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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