Design and Evolution of an Opto-electronic Device for VOCs

Detection

Ana Carolina Pádua

, Susana Palma

, Jonas Gruber

, Hugo Gamboa

and Ana Cecília Roque

UCIBIO, REQUIMTE, Departamento de Química, Faculdade de Ciências e Tecnologia da

Universidade NOVA de Lisboa, 2829-516 Caparica, Portugal

Departamento de Química Fundamental, Instituto de Química da Universidade de São Paulo,

Av. Prof. Lineu Prestes, 748 CEP 05508-000, São Paulo, SP, Brasil

Laboratório de Instrumentação Engenharia Biomédica e Física da Radiação (LIBPhys-UNL),

Departamento de Física, Faculdade de Ciências e Tecnologia da Universidade NOVA de Lisboa,

Monte da Caparica, 2829-516 Caparica, Portugal

Keywords: Device, Electronic-nose, Gas Sensing, Volatile Organic Compounds.

Abstract: Electronic noses (E-noses) are devices capable of detecting and identifying Volatile Organic Compounds

(VOCs) in a simple and fast method. In this work, we present the development process of an opto-electronic

device based on sensing films that have unique stimuli-responsive properties, altering their optical and

electrical properties, when interacting with VOCs. This interaction results in optical and electrical signals that

can be collected, and further processed and analysed. Two versions of the device were designed and

assembled. E-nose V1 is an optical device, and E-nose V2 is a hybrid opto-electronic device. Both E-noses

architectures include a delivery system, a detection chamber, and a transduction system. After the validation

of the E-nose V1 prototype, the E-nose V2 was implemented, resulting in an easy-to-handle, miniaturized and

stable device. Results from E-nose V2 indicated optical signals reproducibility, and the possibility of coupling

the electrical signals to the optical response for VOCs sensing.

1 INTRODUCTION

The interest in odours detection is common in several

areas, namely in food quality, environmental

protection, and medical diagnosis. Volatile organic

compounds (VOCs) can be regarded as indicators of

food spoilage, presence of hazardous gases in the air,

and even certain diseases when found in some

biological samples.

Electronic noses (E-noses) can be used to detect

and identify VOCs in a fast and automated manner.

Since their invention (Wilkens and Hartman, 1964),

many were developed and optimized for diverse

applications (Zohora et al., 2016). During the 80s, E-

noses were defined as instruments which included an

array of heterogeneous electrochemical gas sensors

with partial specificity and a pattern recognition

system (Persaud and Dodd, 1982; Llobet et al., 1999).

However, this definition has been broadening along

the time. In the last years, the term E-nose has been

used to mention gas sensors that alter their properties,

in consequence of changes in a gaseous atmosphere.

Generally, the E-noses architecture is similar to

the human olfactory system (Gutierrez and Horrillo,

2014). They comprise of a delivery system that

transfers the air to be analysed from the headspace of

a sample chamber to a detection chamber, like the air

circulating in the nasal cavities; Inside the detection

chamber, an array of heterogeneous gas sensors with

partial specificity and selectivity mimics the odorant

receptors, and their interaction with the VOCs; and a

signal processing unit with pattern recognition

methods have the same function that the olfactory

bulb and the brain have in odours recognition.

Currently, there are some commercial products

based on E-nose technology, suitable for a wide range

of applications. For instance, The eNose company is

mainly focused on applications for medical research,

namely for differentiating head and neck carcinoma

from lung carcinoma (van Hooren et al., 2016), and

for diagnosis of bacterial and viral infections in

obstructive pulmonary disease (van Geffen, Bruins

and Kerstjens, 2016). Breathtec Biomedical, Inc. is

interested in early screening of diseases such

Pádua, A., Palma, S., Gruber, J., Gamboa, H. and Roque, A.

Design and Evolution of an Opto-electronic Device for VOCs Detection.

DOI: 10.5220/0006558100480055

In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 1: BIODEVICES, pages 48-55

ISBN: 978-989-758-277-6

as cancer, tuberculosis, and diabetes. Peres offers a

product to evaluate food quality. Sensigent, Sacmi,

and AIRSENSE Analytics developed very versatile E-

noses for environmental protection, security

screening and quality control that benefit from the use

of customizable sensor modules, and pattern

recognition methods based on machine learning

algorithms. Nano Mobile Healthcare is developing a

technology from NASA, not only for aerospace safety,

but also for medical diagnosis and road security. And,

CSIRO is creating a biosensor with numerous

possible applications.

The sizes of commercial E-noses range from

desktop, to laptop or hand size. The sensing materials

also vary, being the most common metal oxides

(Barsan, Koziej and Weimar, 2007; Mirzaei,

Leonardi and Neri, 2016), and polymers (Li, 2009).

Other arrays based on metals (Gutmacher et al.,

2011), nanoporous pigments/dyes (Feng et al., 2010),

nanostructures (Jing Kong et al., 2000) and liquid

crystals (Boden et al., 1999) have also been used for

gas sensing.

2 SENSING MATERIALS

Our research group has developed a new class of

sensing gels for gas sensing. These materials possess

enormous versatility and have unique stimuli-

responsive properties, altering their optical and

electrical properties when interacting with VOCs

(Hussain et al., 2017). The sensing gels are composed

of liquid crystal (LC) droplets self-assembled in the

presence of ionic liquid, dispersed inside a

biopolymer matrix.

The way the sensing gels alter their optical

properties relies on the way light propagates through

nematic liquid crystals, which typically produce a 90-

degree shift in light polarisation. Hence, having the

sensing films sandwiched between two crossed

polarising filters, it is possible to observe changes in

light polarisation, when in the presence or absence of

VOCs.

Light-emitting diodes (LEDs) are sources of

unpolarised light. When the emitted light passes

through the first polariser, only light polarised along

the y-axis can pass. Next, the light passes through the

second polariser (called the analyser), which only

allows light polarised along the x-axis to pass.

Therefore, the light that pass through the analyser is

minimal, since there is negligible light polarised

along the x-axis emerging from the polariser.

However, if a glass slide with the sensing gel

spread on it (which has nematic LC in its

composition) is placed between the polariser and the

analyser, the anisotropy of the nematic LC, produces

a shift in the light polarised along the y-axis (that

comes from the first polariser). This way, part of that

light becomes polarised along the x-axis. Therefore,

the light can pass though the analyser, and be detected

by the light-dependent-resistor (LDR) - Figure 1 (a).

In the presence of VOCs, the LCs change their

configuration from radial to isotropic. Thus, the light

polarised along the y-axis, even passing through the

gel, maintains the polarisation, and so is blocked by

the analyser - Figure 1 (b). Hence, minimal light

intensity reaches the LDR.

Figure 1: (a) The light emitted by the LED achieves the

LDR when no VOCs are interacting with the sensing gel;

(b) and is blocked when VOCs are interacting with the

sensing gel.

Regarding the electrical effects, the sensing gels

exhibit high conductivity in the absence of VOCs. On

the contrary, when interacting with VOCs their

conductivity decreases (Hussain et al., 2017).

To explore the application of these gels for gas

sensing, our research group is developing an

electronic nose (E-nose). If the interaction dynamics

of distinct VOCs with the sensing gels vary, different

Design and Evolution of an Opto-electronic Device for VOCs Detection

optical and electrical signals will be obtained. This

brings the possibility of VOCs detection and

identification in a simple and rapid manner. The final

goal is to achieve an accurate, miniaturized and

scalable device that could run the analysis

automatically.

3 DESIGN AND ASSEMBLY OF

DEVICE VERSIONS

The first prototype of E-nose, called the E-nose V0,

is shown in Figure 2 (a). The apparatus is composed

of a detection chamber, a delivery system, and a

transduction system.

Figure 2: (a) Schematic of E-nose V0 and (b) detection

chamber.

The delivery system includes the air pumps

(exposure and recovery pumps), the sample chamber,

tubes and connectors, and two non-return valves to

prevent back-flow. The Exposure pump is responsible

for carrying the VOCs from the sample chamber

(where is the chemical solution) to the detection

chamber. Therefore, it is ON in the exposure periods

and OFF in the recovery periods. The recovery

system is composed of two air pumps which clean the

detection chamber, making the atmospheric air

circulate through the chamber, and removing the

VOCs. Some tubes were longer than necessary, which

resulted in higher exposure and recovery times

required for the experiments. Moreover, the area of

the liquid-gas surface inside the sample chamber was

changing for different volumes of solvent, due to its

tapered configuration.

The detection chamber – Figure 2 (b) - is the E-

nose component where the VOCs interact with the

sensing materials. It contains an array of four optical

sensors able to detect those interactions. For each

optical sensor, the unpolarised light emitted by the

LED pass through a sensing film sandwiched between

two crossed polarising filters (polariser and analyser),

and finally reaches the photo detector. Photo resistors,

photo diodes or photo transistors could have been

used as photo detectors. Our choice was the use of

light dependent resistors (whose resistance decrease

with increasing incident light) because they are the

most commonly used photo detectors, and could be

used in a very simple circuit (based on voltage

dividers). Moreover, LDRs are cheap, readily

available in many sizes and shapes, and need low

power and voltage for operation. Regarding the

electronic components, since the LEDs and LDRs

have some variations inherent to their own

production, signals calibration is an important issue.

Additionally, interference between optical sensors

was observed in the signals response, because the

LDRs of the optical pairs were not only receiving

light from the LED in front, but also from the LEDs

in the surroundings. Variations in the sensing films’

exposed areas to light also resulted in unstable

responses, given that the sensing gels were not

homogeneously spread over all the parts of the glass

slides. The first prototype also suffered difficulties to

handle and it had air leaks in the tube connectors.

The transduction system was based on a National

Instruments board, which acquired the data generated

by the LDRs. The collected signals were sent to a

computer and could be visualized in a LabVIEW

interface. Additionally, the exposure and recovery

times were defined as LabVIEW inputs. The board

used a 5 V to trigger the relay switch unit, which in

turn determined the exposure and recovery pump

states. In some situations, the noise was too high,

inhibiting the observation of the sensor response.

Besides, the hardware and software used were both

expensive. We concluded that the construction of a

new cheaper and controllable transduction system

could help solving these problems.

3.1 Optical E-nose V1

The schematic of the optical E-nose V1, which

resulted from improvements made in E-nose V0, is

represented in Figure 3.

BIODEVICES 2018 - 11th International Conference on Biomedical Electronics and Devices

Figure 3: Schematic of E-nose V1.

A new detection chamber, easier to handle, was

assembled for E-nose V1. Inside it, the interference

between optical sensors was minimized.

Opaque mask’s layers – Figure 4 (a) - were

implemented to prevent the interference of dispersed

light from neighbour LEDs with each LDR response.

Given that the sensing gels on the glass slides were

not homogeneously spread, opaque black masks –

Figure 4 (b) - were applied on the back of the glass

slides. This delimitates the area of gel exposed.

Figure 4: (a) Opaque masks layers implemented to prevent

the interference of dispersed light from the LEDs in the

surroundings with the LDRs response. (b) Sensing film

with an opaque mask applied.

A new hermetic sample chamber with a

cylindrical configuration was implemented. This

way, the area of the liquid-gas surface is the same,

independently of the volume used. In the pipelines,

shorter silicone tubes and polypropylene connectors

were used. Having shorter tubes, lower recovery and

exposure periods were required.

The transduction system previously implemented

in E-nose V0 was not scalable, because the data

acquisition system was expensive, and required cable

connection to a computer. Thus, for E-nose V1, the

transduction system was redesigned. The new system

uses an Arduino Uno (a microcontroller) and a

Raspberry Pi 2 Model B (an embedded system), that

can be remotely controlled by a computer. Since the

transduction system was implemented using open-

source hardware and software, it became two orders

of magnitude cheaper than the previous version.

Currently, it is an autonomous unit, the mechanisms

for data visualization and data analysis are faster, and

a scalable architecture was achieved.

3.2 Hybrid E-nose V2

The new E-nose implemented should fulfill some

requirements: it should be stable, miniaturized, and

easy to handle. Moreover, it should enable less time

needed for experiments, and to test more sensing

films simultaneously. Having these goals in mind, the

E-nose V2 was designed according to the schematic

shown in Figure 5. This E-nose is hybrid, since the

optical detection chamber can be easily replaced by

an electrical sensors chamber.

Figure 5: Schematic of the E-nose V2.

The delivery system is composed of an exposure

and a recovery pumps. It has also a sample chamber,

tubes, connectors, and non-return valves similar to the

ones used in E-nose V1.

The transduction system is a replica of the E-nose

V1, based on Arduino Due and Raspberry Pi 2 Model

B. Arduino Due was used, because it has twelve

analog input pins, whereas Arduino Uno has only six.

A humidity and temperature sensor was included

in the E-nose instrumentation to measure the room

conditions. And, the relays switch unit was wired to

the microcontroller and pumps.

3.2.1 Optical Detection Chamber

The optical detection chamber is composed of: an

opaque external box - Figure 5 A) - that protects the

optical sensors from the interference of

environmental light; an internal support for sensing

films with a glass chamber on it to concentrate the

VOCs near the sensing films - Figure 5 B); Printed

Circuit Boards (PCBs) - Figure 5 C) - for the emission

Design and Evolution of an Opto-electronic Device for VOCs Detection

circuit – Figure 6 (a) - and for the detection circuit

Figure 6 (b).

Figure 6: Schematic of the (a) emission circuit and (b)

detection circuit of E-nose V2 PCBs.

Inside the E-nose V2 detection chamber, six

LEDs/LDRs were placed in parallel, instead of four

used in E-nose V1. Another difference is that the

LDRs power supply is 3.3 V, because an analog input

value higher than 3.3 V may damage the Arduino

Due. The components used in the PCBs are through-

hole technology mounting type.

3.2.2 Electrical Detection Chamber

For testing the sensing films electrical response, the

detection chamber should be replaced by the

electrical sensors chamber. This consists of a little

box with capacity for an array of 8 interdigitated

electrodes inside. The sensing films exhibit capacitive

effects. To avoid accumulation of charges in the

electrical films, they can be continuously polarised

and depolarised, using alternating current (AC).

The method used to detect the changes that occur

in the electrical sensors while interacting with the

VOCs requires the use of a conductivity meter

installed between the Arduino and the detection

chamber. The conductivity meter implemented is

described in (da Rocha et al., 1997). An oscillator

generates a triangular wave, that is applied to one of

the electrode terminals. The other terminal is wired to

the input of a current-to-voltage converter. After

rectification and filtering, the output voltage becomes

proportional to the conductance in the electrode.

4 RESULTS

4.1 Signals Calibration

The optical sensors were calibrated for each

LED/LDR pair, according to the following equation:

Calibrated signal =

𝑠 − min

max − 𝑚𝑖𝑛

(1)

s – signal values obtained (V). The value is given by

the LDR, when a sensing film is sandwiched between

two crossed polarising filters, in the absence - Figure

1 (a) - or presence of VOCs - Figure 1 (b).

min – average of signal values obtained when two

crossed polarising filters are placed between the LED

and the LDR. Without placing the sensing gel in the

middle, the light intensity that reaches the LDR is

minimal. Therefore, given the LDR response curve,

its resistance will be maximum. Consequently,

according to the Ohm’s law, the voltage drop at the

LDR will be maximum. Yet, taking in account the

LDR schematic shown in Figure 6 (b), the analog

output signal 𝑉

𝑜𝑢𝑡

(detected by the Arduino) is given

by:

𝑉

𝑜𝑢𝑡

= 𝑉

𝑅

= 𝑉

𝑆𝑜𝑢𝑟𝑐𝑒

− 𝑉

𝐿𝐷𝑅

(2)

Thus, if the voltage drop at the LDR is maximum, the

output voltage will be minimum.

max – average of signal values obtained when two

parallel polarising filters are placed between the LED

and the LDR (without sensing gel in the middle). The

light intensity that reaches the LDR is maximum.

Therefore, its resistance will be minimum.

Consequently, the voltage drop will be minimum.

According to equation 2, if the voltage drop at the

LDR is minimum, the output voltage will be

maximum.

The calibration signals, from which the min and

max are calculated, are obtained without placing any

sensing film between the two polarising filters. The

experiments are performed inside the detection

chamber, with the LEDs ON. Each E-nose (V1 or

optical V2) only needs a single calibration, before the

first experiment, and not in the beginning of each

experiment. Each E-nose unit requires its own

calibration, and cannot use calibration values from

other E-noses, because the rationale behind

calibration is to compensate differences among LEDs

and LDRs inherent to their production.

4.2 Optical Signals Evolution

Examples of optical signals obtained in E-nose V0,

V1 and V2 are shown in Figure 7. A significative

BIODEVICES 2018 - 11th International Conference on Biomedical Electronics and Devices

improvement in the signal to noise ratio can be

observed from E-nose V0, to E-noses V1 and V2.

From E-nose V1 to E-nose V2, the exposure and

recovery times were reduced for 1/10. This was

possible due to the miniaturized detection chamber

implemented in E-nose V2. The total chamber

volume was reduced from 1200 mL (in V1) to 20 mL

(in V2). Consequently, the E-nose V2 allows

acquisition of more data in less time.

4.3 Signals Obtained

To evaluate if the E-nose V1 could detect vapors of

different organic solvents, several optical sensing

films were prepared. 60 µL of sensing gel were spread

over microscope glass slides cut with dimensions 40

mm x 15 mm.

3 tests were conducted in the E-nose V1, using the

conditions: 5 mL of organic solvent inside the sample

chamber, heated at 36 °C. The room temperature was

set to 20 °C. The room humidity ranged from 46 % to

87 %. The exposure time was 50 s, and the recovery

time was 150 s. The total duration was 15 min. And,

the sampling rate was 10 Hz.

Test 1, 2 and 3 included 13 experiments, each one

using different organic solvents, namely acetone,

carbon tetrachloride, chloroform, dichloromethane,

diethyl ether, isopropanol, ethanol, ethyl acetate,

heptane, hexane, methanol, toluene and xylene. The

results obtained for acetone, carbon tetrachloride,

hexane, and methanol are shown in Figure 8.

Figure 7: Evolution of optical signals from (a) E-nose V0

to (b) E-nose V1 and (c) E-nose V2. The gas sample used

was atmospheric air saturated in acetone for all the plots.

Figure 8: Optical signals obtained using the same sensing film exposed to different VOCs in test 1, test 2 and test 3, using E-

nose V1. The sensing films were composed of 1-butyl-3-methylimidazolium dicyanamide [BMIM] [DCA], 4-Cyano-4'-

pentylbiphenyl (5CB), Bovine Skin Gelatine (BSG), Sorbitol, and Milli-Q water (Hussain et al., 2017).

Design and Evolution of an Opto-electronic Device for VOCs Detection

Figure 9: (a) Optical signals obtained using the same sensing film cyclically exposed to acetone along 10 days. The sensing

films were composed of [BMIM] [DCA], 5CB, BSG, and Milli-Q water (Hussain et al., 2017). (b) Electrical signals obtained

using the same sensing film for different VOCs exposure. The electrical films were composed of [BMIM] [DCA], 5CB, BSG,

Sorbitol, and Milli-Q water (Hussain et al., 2017).

One can observe that for the same test (test 1, 2 or

3) the interaction of the sensing gels with different

VOCs originates signals with different features. This

is an indicator that the device might be useful for

VOCs distinction and identification.

However, observing the signals for each VOC, we

can identify significant differences comparing the

results from test 1, test 2 and test 3. Thus, we can

conclude that the results were not reproducible for

different tests. Possible reasons for lack of

reproducibility can be: the sensing films spreading

method was not adequate; the device was not stable

enough, because it was difficult to place the sensing

films at the same position for different tests; and the

LDRs PCB had to be taken out and placed again for

different tests, due to E-nose V1 horizontal

configuration.

To solve these issues, the E-nose V2 was

assembled, and a reproducibility test was conducted.

An array of six sensing films with the same

composition was placed inside the detection chamber,

and kept at the same position for 10 days.

The experimental conditions were: 5 mL of

acetone inside the sample chamber, at 36 °C. The

room temperature was 21-23 °C. The room humidity

ranged from 58 % to 89 %. The exposure time was 5

s, and the recovery time was 15 s. The total duration

was 50 min. And, the sampling rate was 5 Hz.

Two of the six sensing films tested originated

reproducible responses along the 10 days. Figure 9 (a)

shows a reproducible response given by one of them.

To test the electrical response, interdigitated

electrodes 0.2 mm were prepared, spreading 15 µL of

the sensing gel over each one. The sensing gel

composition tested that gave an electrical response for

several VOCs – see Figure 9 (b) - is described in the

caption of this Figure. The conditions used in the

experiment were: 5 mL of the organic solvent inside

the sample chamber, at 37 °C. The exposure time was

10 s, and the recovery time was 50 s. The total

duration was 4 min.

5 CONCLUSIONS

Regarding the device evolution, the E-nose V2 is

more stable, miniaturized, and controllable than E-

nose V1. The detection chamber of E-nose V2 was

miniaturized, and consequently the exposure and

recovery times required for VOCs detection were

reduced. It is easier to handle, because it has a vertical

configuration, while E-nose V1 has a horizontal one.

Thus, in E-nose V2, the sensing films can be easily

placed and removed. Also, the chamber is more stable

because the sensing films are placed in fixed

positions. Nevertheless, more improvements are

needed to get close to a commercial product: a

hermetic detection chamber should be implemented;

and, the LED and photo detector of each optical pair

should be perfectly aligned. This can be achieved

using PCBs with surface-mount technology

components. For future versions, photo diodes or

photo transistors should be tested to substitute the

LDRs, because they might have better performance-

to-cost ratio, sensitivity and stability for this

application. Besides, their response speed is faster.

The humidity and temperature sensors installed in

E-nose V2 might add valuable information about the

influence of the room conditions in the sensing films

response. We intend to study that correlation in detail

soon. For the transduction system, the signals

BIODEVICES 2018 - 11th International Conference on Biomedical Electronics and Devices

response must be normalized, and several

classification methods can be explored.

Furthermore, small, lightweight and low-power

pumps can be used in future versions of the device, so

it can achieve portability without the need of an

electric generator.

In what concerns to the electrical part, the

conductivity meter architecture should be re-designed

to be simpler and easily scalable. For instance, the

possibility of generating an input digital wave should

be explored. In addition, the electrodes finishing

surface should be more corrosion-resistant (the use of

nickel and gold, or platinum might be a solution). The

duration of the experiments related to the electrical

signals should be longer, allowing the study of the

response at different measurement intervals, to

improve quantification and interpretation of results.

The studies performed so far intend to

characterize the device, identify its limitations, and

optimize the technology. That is why, the tests were

performed successively in cycles during several

minutes. Nevertheless, our vision is to achieve a

device that gives a response in the range of seconds.

The final goal is to accomplish a portable and

user-friendly device. Accuracy, stability, and

scalability are imperative to get to an E-nose, that can

be explored towards several applications in

environmental protection, security, product quality,

or medical research.

ACKNOWLEDGMENTS

This work was supported by the European Research

Council (SCENT-ERC-2014-STG-639123) and

UCIBIO, financed by FCT/MEC (UID/Multi/

04378/2013) and co-financed by the ERDF under the

PT2020 Partnership Agreement (POCI-01-0145-

FEDER-007728). The authors thank FCT/MEC for

the research fellowship PD/BD/105752/2014 for A.P.

The authors also acknowledge funding from CNPq,

Brazil (400740/2014-1).

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Design and Evolution of an Opto-electronic Device for VOCs Detection