Sensors and Actuators B 155 (2011) 430–435
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical
journal homepage: www.elsevier.com/locate/snb
A CMOS optical detection system for point-of-use luminescent oxygen sensing
Li Shen a , Michael Ratterman a , David Klotzkin b , Ian Papautsky a,∗
a
b
School of Electronics and Computing Systems, University of Cincinnati, United States
Department of Electrical Engineering, Binghamton University, United States
a r t i c l e
i n f o
Article history:
Received 27 July 2010
Received in revised form 1 December 2010
Accepted 3 January 2011
Available online 10 January 2011
Keywords:
Oxygen sensor
CMOS image sensor
Polarizerization signal isolation
a b s t r a c t
This work describes a stable and sensitive optical oxygen sensor based on a consumer CMOS image
sensor array and polarization signal isolation. The consumer CMOS image sensor is inherently color
discriminating, while the polarization is a wavelength-independent scheme for filtering excitation light.
Combination of these two components generates a compact, multi-color detection system applicable
to luminescence-based sensing. The optical system is applied to point-of-use oxygen sensing based on
quenching of platinum octaethylporphine (PtOEP) luminophore. Sensitivity of the demonstrated portable
oxygen sensor is comparable to that of benchtop spectroscopy-based systems. Taking advantage of the
spatial resolution of the CMOS image sensor, an oxygen insensitive reference can be integrated to improve
the reliability when powered by a battery. The low-cost and high sensitivity of the demonstrated optical
sensing approach make it promising for point-of-use applications.
© 2011 Elsevier B.V. All rights reserved.
1. Introduction
Current research in point-of-care (POC) biotechnology has
focused on increased miniaturization and integration for higher
throughput, decreased reagent cost, and increased sensitivity.
Most of the mainstream biological analyses are based on optical
methods (i.e., luminescence, absorption). These optical detection
systems typically require sophisticated instrumentation, such as
spectrophotometers or photomultiplier tubes, and trained personnel. The need for portable and low-cost optical sensing has
led to intense focus on miniaturization of sensor components.
Semiconductor and organic LEDs are gaining wide acceptance as
portable light sources in such systems [1], and have been used in
immunosensors [2,3] and chemical sensors [4,5]. Signal detection
and isolation, however, remain active areas of research.
Filtering of excitation light from signal light is critical in
microscale fluorescent systems. A common system design places an
excitation LED orthogonal to the interrogation region and detector
of the microfluidic system. This reduces system noise due to leakage
of unabsorbed excitation light; however, such systems are bulky.
The systems using a stacked arrangement, where the light source
is in-line with the interrogation region and detector, are much
more compact and preferable in portable systems. In such a system,
however, the emission signal is drowned out by the leaking excita-
∗ Corresponding author at: School of Electronics and Computing Systems, 814
Rhodes Hall, ML030, University of Cincinnati, Cincinnati, OH 45221, United States.
Tel.: +1 513 556 2347; fax: +1 513 556 7326.
E-mail address: [email protected] (I. Papautsky).
0925-4005/$ – see front matter © 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.snb.2011.01.001
tion light. A variety of techniques have been reported for filtering
in these stacked micro fluorescence systems, including interference filters [6], color filters [7], and dye-based filters [8]. These
approaches however are wavelength-specific, making the system
application-specific and far less versatile. In this work, signal isolation is achieved by cross-polarizing the excitation and emission
light; an approach we introduced recently [9,10]. Two perpendicularly placed polarizers, with extinction ratio of 28 dB, are able to
separate the emission light from the strong excitation light (Fig. 1a).
Compared with using filters, this approach is inexpensive, easy to
integrate, and is wavelength independent.
In addition to filtering, a sensitive and reliable detector is critical to developing a portable sensor. Conventional photomultiplier
tubes have been used for benchtop microfluidic systems [11,12].
Silicon photodiodes [13,14], or avalanche photodiodes [15] can be
used in POC or point-of-use systems. Integration of these external
components however presents alignment and assembly challenges.
In the past, we [9,10] and others [16,17] have used organic photodiodes (OPDs) as low-cost integrated detection alternatives, being
flexible and miniaturizable [18]. However, OPDs suffer from low
power conversion efficiency [19] and short lifetime [20,21].
Recently, CMOS image arrays have attracted interest as detectors for POC/point-of-use systems because of the high-speed
readout and low power consumption. El Gamal and Eltoukhy [22]
recently reviewed developments in CMOS image sensors and suggested applications to lab-on-a-chip as one of the future directions.
CMOS image sensors, commonly used today in digital cameras, are
built using the same process as ICs and consist of an array of photodetectors covered by a mosaic of microscale band-pass (Bayer)
filters (Fig. 1b). Raw data taken by a CMOS image sensor are grids of
L. Shen et al. / Sensors and Actuators B 155 (2011) 430–435
Fig. 1. (a) Illustration of polarization filtering which permits isolation of optical
signal (Rhodamine B emission centered at 625 nm) from high background signal
due to leaking excitation light (530 nm). (b) Schematic of a photodetector array
covered by Byer filters in a CMOS detector. (c) Arrangement of the light source (LED),
detector (CMOS), polarizers, oxygen sensitive PtOEP film and oxygen insensitive film
Rhodamine B in the portable oxygen sensor.
three primary colors: red, green and blue (RGB). Each pixel contains
the intensity information of one color. The intensity of each color is
described within a given range from a minimum and a maximum
which are dependent on the resolution of the analog to digital converter. This approach of using CMOS detector as detector has been
successfully applied for bioassays [23] and fluorescence-based cell
detection [24–27].
In this work we describe an optical sensing system based on
a low-cost consumer CMOS image sensor and explore the feasibility of using it as a detector in a portable oxygen sensor.
Oxygen detection is important in clinical diagnosis, biological
research and environmental monitoring. The conventional oxygen sensors based on Clark electrodes consume oxygen and are
easily poisoned by various organic compounds [28]. On the other
hand, optical oxygen sensors offer quick response time, no oxygen consumption, and high sensitivity [29]. The developed oxygen
sensor (illustrated in Fig. 1c) is based on oxygen sensitive metalloporphyrin luminophore platinum octaethylporphine (PtOEP) and
oxygen insensitive Rhodamine B (RhB). The CMOS image sensor
permits selective detection of the red emission from PtOEP and RhB
as well as simultaneous monitoring of their emissions. The oxygen
sensor exhibits high sensitivity and good stability.
2. Experimental methods
A CMOS image sensor with a USB interface (OmniVision,
OV9810) was used in this work. The sensor has a packaged footprint
of 8.195 mm × 7.535 mm, with 6.160 mm × 4.606 mm imaging area.
The active array size was 3488 × 2616 pixels (9 megapixel resolution), each approximately1.75 ␮m × 1.75 ␮m. The sensor was
placed at the bottom of the device stack as the detector and was
controlled by the supplied software. Captured raw images were
split to three grayscale images (each representing a separate RGB
color) and quantitatively analyzed using ImageJ (ver. 1.43u). Each
grayscale image yielded an average pixel intensity value.
In the spectral response test, the white LED was biased at a
constant potential of 3.0 V (∼16 mA forward current, based on
the manufacturer provided data sheet). Illumination light in the
430–680 nm range was selected by the monochromatorin 10 nm
increments. Intensities in each of the RGB channels of the CMOS
image sensor were recorded. Spectral response of each channel
431
was obtained when the recorded intensities were normalized to
the white LED emission spectrum.
The sensor is based on the oxygen-sensitive PtOEP encapsulated
in ethyl cellulose (EC). A green LED (Bivar R20GRN-F-0160) with a
central emission wavelength of ex = 520 nm was used as the excitation light source (Fig. 1c). The excitation light was linearly polarized
by passing through polarizer 1 (NT45667, Edmund Optics). The red
emission of the PtOEP film (em = 644 nm) passed through polarizer
2. The polarized excitation light not absorbed by the PtOEP film was
blocked by polarizer 2. When cross-polarized, the extinction ratio
of excitation light to leakage light is 28 dB [30]. The oxygen sensitive film was prepared by completely dissolving 10 mg of PtOEP
(PTO534, Frontier Scientific) in 10 mL tetrahydrofuran. The mixture
was added to a polymer solution prepared by dissolving 3 g EC (48%
ethoxyl) in the mixture of toluene (24 mL) and ethanol (6 mL).
For oxygen measurements, all automatic CMOS image sensor
functions, such as exposure time control, gamma correction, and
auto white balance (AWB), were set to manual. We used two flow
meters to control the ratio of oxygen and nitrogen supplied from
tanks. A mixing chamber was used to pre-mix the gases prior to
introduction to the gas testing chamber. Our sensor was located in
the center of the testing chamber; the chamber oxygen concentration was indicated by a commercial oxygen sensor (Nuvair, Pro O2
remote analyzer). During measurements, oxygen concentration in
the chamber was changed by adjusting input gas flow rates. Signals
and background were obtained by taking images of the PtOEP film
and a bare glass wafer. The values in the red channel were used
for oxygen measurement. By subtracting the background from the
signal, the emission intensity of PtOEP at different oxygen concentration was obtained. To test stability of the sensor performance
under an unstable light source, the forward voltage of the LED
was manually varied by ±0.02 V during oxygen measurements. The
emission intensities of the RhB reference were standardized and the
emission intensities of the PtOEP were calibrated accordingly.
3. Results and discussion
We first tested the spectral response of the CMOS chip RGB
channels to examine the color discriminating capability. We used a
monochrometer to select specific wavelengths of illumination light
and recorded the spectral response in the 430–680 nm range in
10 nm step increments. As illustrated in Fig. 2a, each channel of
the CMOS detector exhibits a strong response to the corresponding wavelength range, as expected. The blue pixels exhibit a peak
response at 460 ± 30 nm, while the green and red pixels peak at
540 ± 40 nm and 600 ± 50 nm respectively. This test confirms that
the CMOS detector we used is inherently discriminating to the RGB
colors and demonstrates the spectral response range of each color
pixel type. These results are helpful in the development of sensors
that take advantage of the CMOS detector’s color discriminating
capability.
While Bayer filters permit color discrimination in the CMOS
detector, response of each color pixel type does overlap. In a consumer camera this is desirable as the overlap permits capture of
colors that fall between the standard RGB bins, such as yellow
at 580 nm. In sensor applications, however, when individual color
channels in the CMOS detector are used to distinguish between
the excitation and emission of analyte, the spectral overlap leads
to noise. For example, a sensor based on detection of fluorescein isothiocyanate (FITC) – a fluorescent dye commonly used in
bioapplications – will detect emission signal in the green channel (521 nm) and unabsorbed excitation light (488 nm) in the blue
channel. The overlap between the two channels (Fig. 2a) will lead
to high background noise as a fraction of the excitation light will
be picked-up by the green channel.
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L. Shen et al. / Sensors and Actuators B 155 (2011) 430–435
Fig. 2. (a) Responsivity of the CMOS detector in each of its color channels. Inset images taken by the CMOS detector illustrate response at center wavelengths 460 nm, 540 nm
and 620 nm. (b) Response of the CMOS detector to 620 nm light as compared to a current measured by a silicon photodiode. The gamma correction function of the CMOS
detector distorts the linear response.
Fig. 3. The PtOEP absorption and emission spectra overlaid with the green LED
emission and the red channel response of the CMOS detector.
Optical signal isolation based on cross-polarization is a simple,
wavelength-independent approach that ideally complements the
CMOS detector. Cross-polarization offers a high extinction ratio,
on the order of 28 dB, and is able to separate weak emission light
from a strong background excitation in a stacked configuration
where the excitation light source and detector are positioned inline (Fig. 1c). The approach is wavelength independent, as the
high-efficiency linear polarizer films exhibit high-transmittance
of ∼40% at wavelengths above 400 nm. We recently used crosspolarization to demonstrate quantitative measurements down to
10 nM concentration of Rhodemine 6G fluorophore in a microflu-
idic lab-on-a-chip, a hundred-fold improvement from previously
published results [16,17]. Herein, the use of cross-polarization will
permit us to sensitively detect small changes in emission of PtOEP
due to quenching by oxygen in presence of the leaking excitation
light. However, before proceeding with discussion of the oxygen
sensor, we first describe further CMOS detector characterization
focused on integrated detector functions capable of influencing
sensor performance.
While CCDs offer better low-light performance, a CMOS image
sensor was selected for this work based on the overall sensor needs.
The two image sensor types were recently compared by Gamal
and Eltoukhy [22], who suggested that CMOS sensors are better
suited for low cost portable sensors. Most important to our application, since most camera control functions of a CCD are integrated
off-chip, the CCD-based detection systems tend to increase in size
and cost very rapidly. A CMOS array integrates sensing with A/D
converter and gain amplifier at the pixel level, making it highly
customizable [22]. Although these features make CMOS sensors
popular with the consumer market, their impact must be fully
understood for application to the light intensity-modulated optical sensing. Thus, in the next set of experiments we manually
controlled these functions (by writing the registers through the
standard serial camera control bus interface) to investigate capabilities of a consumer CMOS detector.
In photography, gamma correction is used to compensate nonlinear decoding process of displays by encoding the signal inversely.
The gamma correction is given by:
Iout = Iin
I in
Imax
(1)
Fig. 4. (a) Emission intensity of PtOEP as a function of oxygen concentration. (b) Stern–Volmer plot of the oxygen sensor. Inset images illustrate emission of PtOEP at low
and high oxygen concentrations.
L. Shen et al. / Sensors and Actuators B 155 (2011) 430–435
where Iout is the displayed intensity, Iin is the detected intensity, and
the exponent is the gamma correction index. The Imax is the upper
limit which depends on the color depth of the image sensor. The
OV9810 is a 24-bit color image sensor so its Imax is 255. The default
value of is 1/2.2 which makes the response of the CMOS detector non-linear to the light intensity [31]. Turning off the gamma
correction by setting = 1 leads to the CMOS detector exhibiting
perfect linearity satisfying a fundamental requirement as a detector. Fig. 2b illustrates the red channel response to monochromatic
620 nm light generated by biasing LED from 2.6 V to 2.88 V to yield
different intensities directly measured by a silicon photodiode. The
blue and green channels were tested in the same way and they
demonstrated good linearity as well. The effect of gamma correction is clearly evident. As these results indicate, gamma correction
must be turned off for the detector to yield a linear response over
the entire sensor range. However, gamma could provide additional
signal amplification for low-light conditions if sensor range is limited. The auto white balance (AWB) and auto exposure were tested
similarly. They were also manually controlled to keep the consistency during the following experiments.
Having examined the CMOS detector features, in the next set
of experiments we explored application to luminescent oxygen
sensing using PtOEP, which is known to be sensitive to oxygen.
The absorption and emission of PtOEP are centered at 535 nm and
640 nm when encapsulated in EC [32]. As Fig. 3 illustrates, there
is a significant overlap between the green LED emission (520 nm)
and the absorption of PtOEP. The red channel, which has strong
response to red light, was used to detect the PtOEP emission. The
response of red channel cuts off at around 580 nm, resulting in further filtering of the excitation light. Moreover, the green channel
responds to the LED emission well but does not respond to the
intensity variation of the red PtOEP emission. Thus, it is possible to
monitor the intensity of the light source using the green channel
and calibrate the measured result accordingly.
This oxygen sensor based on CMOS detector exhibited high
sensitivity as well as good linearity in the Stern–Volmer analysis. Fig. 4a illustrates the steady state emission intensities of
PtOEP sensor subject to different oxygen levels. The red pixel
values decrease significantly with the increasing oxygen concentration as the quenching effect becomes stronger. The intensities
in green and blue channels are much more stable because these
two channels are inert to the red emission of PtOEP which varies
with the oxygen concentration. The standard approach to characterizing luminescence quenching based oxygen sensors is using
Fig. 5. Response of the oxygen sensor exposed to an alternating streams of oxygen
and nitrogen gases. The arrows indicate the time when the gases were switched
(filled arrows indicate nitrogen; hollow arrows indicate oxygen).
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Stern–Volmer analysis in which,
I0
= 1 + KSV [O2 ]
I
(2)
where I0 and I are the emission intensities in the absence and presence of oxygen at concentration of [O2 ], respectively,and KSV is
Stern–Volmer constant. Fig. 4b illustrates a typical Stern–Volmer
plot of the developed oxygen sensor. The high correlation coefficient (0.9982) indicates a linear relationship between the oxygen
concentration and the ratio of emission intensities in the absence
(I0 ) and presence (I1 0 0 ) of oxygen. The ratio I0 /I1 0 0 as sensitivity of
the oxygen sensor is estimated to be ∼41. This result is comparable
to the ∼50 values reported by others using an external spectrophotometer [33,34] and is much higher than that of an integrated
lab-on-a-chip sensor (∼1.4) reported recently [35]. The insets in
Fig. 4b illustrate images taken at low and high oxygen concentrations. As emission of PtOEP is strongly quenched by oxygen, little
emission light is observed and the corresponding image was dark
(right inset). In low oxygen conditions, however, the emission of
PtOEP film increases and the image becomes red.
The oxygen sensor exhibited reversible quenching and good
repeatability when exposed to an alternating atmosphere of oxygen and nitrogen. A typical dynamic response of the sensor is
illustrated in Fig. 5. The response time of an optical oxygen sensor is considered as the time of 90% total intensity change when
switching between oxygen and nitrogen conditions. The response
time of the oxygen sensor in this work was ∼4 s upon switching from nitrogen to oxygen and the reverse switch time, from
oxygen to nitrogen, was ∼80 s. The asymmetric response curve
with a slow O2 to N2 response compared to N2 to O2 response
is typical of the luminescent thin film oxygen sensors [36]. The
response is comparable to the reported sensor using polystyrene
as luminophore-encapsulating matrix (18 s/60 s) [33]. We believe
the response time is limited by the mass-transport in our gas test
chamber (∼3 L volume), which can take 22–60 s to fill depending
on input gas flow rate (up to 8 l per min). Reducing the test chamber volume will improve sensor response time in the gas cycling
test. A number of methods may also be used to improve the film
response time, such as using Pt porphyrins bearing side groups
designed to increase solubility at higher concentration in a thinner layer [30] or use a material with high diffusivity to oxygen
[34].
The oxygen sensor showed excellent reliability after 30 h exposure to a green LED in ambient air (21% oxygen condition). Fig. 6
illustrates intensities of the RGB channels during the test. At 21%
O2 , emission of PtOEP was not strong but very stable during the
Fig. 6. Stability of the RGB channels in the CMOS detector of the oxygen sensor in
ambient air.
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L. Shen et al. / Sensors and Actuators B 155 (2011) 430–435
Fig. 7. (a) Emission of PtOEP is quenched by oxygen while emission of the reference Rhodamine B remains unchanged. Light emission in the red channel of CMOS
detector at (b) low oxygen and (c) high oxygen conditions. Dashed lines indicate
approximate boundaries of each film.
1800-min test. The signals fluctuated slightly initially but stabilized
during the first ten minutes. The fluctuation may be caused by the
LED or the power supply. This result suggests that a ten-minute
warm-up time is necessary for the system to reach a stable condition for accurate measurement. After the warm-up, the mean value
of the intensities in red channels is 16.5 with a standard deviation
of 0.33, resulting in a coefficient of variation of only 0.02. Based
on these results, the oxygen sensor is reliable and can be used for
continuous oxygen sensing applications.
The oxygen sensor exhibited high sensitivity when the light
source was powered by the stable external power supply. However,
such a power supply is not always available outside the laboratory
and batteries are used in most portable devices. While batteries are
much smaller in size and lighter in weight, their output decreases
over time with use or even due to storage. The lower driving voltage
causes lower light source emission; as a result, the PtOEP emission is a function of the oxygen concentration and the light source
intensity. Thus, an oxygen insensitive reference should be integrated to monitor the light source intensity. In the next experiment,
RhB was integrated as a reference.
The RhB emission does not change with oxygen concentration while the PtOEP emission is sensitive to oxygen. To
enhance RhB stability it was sealed in a glass capillary. Emission of both luminophores was recorded by taking advantage
of the CMOS sensor’s spatial capabilities. The intensity profiles
of two images taken at high and low oxygen conditions are
illustrated in Fig. 7. The PtOEP emission decreases significantly
from 190 to 20 a.u. as expected when the oxygen concentration
increases. On the other hand, the emission of RhB remains constant. The sensor images clearly illustrate the quenching effect
of oxygen on PtOEP. The black tape between the PtOEP and
RhB blocks the bleeding light from PtOEP at low oxygen con-
Fig. 8. PtOEP and RhB emission at different oxygen concentrations under fluctuating LED bias. (a) Uncompensated and (b) compensated. Triangles represent
RhB signal, while circles represent PtOEP intensity. Insets illustrate corresponding
Stern–Volmer plots.
centrations and thus enhances the stability of the RhB reference
signal.
The integrated reference makes the oxygen sensor stable and
accurate because any fluctuation of the power supply can be
observed from the emission intensity of RhB and then negated.
To demonstrate this, the LED bias was intentionally varied during oxygen measurement by ±0.02 V, which corresponds to less
than 1% change. The oxygen sensor was first characterized with LED
biased at 3.0 V using a Keithley 6487 voltage source. Fig. 8a illustrates the resulting RhB and PtOEP emission intensities that deviate
from the calibration curve (dotted lines). After the RhB intensities were used to compensate fluctuations in the PtOEP intensities,
the sensor exhibited good linearity in response (Fig. 8b). The inset
images in Fig. 8 illustrate the Stern–Volmer plots based on the calibrated PtOEP intensities. The coefficient of determination (R2 ) of
0.88 demonstrates the good linearity of the sensor. Without the
RhB reference, the R2 decreases to 0.54 under less than 1% of power
supply output fluctuation.
4. Conclusions
In summary, a portable optical oxygen sensor using a low-cost
CMOS image sensor as a detector and a cross-polarization scheme
as signal isolation was demonstrated. The sensor exhibited sensitivities comparable to that of macroscale benchtop sensor systems.
L. Shen et al. / Sensors and Actuators B 155 (2011) 430–435
The integrated oxygen insensitive reference was monitored simultaneously by the CMOS sensor, permitting compensation when
the light source is not stable. We are currently in process of
applying the system to multi-analyte sensing by taking advantage
of the detector’s inherent color discriminating capabilities. Overall, the described approach of using the wavelength-independent
polarizer scheme and color-recognizable CMOS image sensor clearly demonstrate suitability for reliable, on-site sensor
applications.
Acknowledgements
This work was supported by the NSF awards ECCS-0725812 and
ECCS-0930305.
References
[1] F.B. Myers, L.P. Lee, Innovations in optical microfluidic technologies for pointof-care diagnostics, Lab Chip 8 (2008) 2015–2031.
[2] B.C. Heinze, J.-Y. Song, C.-H. Lee, A. Najam, J.-Y. Yoon, Microfluidic immunosensor for rapid and sensitive detection of bovine viral diarrhea virus, Sens.
Actuators B 138 (2009) 491–496.
[3] D.B. Papkovsky, T.C. O’Riordan, G.G. Guilbault, An immunosensor based on the
glucose oxidase label and optical oxygen detection, Anal. Chem. 71 (1999)
1568–1573.
[4] R. Irawan, S.C. Tjin, X. Fang, C.Y. Fu, Integration of optical fiber light guide,
fluorescence detection system, and multichannel disposable microfluidic chip,
Biomed. Microdev. 9 (2007) 413–419.
[5] M. Hajj-Hassan, T. Gonzalez, E. Ghafar-Zadeh, H. Djeghelian, V. Chodavarapu, M. Andrews, D. Therriault, Direct-dispense polymeric
waveguides platform for optical chemical sensors, Sensors 8 (2008)
7636–7648.
[6] M.A. Burns, B.N. Johnson, S.N. Brahmasandra, K. Handique, J.R. Webster, M.
Krishnan, T.S. Sammarco, P.M. Man, D. Jones, D. Heldsinger, C.H. Mastrangelo,
D.T. Burke, An integrated nanoliter DNA analysis device, Science 282 (1998)
484–487.
[7] S.J. Hart, R.D. Jiji, A simple, low-cost, remote fiber-optic micro volume fluorescence flowcell for capillary flow-injection analysis, Anal. Bioanal. Chem. 374
(2002) 385–389.
[8] O. Hofmann, X. Wang, A. Cornwell, S. Beecher, A. Raja, D.D.C. Bradley, A.J.
DeMello, J.C. DeMello, Monolithically integrated dye-doped PDMS long-pass
filters for disposable on-chip fluorescence detection, Lab Chip 6 (2006)
981–987.
[9] A. Pais, A. Banerjee, D. Klotzkin, I. Papautsky, High-sensitivity, disposable labon-a-chip with thin-film organic electronics for fluorescence detection, Lab
Chip 8 (2008) 794–800.
[10] A Banerjee, A. Pais, I. Papautsky, D. Klotzkin, A polarization isolation method
for high-sensitivity, low-cost on-chip fluorescence detection for microfluidic
lab-on-a-chip, IEEE Sens. J. 8 (2008) 621–627.
[11] P. Hartmann, M.J.P. Leiner, M.E. Lippitsch, Luminescence quenching behavior
of an oxygen sensor based on a Ru(II) complex dissolved in polystyrene, Anal.
Chem. 67 (1995) 88–93.
[12] H. Chuang, M.A. Arnold, Radioluminescent light source for optical oxygen sensors, Anal. Chem. 69 (1997) 1899–1903.
[13] C. McDonagh, C. Kolle, A.K. McEvoy, D.L. Dowling, A.A. Cafolla, S.J. Cullen, B.D.
MacCraith, Phase fluorometric dissolved oxygen sensor, Sens. Actuators B 74
(2001) 124–130.
[14] A.N. Watkins, B.R. Wenner, J.D. Jordan, W. Xu, J.N. Demas, F.V. Bright, Portable,
low-cost, solid-state luminescence-based O2 sensor, Appl. Spectrosc. 52 (1998)
750–754.
[15] Y. Kostov, P. Harms, L. Randers-Eichhorn, G. Rao, Low-cost microbioreactor for
high-throughput bioprocessing, Biotechnol. Bioeng. 72 (2001) 346–352.
[16] O. Hofmann, P. Miller, P. Sullivan, T.S. Jones, J.C. Demello, D.D.C. Bradley, A.J.
Demello, Thin-film organic photodiodes as integrated detectors for microscale
chemiluminescence assays, Sens. Actuators B 106 (2005) 878–884.
[17] X. Wang, O. Hofmann, R. Das, E.M. Barrett, A.J. DeMello, J.C. DeMello, D.D.C.
Bradley, Integrated thin-film polymer/fullerene photodetectors for on-chip
microfluidic chemiluminescence detection, Lab Chip 7 (2007) 58–63.
435
[18] T.N. Ng, W.S. Wong, M.L. Chabinyc, S. Sambandan, R.A. Street, Flexible image
sensor array with bulk heterojunction organic photodiode, Appl. Phys. Lett. 92
(2008) 213303.
[19] P. Peumans, S.R. Forrest, Very-high-efficiency double-heterostructure copper
phthalocyanine/C60 photovoltaic cells, Appl. Phys. Lett. 79 (2001) 126–128.
[20] P. Vivo, J. Jukola, M. Ojala, V. Chukharev, H. Lemmetyinen, Influence of Alq3 /Au
cathode on stability and efficiency of a layered organic solar cell in air, Sol.
Energy Mater. Sol. Cells 92 (2008) 1416–1420.
[21] Q.L. Song, M.L. Wang, E.G. Obbard, X.Y. Sun, X.M. Ding, X.Y. Hou, C.M. Li, Degradation of small-molecule organic solar cells, Appl. Phys. Lett. 89 (2006) 251118.
[22] A. El Gamal, H. Eltoukhy, CMOS image sensors, IEEE Circuits Devices Mag. 21
(2005) 6–20.
[23] D.M. Vykoukal, G.P. Stone, P.R.C. Gascoyne, E.U. Alt, J. Vykoukal, Quantitative detection of bioassays with a low-cost image-sensor array for integrated
microsystems, Angew. Chem. Int. Ed. 48 (2009) 7649–7654.
[24] Y. Hosseini, K.V.I.S. Kaler, Integrated CMOS optical sensor for cell detection and
analysis, Sens. Actuators A 157 (2010) 1–8.
[25] X. Heng, D. Erickson, L.R. Baugh, Z. Yaqoob, P.W. Sternberg, D. Psaltis, C. Yang,
Optofluidic microscopy—a method for implementing a high resolution optical
microscope on a chip, Lab Chip 6 (2006) 1274–1276.
[26] G. Medoro, N. Manaresi, A. Leonardi, L. Altomare, M. Tartagni, R. Guerrieri, A labon-a-chip for cell detection and manipulation, IEEE Sens. J. 3 (2003) 317–325.
[27] J.M. Song, M. Culha, P.M. Kasili, G.D. Griffin, T. Vo-Dinh, A compact CMOS biochip
immunosensor towards the detection of a single bacteria, Biosens. Bioelectron.
20 (2005) 2203–2209.
[28] J.R. Bacon, Determination of oxygen concentrations by luminescence quenching of a polymer-immobilized transition-metal complex, Anal. Chem. 59 (1987)
2780–2785.
[29] P. Douglas, K. Eaton, Response characteristics of thin film oxygen sensors, Pt and
Pd octaethylporphyrins in polymer films, Sens. Actuators B 82 (2002) 200–208.
[30] D.B. Papkovsky, G.V. Ponomarev, W. Trettnak, P. O’Leary, Phosphorescent complexes of porphyrin ketones: optical properties and application to oxygen
sensing, Anal. Chem. 67 (1995) 4112–4117.
[31] G. Sharma, Digital Color Imaging Handbook, 2003.
[32] S.R. Ricketts, P. Douglas, A simple colorimetric luminescent oxygen sensor
using a green LED with Pt octaethylporphyrin in ethyl cellulose as the oxygenresponsive element, Sens. Actuators B 135 (2008) 46–51.
[33] S.-K. Lee, I. Okura, Porphyrin-doped sol–gel glass as a probe for oxygen sensing,
Anal. Chim. Acta 342 (1997) 181–188.
[34] T.-S. Yeh, C.-S. Chu, Y.-L. Lo, Highly sensitive optical fiber oxygen sensor using
Pt(II) complex embedded in sol–gel matrices, Sens. Actuators B 119 (2006)
701–707.
[35] E. Kraker, A. Haase, B. Lamprecht, G. Jakopic, C. Konrad, S. Köstler, Integrated
organic electronic based optochemical sensors using polarization filters, Appl.
Phys. Lett. 92 (2008) 033302.
[36] R. Herne, J. Brocas, E. Vander Donckt, The response time of optical sensors based
on luminescence quenching, Anal. Chim. Acta 364 (1998) 131–141.
Biographies
Li Shen received the BS and MS degrees in electrical engineering from Southeast
University, Nanjing, China. He is currently pursuing the PhD degree in electrical
engineering at the University of Cincinnati. His research interests include optical
gas sensors, lab-on-a-chip, and biosensors for point-of-care applications.
Michael Ratterman is currently pursuing a PhD at the University of Cincinnati, after
receiving his BS in electrical engineering in 2009. During that time, his senior project
development team won the “Best of EE” award at the Cincinnati Tech Expo. His
research interests include microfluidics, optical-gas sensing, embedded firmware
design, and image processing.
David Klotzkin is an Associate Professor in the Electrical and Computer Engineering
Department at Binghamton University. He received a PhD from the University of
Michigan in 1998. His current research interests include optical sensing and optical
communications.
Ian Papautsky is an Associate Professor in the School of Electronics and Computing Systems at the University of Cincinnati. He received a PhD in bioengineering
from the University of Utah, Salt Lake City, UT. His research interests focus
on developing disposable polymer microfluidic lab-on-a-chip (LOC) systems for
point-of-care (POC) applications and bio/chemical sensors for in situ sensing and
analysis.