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Intrinsic conducting polymers (CPs) have excellent electrochemical characteristics, such as tailored electrical conductivity by electronic doping, high environmental stability, and biocompatibility. This entry intend to overview the use of conducting polymers (CPs), extensively studied due to their high versatility and electrical properties, as chemical sensor arrays in electronic tongues and noses. Their performance in terms of sensitivity and other parameters will be studied based on the characteristic features of common conducting polymers, such as electrical conductivity and nanostructured morphology. Furthermore, the application of electronic devices in commercial prototypes will also be included here.
Electrochemical Device |
Analyte |
Working Media |
Sample |
Analytical Parameters |
Ref. |
|
---|---|---|---|---|---|---|
LD (µM) |
LR (µM) |
|||||
PTh |
||||||
MWCNT/PTh/Pt |
BPA |
PBS pH 7.5 |
Water |
0.009 |
0.05–0.4 |
[56] |
MnO2/PTh/rGO/GCE |
MP |
PBS pH 7 |
Human urine and blood |
0.0057 |
0.5–10 |
[57] |
GO-4-ATP-Au-PTh/Au GCE |
Nicotine |
PBS pH 7 |
Serum, urine, cigarette |
0.17 |
1.0–30 |
[58] |
PTh-AgBr |
Glucose |
NaOH |
Human blood plasma |
0.31 |
4–5000 |
[59] |
PTh-Ag/GCE |
L-Tryp |
PBS pH 7 |
Soybeans extract |
0.020 |
0.2–400 |
[60] |
PEDOT |
||||||
PEDOT/IL/GCE |
DA |
PBS pH 7.4 |
Human urine |
0.033 |
0.2–328 |
[61] |
UiO-66-NH2@PEDOT/GA/GCE |
PCMC |
ABS pH 6 |
Tap water |
0.2 |
0.6–18 |
[62] |
PEDOT/AG/GCE |
AC |
PBS pH 7 |
Local tablets |
0.041 |
0.15–5881 |
[63] |
Cu2O/PEDOT/MWCNT |
Glucose |
NaOH |
Human blood serum |
0.04 |
0.495–374 |
[64] |
GC/PEDOT-AuNPs-SV |
CA |
PBS pH 7 |
Juice |
4.24 |
10–1000 |
[65] |
PEDOT-Tyr/SNG-C |
CA |
PBS pH 7 |
Wine, beer |
4.33 |
10–300 |
[66] |
PEDOT/PEDOT-SH/Au |
Nitrite |
PBS pH 6.9 |
Tap water, milk |
0.051 |
0.15–1000 |
[67] |
PEDOT/Au |
UA |
PBS pH 6.6 |
Milk |
7.0 |
6–200 |
[68] |
GCE/PEDOT-MC/AgNPs |
Rutin |
PBS pH 3 |
Tablets |
0.0035 |
0.005–0.5 |
[69] |
Pt/PEDOT-PBNPS |
H2O2 |
ABS pH 5.5 |
Human blood |
1.4 |
5–1000 |
[70] |
PANI |
||||||
Co3O4@PANINFs/GCE |
Glucose |
PBS pH 7.4 |
Human serum |
60 |
100–8000 |
[71] |
TiO2@PANI@Au/GCE |
Hydrazine |
NH3/NH4+ pH 9 |
Power plant sewage |
0.15 |
0.9–1200 |
[72] |
PANI/SnO2/GCE |
Nitrite |
PBS pH 6 |
- |
0.04 |
0.12–7777 |
[73] |
GCE/PANI-Fe3O4 |
DA |
PBS pH 7 |
Water |
0.176 |
0.2–2.4 |
[74] |
GCE/PANI-NiO |
DA |
PBS pH 7 |
Water |
0.166 |
0.2–2.4 |
[74] |
α-Fe2O3/PANI/GCE |
UA |
PBS pH 7 |
Human urine |
0.038 |
0.01–5 |
[75] |
NiO-NPs@PANINS/SPE |
Glucose |
NaOH |
Human blood serum |
0.06 |
1–3000 |
[76] |
MeGO/PANI |
AA |
PBS pH 7.4 |
- |
2.0 |
8–5000 |
[77] |
PPy |
||||||
Fe3O4@PPy/MWCNTs/GE |
AT |
BR pH 4 |
Serum, tablets |
0.0230 |
0.0314–201 |
[78] |
AuNP/PPy/GCE |
L-dopa |
PBS pH 7 |
Urine |
0.075 |
0.1–6.0 |
[79] |
PDA/PPy/GCE |
UA |
PBS pH 8 |
Human serum, urine |
0.11 |
0.5–40 |
[80] |
PGE/CuO-NPs/PPy |
TR |
PBS pH 8.5 |
Tablets |
0.001 |
0.005–380 |
[81] |
PPy:LAC |
Lactate |
KNO3 |
Human tear, rat blood |
81.0 |
100–10,000 |
[82] |
AuCu/PPy/Cu-TCCP |
H2O2 |
PBS pH 8 |
Medical H2O2 solution |
0.0067 |
0.71–24,100 |
[83] |
AA: ascorbic acid; ABS: acetic buffer solution; AC: acetaminophen; AT: atorvastatin; ATP: adenosine triphosphate; BPA: bisphenol A; BR: Britton-Robinson; CA: caffeic acid; CuO-NPs: copper oxide nanoparticles; DA: dopamine; PTh: polythiophene; GA: graphene aerogel; GCE: glassy carbon electrode; IL: ionic liquid; LAC: lactate; LD: limit of detection; LR: linear range; L-Tryp: L-tryptophan; MC: mesoporous carbon; MP: methyl parathion; MWCNT: multi-walled carbon nanotubes; PANI: polyaniline; PANINS: polyaniline nanofibers; PBNPS: Prussian blue nanoparticles; PBS: phosphate buffer solution; PCMC: p-chloromethylcresol; PEDOT: poly-(3,4-ethylenedioxythiophene); PGE: pencil graphite electrode; PPy: polypyrrole; rGO: reduced-graphene oxide; SPE: screen-printed electrode; SV: sinusoidal voltage; TCCP: meso-tetra-(4-carboxyphenyl)-substituted porphyrins; TR: tramadol; and UA: uric acid.
Sensor Array |
Sample |
Use |
Multivariate Calibration |
Ref. |
|
---|---|---|---|---|---|
No CP Sensor |
CP Sensor |
||||
SNG-C |
PEDOT/Pt |
Musts |
Discrimination of samples collected at different ripening times |
PCA iPLS PLS |
[93] |
- |
PEDOT/Pt |
Red wines |
Classification of different samples and origin |
PCA PLS |
[94] |
Pt Au |
PEDOT/Pt |
Fruit juice |
Discrimination between samples from different fruits |
PCA PLS-LDA |
[95] |
IDE PA6/IDE |
PA6/PANI/IDE (0.25–5.0% PANI) |
Bovine milk |
Discrimination of samples according to tetracycline residue content |
PCA |
[96] |
CE AuCE rGO-CE rGO-AuCE |
PANI-CE PANI-AuCE |
Vinegar, sugar |
Multiflavor detection |
PCA |
[97] |
C/SPE NiO/C/SPE MWCNT/C/SPE SWCNT/C/SPE Pt |
PANI/C/SPE |
Red wine |
Phenolic content |
PCA |
[98] |
SWCNT/SPCE MWCNT/SPCE |
PPy-DSA/SPCE |
White wine |
Discrimination according to varietal origin |
PCA LDA |
[99] |
CPE-CoPc CPE-LuPc2 CPE-LuPc2 |
PPy-dopant/Au Dopant: SO4, DSA, FCN, AQDS, PWA, TSA |
Red wine |
Evaluation of chemical adulteration |
PCA PLS |
[100] |
GdPc2/CSPE DyPc2/CSPE CSPE |
PPy-dopant/CSPE Dopant: FeCN, NP, Mo |
Beef |
Determination of ammonia and putresceine |
PCA PLS-LDA |
[101] |
- |
PPy- dopant/Pt Dopant: DSA, H2SO4, FCN, AQDS, PWA, TSA |
Beer |
Evaluation of bitterness and alcoholic strength |
PCA PLS |
[102] |
- |
PPy-dopant/Pt Dopant: FCN, NP, PWA, H2SO4, MO, AQS |
Olive oil |
Evaluation of bitterness |
PCA PLS |
[103] |
- |
PPy-dopant/SPCE Dopant: DSA, SO4, FCN |
Wine |
Classification of wines according to vintage year |
PCA LDA |
[104] |
Graphite-epoxy PtNPs CuNPs |
PANI PPy |
Wine |
Classification of wines and recognition of the oxygenation effect |
PCA |
[105] |
AQDS: anthraquinone-2,6-disulfonic acid, disodium salt; AQS: anthraquinone-2,6-disulfonic acid; CNT: carbon nanotubes; CoPc: cobalt phthalocyanine; CPE: carbon paste electrode; CuNPs: copper nanoparticles; DSA: sodium 1-decanesulfonate; FCN: potassium hexacyanoferrate (II); IDE: interdigitated electrodes; LDA: linear discriminant analysis; LuPc2: lutetium bis-phthalocyanine; MO: sodium molybdate; MWCNT: multi-walled carbon nanotubes; PA6: polyacrilamide; PANI: polyaniline; PCA: principal component analysis; PEDOT: poly-(3,4-ethylenedioxythiophene); PLS: partial least squares regression; PPy: polypyrrole; PWA: phosphotungstic acid; PtNPS: platinum nanoparticles; rGO: reduced-graphene oxide; SNG-C: sonogel-carbon; SPCE: screen-printed-carbon electrode; SPE: screen-printed electrode; SWCNT: single-walled carbon nanotubes; and TSA: p-toluenesulfonic acid.
Gas Sensor Device |
Target Gas |
Range (ppm) |
Sensing Performance |
Ref. |
||
---|---|---|---|---|---|---|
Gas Conc. (ppm) |
Recovery Time (s) |
Response Time (s) |
||||
SnO2/PTh |
NO2 |
10–200 |
10 |
- |
2.07 |
[116] |
P3CT/CNT |
NMPEA |
0.004–0.032 |
0.004 |
40 |
20 |
[117] |
PEDOT:PSS/FeCl3 |
NH3 |
0.2–200 |
0.5 |
- |
20 |
[118] |
WO3-PEDOT:PSS |
LPG |
500–3000 |
500 |
54 |
29.4 |
[119] |
PANI/PVDF |
NH3 |
0.2–5 |
0.2 |
235 |
174 |
[120] |
PANI/SnO2 |
NO2 |
5–55 |
37 |
25 |
17 |
[121] |
SnO2/rGO/PANI |
H2S |
0.05–10 |
2 |
78 |
82 |
[122] |
PANI-NF |
LPG |
100–1000 |
700 |
200 |
50 |
[123] |
PPy/rGO |
NH3 |
1.0–4.0 |
1.0 |
300 |
60 |
[124] |
PPy thin film |
NO2 |
10–100 |
10 |
374 |
218 |
[125] |
PPy nanoribbons |
CH3CH2OH |
- |
100 |
31 |
2 |
[126] |
PPy-Ag |
CH3COCH3 |
25–600 |
580 |
150 |
175 |
[127] |
PPy-CNT |
H2 |
1–100 |
10 |
- |
>1.0 |
[128] |
CNT: carbon nanotubes; LPG: liquified petroleum gas; NF: nickel ferrite; NMPEA: n-methylphenethylamine; P3CT: poly[3 -(6-carboxyhexyl)thiophene-2,5-diyl]; PANI: polyaniline; PEDOT: poly-(3,4-ethylenedioxythiophene); PPy: polypyrrole; PSS: poly(styrenesulfonate); PTh: polythiophene; PVDF: polyvinylidene; and r-GO: reduced-graphene oxide.
PANI Sensor Array |
Sample |
Use |
Multivariate Calibration |
Ref. |
---|---|---|---|---|
PANI-dopant/IDGEs Dopant: CSA, DBSA, HCl |
Strawberry Grape Apple |
Discrimination of samples according to aromatic substances |
PCA |
[139] |
PANI-HCl/PGIEs PANI-HCl/IDEs |
Strawberry Grape Apple |
Detection of different aromas |
PCA |
[140] |
PANI-dopant/IDGEs Dopant: HCl, TSA, CSA, MSA |
Cow’s estrus |
Determination of estrus times of cows |
PCA |
[141] |
PANI-dopant/IDEs Dopant: HCl, TSA, CSA, MSA |
Bananas |
Monitoring of bananas ripeness |
PCA |
[142] |
PANI-dopant/PGIEs Dopant: CSA, HCl, DBSA |
Gummy candies |
Monitoring of aromas during candy storage |
PCA |
[143] |
PANI-CSA/Chitosan PANI-DBSA/TiO2 PANI-DBSA/CNT |
Simulated human breath |
Preliminary diagnoses of kidney disease |
PCA LDA |
[144] |
PANI/AuNPs |
Human breath |
Early diagnoses of renal diseases |
PCA LDA |
[145] |
PANI-dopant/MWCNT PANI-dopant/GO Dopant: CSA, DBSA, HCl |
Essential oils |
Determination of quality of essential oils |
PCA |
[146] |
CSA: camphorsulfonic acid; DBSA: dodecylbenzenesulfonic acid; GO: graphene oxide; IDE: interdigitated electrode; MSA: methanesulfonic acid; MWCNT: multi-walled carbon nanotubes; PANI: polyaniline; and TSA: p-toluene sulfonic acid.
It is not ambitious to think that the analytical applications of E-Tongues/Noses possess a great impact, not only in the foodstuff ambit but also in the health and environmental sector. Besides, this impact is rising sharply, reflecting the great need in society for these devices. Therefore, their implementation in commercial devices is exceedingly pursued by many sensor companies. Currently, there are some examples of its commercialization.
Concerning E-tongues, Alpha M.O.S and Insent Inc. offers two models (αAstree and TS-5000Z, respectively) that have been used in the evaluation of food quality in the last decade[147][148][149][150][151]. Other laboratory prototypes were also employed for pharmaceutical analysis, providing very satisfactory results, as those obtained with commercial systems[152].
Regarding E-noses, a commercial system containing several conducting polymers as sensor arrays (Cyranose 320®), offered by Sensigent, was employed in the screening of several diseases (breast and lung cancer[153][154][155], asthma[156][157] and amyotrophic lateral sclerosis[158], among others), identification of foodstuffs (rice, wines[159] and fruits[160]) and classification of road asphalt samples[161][162]. Additionally, fecal VOCs can be inspected as well, informing about the microbial enterotype of infants[163]. Other companies also supply E-noses. For example, AromaScan A32S® (Osmetech Inc.) provides useful information about the diagnose of urban trees, being able to discriminate VOCs from healthy and decay woody samples[164] and the assessment of the quality of catfish meat[165]. In this work, off-flavour in catfish filets can be identified from good-flavour ones by means of PCA. Notably, the new device tested displayed promising features for the analysis of commercial beverages[166].
Despite the excellent analytical results provided at laboratory scale in food, pharmaceutical and medical sectors, only some timid examples can be found commercially available. In our modest opinion, the inclusion of CPs and their development may pave the way to keep growing and reach the desired applicability of E-tongues and E-noses systems. Nowadays, in order to climb up into higher technological readiness levels (TRLs), the developed devices must be able to perform reliable, robust, fast, accurate and in-situ measurements using diverse samples, by using a non-complex, low cost and portable instrumentation. The stability of the conducting coatings is another issue to take into account, since the repeatability of the responses provided with the devices can be affected. The conducting film may be passivated after performing successive electrochemical assays, as well as film overoxidation can take place at high potentials. Furthermore, stability can be affected by swelling/deswelling phenomena. With the aim to minimize these factors, several parameters, including analyte concentration, film characteristics (e.g thickness and morphology) and instrumental conditions should be carefully controlled. Further research in this sense is under study to accomplish all the commercial requirements mentioned.