 0.19 to 0.23 ℃, with
temperature increasing from 27 ℃ to 92 ℃,
corresponding to a maximum relative error of 0.71% for
the lower temperature.
Fig. 10 – Calibration curve for the N-LED-IFT technique with a
4th order best fit polynomial.
The calibration curve is obtained by inverting the
normalized curve as presented in Fig. 10. Table 1 presents
the coefficients for the fourth order polynomial that best
fits the results with a correlation factor near the unit. The
regression was made so a continuous range of
temperatures for a continuous range of normalized
intensities is obtained.
Table 1. Calibration polynomial specifications.
Value Standard Error
Intercept 149.526 3.287
B1 -381.139 28.378
B2 603.428 85.000
B3 -533.382 105.588
B4 189.611 46.311
Model Polynomial
Adj. R-Square 0.999
A training benchmark, a type of test usually applied to
computer chips to track CPU utilization and
performance, is applied to the microchannel flow. Here,
the experiment consisted in applying different voltages
to the indium oxide layer deposited in the microchannel
20 30 40 50 60 70 80 900.0
0.2
0.4
0.6
0.8
1.0
1.2
Norm
aliz
ed Inte
nsity [ -
]
Temperature [°C]
NR-LED-IFT
N-LED-LIFT
30 40 50 60 70 80 90200
400
600
800
1000
1200
Inte
nsity [A
.U.]
Temperature [°C]
Experimental data
Temperature error
Intensity error
0.0 0.2 0.4 0.6 0.8 1.0 1.2
20
40
60
80
100
Tem
pera
ture
[°C
]
Normalized Intensity [ - ]
Calibration Experimental Data
Polynomial Fit
7
outer wall and measuring the fluorescence response,
which is compared with a simplified theoretical model.
This simplified model consists in an energy balance to
the system and takes into account convection and
radiation losses to the environment, not including the
thermal inertia terms. Thus, it provides a rough
estimation of the steady-state mean fluid temperature
at different microchannel sections, allowing only a
comparison of the order of magnitude of the results
obtained from the fluorescence technique and those
from this model.
Fig. 11 –Different sections in the microchannel setup.
Fig. 11 shows the different sections of the tube,
important for the analysis performed. Here, position v
represents the place where visualization occurred.
Thermocouples were placed at the wall in positions 1
and 2.
Fig. 12 – Comparison between the temperature estimated
inside the channel and the temperature obtained through the
N-LED-IFT technique.
Fig. 12 presents depicts the value of the fluid
temperature measured by the fluorescence technique in
purple, 𝑇𝑣, plotted together with the time varying wall
temperature measured in section 2, located downstream
from the visualization section and the electrical power
output from the power source, in black. The results show
that the fluid temperature measured with the N-LED-IFT
technique behaviour is in accordance with that of the
wall temperature measured by the thermocouple, also in
agreement with the power variations.
In the heating section, around 43 seconds in the
experiment, it was observed temperature sensitivities of
30.8 %. 𝑠−1 and of 21.9 %. 𝑠−1 for the fluid and
microchannel wall temperatures. There is also noticed a
time delay between the increase in temperature of the
fluid and of the microchannel wall, around 0.42 𝑠, which
is in agreement with the time that the fluid takes to go
from visualization section to section 2
4. Mixing plane visualization at a T junction
One of the biggest advantages of using the LED-IFT
technique is the possibility to obtain 2D fluid
temperature profiles, difficult to obtain through
traditional temperature measurement techniques as
thermocouples. The suitability of N-LED-IFT method for
temperature measurements in microchannel
applications is tested through quantitative visualization
of the temperature field in a mixing plane obtained by
driving a hot and a cold fluid stream together in a T-
shaped micro mixer.
The experimental setup for this experiments,
schematically displayed in Fig. 13, consists of a glass slit,
with three silicon tubes connecting to the exterior. One
inlet port for the cold fluid, pumped by a NE-300 Just
Infusion, a second inlet port for the hot fluid controlled
in a secondary flow loop, pumped by a Harvard 22
syringe pump and one outlet port to allow the flow to
exit the slit.
Fig. 13 – T-shaped micro-mixer scheme.
Hot fluid secondary flow loop consists in a custom made,
thermally isolated, acrylic reservoir where two
immersion resistances (1000 𝑊, model AI 03, 230 𝑉,
50 𝐻𝑧) controlled by an EGO Original 55.13022.060
thermostat (temperature range 30 – 110 ℃) heat water
that will then flow through silicon tubes encircling the
primary flow loop.
In Fig. 14 the mixing plane for three different volumetric
flows is depicted. A lighter (hotter) fluid jet is observed
0 100 200 300 400
20
40
60
80
Tv T
2 P
Output
Tem
pera
ture
[°C
]
Time [s]
0
1
2
Pow
er
(W)
8
to flow across the main cold flow stream. Despite small
temperature differences between the two fluid streams,
contact zones between them are well defined. By varying
the volumetric flow rate from 𝑄𝑐𝑜𝑙𝑑 = 200 𝑚𝑙. ℎ−1 and
𝑄ℎ𝑜𝑡 = 200 𝑚𝑙. ℎ−1 (Fig. 14 (a)), to 𝑄𝑐𝑜𝑙𝑑 = 300 𝑚𝑙. ℎ−1
and 𝑄ℎ𝑜𝑡 = 300 𝑚𝑙. ℎ−1 (Fig. 14 (b)) is evident the
movement from the mixing of both flows to a region
further away from the hot fluid inlet, with a higher curve
angle when 𝑄𝑐𝑜𝑙𝑑 = 500 𝑚𝑙. ℎ−1 𝑄ℎ𝑜𝑡 = 50 𝑚𝑙. ℎ−1
(Fig. 14 (c)).
(a)
(b)
(c)
Fig. 14 – Mixing plane of two laminar stream flows with
different velocities: (a) 𝑄𝑐𝑜𝑙𝑑 = 200 𝑚𝑙. ℎ−1, 𝑄ℎ𝑜𝑡 =
200 𝑚𝑙. ℎ−1; (b) 𝑄𝑐𝑜𝑙𝑑 = 300 𝑚𝑙. ℎ−1, 𝑄ℎ𝑜𝑡 = 300 𝑚𝑙. ℎ−1; (c)
𝑄𝑐𝑜𝑙𝑑 = 500 𝑚𝑙. ℎ−1, 𝑄ℎ𝑜𝑡 = 50 𝑚𝑙. ℎ−1. Cold fluid coming from
left to right and hot fluid inlet is on the top.
Increasing the volumetric flow rate, the Reynolds
number increases, which after some point is reflected in
flow properties modifications and the results are shown
in Fig. 15. Images were captured for 𝑄𝑐𝑜𝑙𝑑 =
1000 𝑚𝑙. ℎ−1 and 𝑄ℎ𝑜𝑡 = 1000 𝑚𝑙. ℎ−1 with a 5 𝑚𝑠
difference between each image. It can be noticed that
the small spatial resolutions obtained with this
temperature measurement technique is able to retrieve
detailed temperature information in the resulting
vortexes, and capture the evolution of heat transfer
phenomena in flows with this characteristics in such
short timescales.
(a)
(b)
(c)
Fig. 15 – Mixing plane of two turbulent stream flows for the
same volumetric flow, 𝑄𝑐𝑜𝑙𝑑 = 1000 𝑚𝑙. ℎ−1 and 𝑄ℎ𝑜𝑡 =
1000 𝑚𝑙. ℎ−1. Consecutive images captured with a 200 𝐻𝑧
acquisition rate. Cold fluid coming from the left to the right
and hot fluid inlet on the top
5. Uncertainty analysis
The error expression adopted for this work followed
ASME standards [28] and is described below. Considers
both the accuracy and the precision of the
measurements performed.
𝐸𝑟𝑟𝑜𝑟 = ±√𝐵2 + 2 × 𝜎2 (7)
9
where 𝐵 is the Bias (accuracy) of the measurement
device, 𝜎 is the standard deviation of the parameter
measurements, corresponding to the precision of
measurements, and the constant 2 is a commonly used
constant to represent a 95% confidence interval with 4
degrees of freedom
6. Conclusions
In this study two LED-IFT techniques were described,
developed and applied to microscale flows in a
microchannel and in a T-shaped junction using a LED
SFL100 530 𝑛𝑚 as illumination source.
Rhodamine B and Rhodamine 110 were used as
temperature sensitive and temperature insensitive dyes,
respectively. Several parameters impacting the
technique implementation were addressed and a
comparison between N-LED-IFT and NR-LED-IFT was
performed. Results indicated no straight advantage in
using an extra dye, requiring more computer
time/memory capability and adding computational
errors in the process, so N-LED-IFT was chosen to
proceed with experiments.
Temperatures measured with N-LED-IFT showed
agreement with flow temperature predicted through a
simplified theoretical model, presenting higher
deviations for increasing or decreasing heat flux steps
and a very good agreement with wall temperature
measured with the thermocouple. The wall temperature
was found slightly higher than the flow temperature
since the joule heating was applied to the microchannel
wall and heat transfer by conduction prevails facing heat
transfer by convection and the thermal inertia of the
fluid. Divergences between the results from the
fluorescence technique and those from the theory can
be associated with the setup thermal inertia and with the
simplifications applied to the model. The capability of
this technique to be applied to low and high velocity
microscale flows using a LED illumination source was
demonstrated. 2D fluid temperature profiles where
obtained with high spatial (1.54m) and temporal (5 𝑚𝑠)
resolutions. LED illumination being more stable, less
expensive and energy consuming, and at the same time
allowing a wider range of wavelengths to appropriately
match the maximum wavelength for the fluorescence of
the dye, presents an alternative to lasers in fluorescence
based techniques.
Precision and accuracy are directly related with the
equipment used for image acquisition and temperature
measurement for the calibration curve. A thorough
calibration process was performed and found crucial to
obtain quality results. The results presented showed
errors lower than 3.8 % in fluorescence intensity and
lower than 0.71 % in temperature measurements. Call of
attention upon the fact that reference temperatures for
the calibration and for the measurements normalization
images must be the same.
Although LED-IFT related errors can be reduced by
averaging results over larger areas consequently
reducing the effect of possible noise present in data
acquired, for non-stationary conditions, averaging over
large areas will lead to information loss as seen after
some preliminary processing, All results presented in
this study are therefore obtained from single-pixel
information.
In order to validate the results from any LED-IFT
technique, a more realistic model of fluid temperature is
needed to compare temperature information. Also,
studies involving heat transfer in microscale turbulent
flows with 2D temperature visualization can provide
better understanding to such complex phenomena.
Aknowledgements
Financial support through project PTDC/EME-
MFE/109933/2009 from Fundação para a Ciência e a
Tecnologia, FCT, is gratefully acknowledged. Laboratory
facilities were built in the framework of project
RECI/EMS-SIS/0147/2012 and therefore also
acknowledged.
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