Fabrication of low cost chemical and electrochemical
sensors aiming to apply for food and forensic detection
Thiago R.L.C da Paixão
Institute of Chemistry – University of São Paulo, São Paulo SP - Brazil 05508-000
Electronic Tongue and Chemical Sensor Lab
*[email protected]
Summary
-
From development of electrochemical sensor to development of
electronic tongues
-
What is an electronic tongue?
-
Electronic tongue for the basic taste model
-
Electronic tongues for the discrimination of forensic, clinical and
food samples
-
Colorimetric approach and Electronic tongues
-
Final consideration
A summary of milestones in sensor development
A summary of milestones in sensor development
-
Historically development of potentiometric sensors always aims to improve selectivity
of the analytical method or sensor
-
However, only a few potentiometric sensors can really be called selective
-
Samples with complex matrices versus simples matrices
RT
zi / z j
E=E +
ln[ai + ∑ K ij (a j )
]
zi F
j
0
Nikolsky-Eisenman Equation
Electronic Nose
Electronic Tongue and Nose
Set of electrochemical sensors to crudely mimic the mammalian nose and tongue.
These sensors work as their human analogues, providing a global signal, a
fingerprinting, to characterize and recognize certain sample
Coffee
Coffea Arabica
Coffea Canephora
Electronic Tongue and Nose
Set of electrochemical sensors to crudely mimic the mammalian nose and tongue.
These sensors work as their human analogues, providing a global signal, a
fingerprinting, to characterize and recognize certain sample
Coffee
Coffea Arabica
Coffea Canephora
Electronic Tongue and Nose
Set of electrochemical sensors to crudely mimic the mammalian nose and tongue.
These sensors work as their human analogues, providing a global signal, a
fingerprinting, to characterize and recognize certain sample
Coffee
Coffea Arabica
Coffea Canephora
Coffee
Coffea Arabica
Coffea Canephora
Electronic Tongue
“The electronic tongue is an analytical instrument
comprising an array of nonspecific, low-selective,
chemical sensors with high stability and cross-sensitivity
to different species in solution, and an appropriate
method of PARC and/or multivariate calibration for data
processing”
Principal Component Analysis (PCA)
SIMCA (Soft independent modeling of class analogy)
Partial Least-Square(PLS)
Artificial Neural Networks (ANN) ….
Y. Vlasov, A. Legin, A. Rudnitskaya, C. Natali, A. D.
Amico, Pure Appl. Chem, 77 (2005) 1965.
Non-supervised pattern recognition - PCA
There are statistical tools that reduce a large number of independent variables to a
smaller set of variables.
The Principal Component Analysis is a statistical technique that linearly transforms an
original set of variables into a smaller set of variables, which represents most of the
information of the original data.
Thus, a smaller set of data is easier to analyze than a large set of data.
Other advantage is the possibility to analyze the data graphically.
How it works??? – PCA (A simple example)
Petal lenght
Petal width
Flower Types
Petal
Sepal
How it works??? – PCA (A simple example)
Petal Width / cm
1.6
1.2
versicolor
0.8
0.4
setosa
0.0
1
2
3
4
Petal Lenght / cm
5
How it works??? – PCA (A simple example)
PC1 = 0.70711PL – 0.70711PW
PC2 = 0.70711PL + 0.70711PW
PC2
PC1
Petal Width / cm
1.6
1.2
y
versicolor
0.8
x
0.4
setosa
0.0
1
2
3
4
Petal Lenght / cm
5
How it works??? – PCA (A simple example)
-1.0
-0.5
0.0
0.5
Principal Component 2
0.4
1.0
Petal Width
0.5
0.2
0.0
0.0
-0.2
-0.5
Petal Length
-0.4
Sample
PC1 PC2 ….
-2
Virginic
.
.
x
y
0
2
Principal Component 1
(1.03 %)
(98.97 %)
How it works??? – PCA (A simple example)
Petal lenght
Petal width
Flower Types
Petal
Sepal
How it works??? – PCA (A simple example)
Virginic
0.6
PC2 (1.86 %)
0.4
Setosa
Versicolor
0.2
0.0
-0.2
-0.4
-0.6
-2
-1
0
PC1 (98.14 %)
1
Sepal width
Petal lenght
Petal width
How it works??? – PCA (A simple example)
Sepal lenght
How it works??? – PCA (A simple example)
Versicolor
3
Setosa
2
PC2 (22.85 %)
Virginic
1
0
-1
-2
-3
-4
-3
-2
-1
0
PC1 (72.96 %)
1
2
3
Electronic Tongue / PCA
Samples
Signal for different sensors or different current values for a cyclic voltammetric
Electronic Tongues
1) Array of sensors made of lipid membranes dispersed in PVC matrix using
potentiometric measurements;
2) Array of sensors modified with plasticizers and PVC doped with metalloporphyrins
using potentiometric measurements;
3) Array of sensors made of metallic sensors and/or modified surfaces using
voltammetric/amperometric measurements;
4) Array of sensors using conducted polymers using conductance measurements at AC
currents.
F. Winquist, Microchim. Acta, 163 (2008) 3.
P. Ciosek, W. Wroblewski, Analyst, 132 (2007) 963.
Overview of the development of electronic tongues
120
Articles
80
60
Keyword: “electronic tongue”
40
20
0
1980
1985
1990
1995
2000
2005
2010
2015
200
Year
Patents
Published Patents
Published Articles
100
150
100
50
Food
0
1980
1985
1990
1995
Year
2000
2005
2010
2015
Devices developed in the laboratory
a) Integrated Au sensor
b) Integrated Cu sensor
L. Angnes, E.M. Richter, M.A. Augelli, G.H. Kume, Anal. Chem., 72 (2000) 5503.
D. Daniel, I.G.R. Gutz, Electrochem. Commun., 5 (2003) 782.
Adhesive label paper
Devices developed in the laboratory
c) Integrated Au sensor (with 2 working electrodes)
Devices developed in the laboratory (Paper devices)
Particularly advantageous for resource limited settings, school
laboratories and developing countries.
W. R. de Araujo and T. R. L. C. Paixão, Analyst, 2014, 139, 2742-2747
Devices developed in the laboratory (Paper devices)
http://www.rsc.org/chemistryworld/2
014/03/office-paper-electrochemicalanalytical-device-sensor
http://blogs.rsc.org/an/2014/04/
28/hot-articles-in-analyst-38/
W. R. de Araujo and T. R. L. C. Paixão, Analyst, 2014, 139, 2742-2747
Data treatment (Principal Component Analysis)
Obtenção do conjunto de dados
Eletrodo
de ouro
Gold Electrode
Current
Corrente
Valores
de corrente
Current values
of the
do
eletrodo
de
ouro
Gold Electrode
Chemometrical Analysis
Análise quimiométrica
l1
Current
Corrente
Potencial
Potential
.
.
.
.
.
.
Sample
Amostra 21
PC2
ln
Potencial
Potential
Eletrodo
de ouro modified
Gold Electrode
modificado com
Withda
Prussian
Azul
PrússiaBlue
Current
values
of the
Valores
de corrente
Gold
Electrode
modified
do eletrodo de
ouro
modificado
With
Prussian Bluecom
Amostra 1
Sample 2
Azul da Prússia
l = I representa
umacurrent
linha,
Line
represents the
cada linha representa uma
values
amostrafor each sample
Principal component analysis (PCA) was performed in Statistica 12.0 (StatSoft Inc., USA).
The analysis was carried out using voltammetric current values without any previously
preprocessing and scaling from one or two working electrodes as input.
PC1
Characterization of the disposable devices
Supporting Electrolite
0.5 mol L-1 KCl (a, b)
0.1 mol L-1 KCl (c)
0.5 mol L-1 NaNO3 (d)
c
2
Ag/AgCl(sat) (a)
Ag ink (b, c, d)
d
0
I / µA
v = 50 mV s-1
1 mmol L-1 K3Fe(CN)6
b
-2
-4
-0.2
a
Au Electrode
0.0
0.2
E / V vs Ag/AgCl or Ag
0.4
0.6
Characterization of the disposable devices
Supporting Electrolite
+ Analyte
1 mol L-1 NaOH + 2 % Ethanol (v/v)
Cu electrode
400
I / µA
200
Auxiliar and reference
electrodes, respectively:
Pt and Ag/AgCl (sat) (−)
Cu and Ag/AgCl (sat) (−)
Cu and Ag ink (−)
0
-200
-0.8
-0.4
0.0
0.4
E / V vs Ag/AgCl or Ag
0.8
v = 50 mV s-1
Characterization of the disposable devices (Paper devices)
Characterization of the disposable devices (Paper devices)
Detection of Explosives
Characterization of the disposable devices (Paper devices)
Detection of chloride
(Environmental and
Clinical Analysis)
Paper device (Airborne Explosive Detection)
0
A
0
B
-600
-200
2500
I / µA
-1200
400
2000
- Ip /µ A
-400
-Ip / µA
IP / µA
600
1500
-1800
200
1000
500
0
0.0
-0.8
0.5
1.0
1.5
-2400
2.0
0
0
-1
[PA] / mmol L
-600
-0.7
-0.6
-0.5
50
100
150
200
250
300
Time / s
-0.4
E / V vs. Ag
-0.3
-0.2
-0.1
-3000
-0.7
-0.6
-0.5
-0.4
-0.3
-0.2
E / V vs. Ag
Differential Pulse Voltammograms obtained with silver office paper-based
electrochemical cell in a 0.5 mol L−1 sulphuric acid as electrolyte solution.
Parameters: step, 0.1 V and amplitude, 0.01 V. A) Successive additions of a
10 µL of picric acid solution resulting in a final concentration of 0.1 – 2.0
mmol L−1. Inset: Analytical curve. Regression linear equation: Ip (µA) = 37×
10−6 + 0.28 (CPA/mmol L−1, R2 = 0.998. B) Different exposure times of flow
air that passed through a chamber containing 0.25g of picric acid. Inset:
Curve obtained of current signal by different exposure times of airborne
explosive.
Characterization of the disposable devices (Paper devices)
Detection of Pb2+
(Environmental
Analysis)
Electronic tongue (taste substance model)
300 mmol L-1 Sucrose
(A)
+
-
0.4 µΑ
+
30 mmol L-1 HCl
(B)
-
40 µΑ
(A)
-1.2
-0.8
-0.4
0.0
(B)
0.4
0.8
-1.2
-0.8
E / V vs Ag/AgCl(sat)
-0.4
0.0
0.4
0.03 mmol L-1 Quinine
(C)
0.8
300 mmol L-1 KCl
(D)
E / V vs Ag/AgCl(sat)
0.4 µΑ
+
+
-
-
v = 100 mV s-1
20 µΑ
(C)
-1.2
-0.8
-0.4
0.0
E / V vs Ag/AgCl(sat)
(D)
0.4
0.8
-1.2
-0.8
-0.4
0.0
E / V vs Ag/AgCl(sat)
0.4
0.8
(Modified with
Prussian blue)
PC2 (30.31%)
Electronic tongue (taste substance model)
20
Sucrose (Sweet)
(30, 100 e 300 mmol L-1)
10
HCl (Sour)
(1, 3 e 30 mmol L-1)
0
Quinine (Bitter)
(0.03, 0,1 e 0,3 mmol L-1)
-10
KCl (Salty)
(30, 100 e 300 mmol L-1)
-20
-30
-20
HCl
KCl
Quinine
Sucrose
-10
v = 100 mV s-1
0
10
20
PC1 (63.36%)
K. Toko, T. Matsuno, K. Yamafuji, K. Hayashi, H. Ikezaki, K. Sato, R. Toukubo, S. Kawarai,
Biosens. Bioelectron., 9 (1994) 359.
30
(Modified with
Prussian blue)
Electronic tongue (taste substance model)
Sucrose (Sweet)
(30, 100 e 300 mmol L-1)
20
HCl (Sour)
(1, 3 e 30 mmol L-1)
PC2 (25.62%)
10
Quinine (Bitter)
(0.03, 0,1 e 0,3 mmol L-1)
0
KCl (Salty)
(30, 100 e 300 mmol L-1)
-10
-20
-20
HCl
KCl
Quinine
Sucrose
-10
v = 100 mV s-1
0
10
PC1 (67.88%)
20
30
Electronic tongue (taste substance model)
(A)
+
400 µA
300 mmol L-1 Sucrose
(A)
(B)
-
30 mmol L-1 HCl
(B)
200 µA
+
-
0.03 mmol L-1 Quinine
(C)
-0.8
-0.4
0.0
0.4
0.8
-0.8
E / V vs Ag/AgCl(sat)
-0.4
0.4
0.8
E / V vs Ag/AgCl(sat)
300 mmol L-1 KCl
(D)
(D)
(C)
+
+
-
-
v = 100 mV s-1
400 µA
400 µA
-0.8
0.0
-0.4
0.0
E / V vs Ag/AgCl(sat)
0.4
0.8
-0.8
-0.4
0.0
E / V vs Ag/AgCl(sat)
0.4
0.8
Electronic tongue (taste substance model)
Sucrose (Sweet)
(30, 100 e 300 mmol L-1)
20
HCl
KCl
Quinine
Sucrose
PC2 (19.96%)
10
HCl (Sour)
(1, 3 e 30 mmol L-1)
Quinine (Bitter)
(0.03, 0,1 e 0,3 mmol L-1)
0
KCl (Salty)
(30, 100 e 300 mmol L-1)
-10
-20
-20
v = 100 mV s-1
-10
0
10
PC1 (63.67%)
20
30
40
Electronic tongue (taste substance model)
Sucrose (Sweet)
(30, 100 e 300 mmol L-1)
2
Quinine (Bitter)
(0.03, 0,1 e 0,3 mmol L-1)
0
KCl (Salty)
(30, 100 e 300 mmol L-1)
v = 100 mV s-1
-2
-3
-2
Cu
)
%
.4
3
PC
2( 0
23
.55
%
3
)
2
6
(6
5
HCl
KCl
Quinine
Sucrose
PC
1
(Prussian Blue)
0
PC3 (6.
8
88%)
HCl (Sour)
(1, 3 e 30 mmol L-1)
Electronic Tongue (Wine discrimination)
Wine Samples. Three different samples of wine (Canção - Flores da Cunha - RS, Góes São Roque - São Paulo e Piagentini - Caxias do Sul - RS) were studied.
1) Canção dry red
2) Canção soft red
3) Canção dry white
4) Góes dry red
5) Góes soft white
6) Piagentini dry red
7) Piagentini soft red
8) Piagentini soft white
9) Piagentini dry white
Electronic Tongue (Wine discrimination)
Cu
Cyclic voltammograms
recorded in different
types of Piagentini wine:
dry white (A), dry red (B),
soft red (C) and soft
white (D) using gold
commercial electrode.
Scan rate:
50 mV s−1.
Electronic Tongue (Wine discrimination)
PC 2 (20.43 %)
16
Piagentini dry white
Piagentini dry red
Piagentini soft white
Piagentini soft red
Cu
8
Samples
preparation,
dilution (v/v)
(1:1) in 2 mol L-1
NaOH
0
-8
-16
-12
-8
-4
0
4
PC 1 (62.85 %)
8
12
16
20
Electronic Tongue (Wine discrimination)
Au
Cyclic voltammograms
recorded in different types of
Piagentini wine: dry white (A),
dry red (B), soft red (C) and
soft white (D) using gold
commercial electrode.
Scan rate:
50 mV s−1.
Measurements were obtained
directly from the wine
samples.
Electronic Tongue (Wine discrimination)
Au
PC 2 (37.57 %)
8
0
Wine without
dilution
-8
Piagentini dry white
Piagentini dry red
Piagentini soft white
Piagentini soft red
-16
-25
-20
-15
-10
-5
PC 1 (50.00 %)
0
5
10
Electronic Tongue (Wine discrimination)
24
Au/Cu
PC 2 (29.22 %)
16
Piagentini dry white
Piagentini dry red
Piagentini soft white
Piagentini soft red
8
0
-8
-16
-20
-10
0
PC 1 (47.56 %)
10
20
Electronic Tongue (Wine discrimination)
Measurements
without dilution
Samples
preparation,
dilution (v/v)
(1:1) in 2 mol L-1
NaOH
1) Canção dry red
2) Canção soft red
3) Canção dry white
4) Góes dry red
5) Góes soft white
6) Piagentini dry red
7) Piagentini soft red
8) Piagentini soft white
9) Piagentini dry white
(▲)
( )
(□)
(○)
( )
(+)
(♦)
(▲)
( •)
Milk adulteration
In September 2007, brazilian consumers
became surprised with the information
that producers had adulterated the milk
sold in supermarket.
Hydrogen
peroxide (H2O2)
Electronic Tongue (Milk)
Paixão TRLC, Bertotti M, Sensors and Actuators B-Chemical 137 (2009) 266-273
Patent - 04 may 2009; Internacional registry: Protocol Nº 018090022336.
Electronic Tongue (Milk)
Paixão TRLC, Bertotti M, Sensors and Actuators B-Chemical 137 (2009) 266-273
Patent - 04 may 2009; Internacional registry: Protocol Nº 018090022336.
Electronic Tongue (Milk)
Paixão TRLC, Bertotti M, Sensors and Actuators B-Chemical 137 (2009) 266-273
Patent - 04 may 2009; Internacional registry: Protocol Nº 018090022336.
Electronic Tongue (Milk)
Paixão TRLC, Bertotti M, Sensors and Actuators B-Chemical 137 (2009) 266-273
Patent - 04 may 2009; Internacional registry: Protocol Nº 018090022336.
Whisky
"Art. 94. Whiskey, "whiskey or whiskey" is a drink with alcoholic content of thirty-eight to
fifty-four percent by volume at twenty degrees Celsius, obtained from the simple
alcoholic distillate aged grain, fully or partially malted, may be added potable ethyl
alcohol from agricultural origin or simple alcoholic distillate from cereals …. water for the
correction alcohol concentration ..."
Infractions and its Classification
Art. 129. Constitute violations:
I - misrepresent, falsify or defraud drink and raw materials;
XII - use of additives not authorized by specific legislation;
XIII - change purposely drink or raw materials
Law nº 2.314, 09/04/1997
Commercial Electronic Tongue (Whisky)
http://www.curiosite.com/html/regalos-originales/engarrafonix_como.html
http://www.curiosite.com/html/regalos
Electronic Tongue(Whisky)
Whisky +
1 mol L-1 NaOH
WS, Wall Street
Novakowski W., Paixão T. R. L. C., Microchemical Journal, 99 (2011) 145-151
Electronic Tongue (Whisky) – Dilution
Whisky + 1 mol L1 NaOH
WS, Wall Street
Novakowski W., Paixão T. R. L. C., Microchemical Journal, 99 (2011) 145-151
Electronic Tongue (Whisky) – dye addition
Whisky +
1 mol L-1 NaOH
WS, Wall Street
Novakowski W., Paixão T. R. L. C., Microchemical Journal, 99 (2011) 145-151
Electronic Tongue (Whisky) – Mixture of different drink brands
Whisky +
1 mol L-1 NaOH
WS, Wall Street;
Bf, Ballantine's Finest;
Ch, Chanceler;
Bl12: Balantine's 12 years old;
O8: Old Eight;
Amb: Ambassador 12 years old
Novakowski W., Paixão T. R. L. C., Microchemical Journal, 99 (2011) 145-151
Fuel (Ethanol Fuel)
- Adulteration process:
- Water addition;
- Methanol Addition.
Electronic tongue (Fuel)
Cu
3
Ethanol 20 % (v/v)
1 mol L-1 NaOH
I / mA
2
1
Ethanol 10 % (v/v)
1 mol L-1 NaOH
0
-0.8
v = 50 mV
s-1
1 mol L-1
NaOH
-0.4
0.0
E / V vs Ag/AgCl
0.4
0.8
Electronic Tongue (Fuel)
H2O Content
8
5,5%
8%
10%
15%
20%
Adulterated
4
PC 2 (8.36%)
Fuel with
addition of NaOH
Adulterated
0
-4
Permitted
Adulterated
-8
-12
Adulterated
-30
-20
-10
0
10
20
PC 1 (77.26%)
30
40
50
Electronic Tongue (Fuel)
Electronic Tongue (Fuel)
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.
Electronic Tongue (Fuel)
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.
Electronic Tongue (Fuel)
5.6%
4
PC2 (18.90%)
7.5%
2
0
15%
-2
10%
-4
-15
-10
-5
0
PC1 (75.29%)
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.
5
10
Electronic Tongue (Fuel)
Sensor
Binary Answer
Instrumentation
Adulterated
FUEL
Patent Register Number: BR1020120312026
Electronic Tongue (Fuel)
PCA score biplots for different solvents. PCA scores were obtained from the capacitance
data directly from pure standard solvents using a Cu interdigitated electrode.
Number of replicates per sample: 3.
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.
Electronic Tongue (Fuel) - Quantification
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.
Electronic Tongue (Gun Shot Residues)
Salles M.O., Bertotti M., Thiago R. L. C., Sensors
and Actuators B-Chemical 166 (2012) 848-852
Electronic Tongue (Gun Shot Residues)
40
40
B
0
-40
-40
I / nA
I / nA
A
0
-80
-80
-120
-120
-160
-160
-0.8
-0.4
0.0
0.4
0.8
-0.8
1.2
0
-40
-40
I / nA
I / nA
C
-80
-120
-160
-160
0.0
0.4
0.8
E / V vs. Ag/AgCl (sat. KCl)
Salles M.O., Bertotti M., Thiago R. L. C., Sensors
and Actuators B-Chemical 166 (2012) 848-852
0.8
1.2
1.2
D
-80
-120
-0.4
0.4
40
0
-0.8
0.0
E / V vs. Ag/AgCl (sat. KCl)
E / V vs. Ag/AgCl (sat. KCl)
40
-0.4
-0.8
-0.4
0.0
0.4
0.8
E / V vs. Ag/AgCl (sat. KCl)
1.2
Electronic Tongue (Gun Shot Residues)
PC2 (23.90 %)
400000
0
-400000
-800000
-800000
-400000
0
PC1 (49.88 %)
Salles M.O., Bertotti M., Thiago R. L. C., Sensors
and Actuators B-Chemical 166 (2012) 848-852
400000
800000
Electronic Tongue (Gun Shot Residues)
360000
PC2 (2.440 %)
240000
120000
0
-120000
-240000
-180000
-120000
-60000
0
PC1 (92.55 %)
Salles M.O., Bertotti M., Thiago R. L. C., Sensors
and Actuators B-Chemical 166 (2012) 848-852
60000
120000
Electronic Tongue (Drugs of Abuse – Drug Origin)
Cocaine Samples
60%
54%
50%
40%
35%
30%
20%
11%
10%
8%
4%
1%
1%
1%
1%
0%
FenacetinaLevamisole
Levamisol Cafeine
Cafeína Lidocaine
Lidocaína Benzocaine
Benzocaína Hidroxizine
Hidroxizina Diltiazen
Diltiazem Paracetamol
Paracetamol Nothing
Nenhum Added
Phenacatin
Adulterant
Data from Dr. Adriano Maldaner
Electronic Tongue (Drugs of Abuse – Drug Origin)
Cocaine and cocaine spiked with some adulterants
Cocaine
Benzocaine 1mM
Cafeine 1mM
Diclofenac 1mM
Phenacetin 1mM
Hydroxyne 1mM
Levamisole 1mM
Lidocaine 1mM
Paracetamol 1mM
Procaine 1mM
PC2 (25.94%)
0.0002
0.0000
-0.0002
-0.0002
0.0000
PC1 (39.24%)
0.0002
Electronic Tongue (Drugs of Abuse – Drug Origin)
Cocaine
Sample 7
Benzocaine 1mM
Cafeine 1mM
Diclofenac 1mM
Phenacetin 1mM
Hydroxyne 1mM
Levamisole 1mM
Lidocaine 1mM
Paracetamol 1mM
Procaine 1mM
0.0004
0.0000
0.25
0.20
I / mA
PC2 (24.43%)
0.0002
-0.0002
-0.0004
-0.0004
Paracetamol 1mM
Sample 7
0.15
0.10
0.05
0.00
-0.0002
0.0000
0.0002
PC1 (51.27%)
0.0004
0.0 0.0006
0.4
0.8
1.2
1.6
E / V vs. Ag/AgCl(KCl sat.)
Electronic Tongue (Drugs of Abuse – Drug Origin)
Sample seized by the Police of São Paulo
-0.00004
0.0004
-0.00006
-0.00008
PC2 (6.61%)
0.0002
-0.00010
0.00065
0.00070
0.00075
0.0000
-0.0002
-0.0004
-0.0008
-0.0004
0.0000
PC1 (86.39%)
0.0004
0.0008
0.00080
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Electronic Tongue (Drugs of Abuse – Drug Origin)
Adulterant concentration found in two cocaine samples.
Sample
Adulterant
Concentration found
/ mmol L-1
3
Phenacetin
(1.0 ± 0.2)
7
Paracetamol
(1.70 ± 0.08)
Anti-doping test
Anti-doping test
http://www.fifa.com/aboutfifa/footballdevelopment/
medical/antidoping/index.html
Electronic Tongue (Anti-doping test)
20
Synthetic
Urine
0
-20
20
PC
1
0
0
-20
(31.
79%
)
-40
30
2
40
(2
9.
5%
)
-30
PC
)
PC 3 (18.62%
Synthetic Urine
with Cocaine
Electronic Tongue (Milk again) – Melamine, Urea and Formaldehyde
PCA 3D plots of commercial (Elegê®) milk samples, unadulterated (black squares),
and adulterated with 10.0 mmol L-1 formaldehyde (red circles), 0.95 mmol L-1 melamine
(blue up triangles), and 4.16 mmol L-1 urea (green down triangles). Whole milk (A),
skimmed milk (B), and semi-skimmed milk (C). Number of replicates per sample: 3.
L. Bueno, M. O. Salles, W. R. de Araujo
and T. R. L. C. Paixão, Analytical Methods (submitted)
Electronic Tongue (Milk again) – Melamine, Urea and Formaldehyde
PCA 3D plots of commercial (Elegê®) milk samples, unadulterated (black squares),
and adulterated with 10.0 mmol L-1 formaldehyde (red circles), 0.95 mmol L-1 melamine
(blue up triangles), and 4.16 mmol L-1 urea (green down triangles). Whole milk (A),
skimmed milk (B), and semi-skimmed milk (C). Number of replicates per sample: 3.
L. Bueno, M. O. Salles, W. R. de Araujo
and T. R. L. C. Paixão, Analytical Methods (submitted)
Electronic Tongue for disease diagnostics
Integration of
Smart materials (Surrey) with
Pattern Recognition Techniques (USP)
and Nanofabrication techniques (NCSU) for
The development of novel electrochemical disease
diagnostics.
Dr Subrayal M. Reddy
Dr Roger J. Narayan
Department of Chemistry, Faculty of
Engineering and Physical Sciences, University
of Surrey, Guildford, UK, GU2 7XH
Joint Department of Biomedical
Engineering, University of North Carolina,
Raleigh, USA
Electronic Tongue with Molecular Imprinted Polymers (MIPs)
Polymerisation
Loose network
Molecular imprinted
polymer
Electrostatic and hydrogen
bonding interactions between
monomer and template molecule
Template
elution
Rebinding
Electronic Tongue with Molecular Imprinted Polymers (MIPs)
BHb MIP on glassy carbon electrode
(Modified Electrode)
t = 0 min
t = 10 min
Transducer signal
changes depending
on the protein
selectively binding
0.00
j / A mm-2
0.02
0.04
Transducer
0.06
Modifier
Layer
0.08
0.10
-1.0
Electrolyte: PBS (pH 7.4),
SDS 5% (w/v) + 15.4 µmol L1 BHb solution
-0.8
-0.6
-0.4
-0.2
E/V vs Ag/AgCl (sat. KCl)
0.0
Electronic Tongue with Molecular Imprinted Polymers (MIPs)
Proof of concept
Electronic Tongue with Molecular Imprinted Polymers (MIPs)
BHb MIP on glassy carbon electrode
10 min
0 min
BHb
BSA
Cyt C
EMb
40
BHb
BSA
Cyt C
EMb
20
PC 2 (27.94%)
PC 2 (36.27%)
20
0
-20
0
-20
-40
-40
-20
0
20
40
60
-40
-40
-20
PC 1 (58.74%)
Lígia Bueno, Hazim F. El-Sharif, Maiara O. Salles, Ryan D. Boehm,
Roger J. Narayan, Thiago R. L. C. Paixão and Subrayal M. Reddy, Sensors and Actuators
B: Chemical, Submitted
0
20
PC 1 (64.66%)
40
Electronic Tongue with Molecular Imprinted Polymers (MIPs)
Forward:
Point-of-care test
Screening for protein-based disease
Markers: e.g. Cancer; diabetes; cardiovascular
Data base comparison
BHb
BSA
Cyt C
EMb
PC 2 (27.94%)
20
PSA
Answer
0
-20
-40
-40
-20
0
20
PC 1 (64.66%)
Prostate cancer
marker
40
Molecular Imprinted Polymers (MIPs) for illicit drug detection
Phenacetin
Carbon Ink Paper Devices
Cocaine
MIP
Bare Electrode
+
Pyrrole/phenacetin MIP
Modified Electrode
Aminopyrine
Maiara O. Salles, William R. de Araujo, Thiago R. L. C. Paixão, Electrochimica Acta, submitted
Molecular Imprinted Polymers (MIPs) for illicit drug detection
Phenacetin
Carbon Ink Paper Devices
MIP
400
I / µA
Cocaine
A
Bare Electrode
200
0
-1.0
+
0.0
0.5
1.0
1.5
2.0
E / (V vs Ag/AgCl(KCl sat.))
I / µA
120
Procaine
-0.5
Pyrrole/phenacetin MIP
Modified Electrode
B
60
0
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
E / (V vs Ag/AgCl(KCl sat.))
Maiara O. Salles, William R. de Araujo, Thiago R. L. C. Paixão, Electrochimica Acta, submitted
Trade-Offs in Chemical Analysis
- Sensors must be robust
- But robustness requires weak interactions only: implies low
sensitivity and low chemical specificity
Paper based device and Colorimetric detection:
• Make the sensors disposable
• Probe a wide range of chemical interaction and reaction
Including strong sensor-analyte binding
• Do it cheap: use visual reporters
Convert chemical interaction responses to a visual output,
i.e., an Electronic Tongue with visual imaging and
Optoelectronic Nose
Background from literature
Chemo-responsive sensor using ORMOSIL (organically modified
silica) to molecular recognition
Solvatochromic Dyes
Base sensitive pH indicators
metalloporphyrins
Acid sensitive pH indicators
Pin Printing of Arrays
Reprinted with permission from John Wiley and Sons:
Molecular Recognition and Discrimination of Amines with a
Colorimetric Array, Angewandte Chemie International Edition
2005, 44, 4528-4532. Copyright 2014.
Suslick’s Colorimetric Array Detector
Chemo-responsive sensor using ORMOSIL (organically modified
silica) to molecular recognition
- Printed array of chemical responsive dyes
- Digitally image obtained using a scanner (Before and after images)
- Difference Map (After image subtract of Before image) is a “molecular
fingerprint”: a unique patterned of R, G and B subtracted values
Before Exposure
After Exposure
R, G and
B values
|Rafter – Rbefore|
|Gafter – Gbefore|
|Bafter – Bbefore|
Before
Values
Reprinted with permission from Suslick K.S. et al.,
Colorimetric Sensor Arrays for Volatile Organic
Compounds, Anal. Chem., 2006, 78 (11), pp 3591–3600.
Copyright 2014 American Chemical Society.
Difference Map
decylamine
R, G and After
B values Values
Each compound has a unique pattern !!!
Difference Maps are Molecular Fingerprints
Reprinted with permission from Suslick K.S. et al.,
Colorimetric Sensor Arrays for Volatile Organic
Compounds, Anal. Chem., 2006, 78 (11), pp 3591–3600.
Copyright 2014 American Chemical Society.
Comparison
Suslick’s Approach
Proposed Method
SUBSTRATE
ORMOSIL
(organically modified silica)
FABRICATION
Pin Printing
Wax Printing + Chemical
Application
MEASUREMENT
Scanner + ChemSens®
Smarthphone +
Home-Made App.
Coffee aromas, Sugars, Vapour phase TATP,
Natural and Artificial Sweeteners, Soft drink,
Beers, Pathogenic bacteria and Organic vapours.
Applications
Chromatography Paper
Objective
Fabrication of the Colorimetric Device
1) Wax
Printing
2) Temp.
Chromatographic
Paper (Filter Paper)
Application of
Reagents
3 min.
120 oC
1. Creatine
2. KI/H+
3. Aniline
1
2
3
Why choose these reagents?
KI/H+
- TATP and HMTD can decompose to H2O2 or organic peroxides;
R. A. A. Munoz, D. L. Lu, A. Cagan and J.Wang, Analyst, 2007, 132, 560.
2I- + H2O2 + 2H+
I2 + 2H2O
iodide to form iodine, resulting in brown coloration of the spot.
Franchimont test
- The Franchimont test (N,N-diethylaniline dissolved in glacial acid acetic)
can be used as a colorimetric test to detect various explosives, including
dinitrobenzene, and yields a brown color.
With a modification of this test, we observed that mixing nitrobenzene
and aniline produced a yellow color.
Why choose these reagents?
Jaffe's reaction
- Creatinine forms a red-orange compound with nitrocompounds
A. R. Butler, Clin. Chim. Acta, 1975, 59, 227.
Janovsky complex
Creatinine
Picric Acid
Measurements using the proposed device
1. Creatine
2. KI/H+
3. Aniline
Imagine
Acquisition
1
2
3
Application of
sample
For example,
HMTD explosive application
Imagine
Acquisition
Software for extraction of RGB values
The application was built in Apple Xcode 4.3.2 using the Apple iOS 5 Software Development
Kit (SDK; Apple Inc., Cupertino, CA, USA). The RGB values for each spot and the standard
deviation for each component were measured using a specific Application Program Interface
(API) that converted each pixel of the image into 24-bit (8 bits per component) data.
RGB
Extraction
1
2
3
After exposition
to HMTD
1. Creatine
2. KI/H+
3. Aniline
Before exposition
to HMTD
Measurements using the proposed device
|Rafter – Rbefore|
Difference Map
|Gafter – Gbefore|
|Bafter – Bbefore|
Sample
Discrimination
(chemometric
approach)
Smarthphone chamber or support
Closed chamber providing a
fixed focal distance and
homogeneous lighting was
built using black poly(methyl
methacrylate)
Smarthphone chamber or support
Closed chamber providing a
fixed focal distance and
homogeneous lighting was
built using black poly(methyl
methacrylate)
Performance of the smarthphone camera
RGB values and relative standard deviations obtained with the developed
colorimetric sensor from blue, red and green squares.
Explosives: Real Test
0 minutes
5 minutes
10 minutes
15 minutes
Colour representation of the RGB values for 0 (A), 5 (B), 10 (C)
and 15 (D) minutes of reaction.
Explosives: Real Test
0 minutes
5 minutes
10 minutes
15 minutes
Colour representation of the RGB values for 0 (A), 5 (B), 10 (C)
and 15 (D) minutes of reaction.
Explosives: Real Test
After 15 min of reaction time: (A) PCA scores
plot, (B) dendogram of 15 samples, and (C)
loadings plot of colorimetric signals for the five
different explosive samples with three
different reagents. Legend of the PCA graph: ■
– TATP; ● – HMTD; ▲ – Nitrobenzene (NB); ▼
– 4-amino-2-nitrophenol (4A2NP); ♦ - Picric
acid (PA).
Mixture of Explosives: Real Test
PCA graph:
■ – TATP;
● – HMTD;
▲ – Nitrobenzene (NB);
▼ – 4-amino-2-nitrophenol
(4A2NP);
♦ – Picric acid (PA),
○ – Nitro explosives (NB +
4A2NP + PA);
□ – Peroxy explosives (TATP +
HMTD);
◊ – All explosives (NB + 4A2NP
+ PA + TATP + HMTD).
Quantitative Performance
■ – TATP;
● – HMTD;
▲ – Nitrobenzene (NB);
▼ – 4-amino-2-nitrophenol (4A2NP);
♦ – Picric acid (PA),
Quantitative Performance
Electronic Tongues – Final Considerations
Despite the introduction of electronic noses begin the process of developing this niche
research, electronic tongues have been developed more quickly than electronic noses.
However, several issues remain to be resolved before these devices become more
affordable.
1. experimental evaluation of the mechanisms of sensors and theoretical
considerations of the electronic tongue operation;
2. development of new sensors and sensor arrays;
3. development of practical application for common tasks.
Y. Vlasov, A. Legin, A. Rudnitskaya 373 (2002) 136
Electronic Tongues – Final Considerations
Book: The Coming Robot Revolution
Publisher: Springer New York
DOI 10.1007/978-0-387-85349-9
Copyright 2009
ISBN 978-0-387-85348-2 (Print)
DOI 10.1007/978-0-387-85349-9_3
Pages 1-18
Subject Collection Engineering
SpringerLink Date Monday, April 20, 2009
Língua eletrônica – Considerações finais
Acknowledgments
Electronic Tongue and Chemical Sensors Group
NAPMI: Núcleo de Apoio à
Pesquisa
em
Materiais
Inteligentes (Research Group
in Smart Materials)
Funding Agencies:
470919/2011-6
2009/07859-1
2012/12106-5
2013/50751-2
Royal Society Grant
Ref: EI130745
Electronic Tongue (Fuel)
Bueno L., Paixão T. R. L. C., Talanta, 87 (2011) 210 – 215.