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Molecular recognition of nitrites and nitrates in water samples using graphene-based stochastic microsensors Raluca Ioana Stefan-Van Staden, Mariana Mincu, Jacobus (Koos) Frederick van Staden, and Livia Gugoasa Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b02467 • Publication Date (Web): 26 Jul 2018 Downloaded from http://pubs.acs.org on July 26, 2018

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Analytical Chemistry

Molecular recognition of nitrites and nitrates in water samples using graphene-based stochastic microsensors Raluca-Ioana Stefan-van Staden1,2, *, Mariana Mincu2, Jacobus Frederick van Staden1, Livia Alexandra Gugoasa1 1

Laboratory of Electrochemistry and PATLAB, National Institute of Research for

Electrochemistry and Condensed Matter, 202 Splaiul Independentei Str., 060021, Bucharest-6, Romania 2

Faculty of Applied Chemistry and Material Sciences, University Politehnica of Bucharest, Bucharest, Romania.

Abstract Two stochastic microsensors based on graphene powders and protoporphyrin IX, were proposed for the simultaneous assay of nitrite and nitrate in water samples. The proposed microsensors can provide a fast screening of water samples with a qualitative and quantitative analysis for NO2and NO3- at very low concentration levels. The linear concentration ranges were wide – covering clean as well as polluted waters. The results provided by the stochastic microsensors were in agreement with those obtained by utilization of standard methods, recoveries higher than 99.00% and RSD lower than 1.00% proving that the method can be reliable used for simultaneous assay of NO2- and NO3- in water samples. Keywords: nitrite, nitrate, stochastic sensors, graphene, protoporphyrin IX

*

Corresponding author: Tel. +40751507779; Fax +4021 3163113; e-mail: [email protected]

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Introduction The nitrates and nitrites are naturally found in the water as part of the nitrogen cycle in nature. Nitrogen is essential for all lifestyles because it is included in the structure of proteins and nucleic acids.1 Anthropogenic activities, such as human interventions help exceeding the maximum allowable concentrations of nitrogen (nitrate/nitrite) in water, air, soil and food.2 High concentrations of nitrate and nitrite in drinking water can be dangerous to health, causing methaemoglobinemia in infants (blue baby syndrome) and determining the occurrence of nitrosoamines in the digestive tract, with carcinogenicity.3,4

A number of methods for the determination of NO2- and NO3- ions were proposed to date: titrimetric methods [5], spectrophotometric methods,6-12 liquid chromatography,13,14 and electroanalytical methods.15,16 Table 1 shown the best limits of determination reported until now in the literature.9, 17-30 The demand for rapid on-site analysis of low concentrations of hazardous substances in water samples, has increased in order to prevent their accumulation in water and reaching of maximum admissible concentrations: 10mg/L for nitrate, and 1mg/L for nitrite in drinking water.31

Stochastic sensors are the only electrochemical sensors capable of performing a reliable qualitatively and quantitative analysis of small amounts of analytes in complex samples, such as water sample, without performing any processing of the water sample (this is an advantage vs the chromatographic methods).32 This paper proposed two stochastic microsensors based on graphene nanopowder and reduced graphene oxide pastes modified with protoporphyine IX for the simultaneous recognition and quantification of nitrate and nitrite in water. 2


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Experimental Materials and reagents Reduced graphene oxide powder; graphene nanopowder and protoporphyrin IX were purchased from Sigma-Aldrich (Vienna, Austria). Sodium nitrite and sodium nitrate were purchased from Merck (Darmstadt, Germany) and paraffin oil from Fluka (Buchs, Sweden).

The deionized water used to prepare the solutions was obtained using a Millipore Direct-Q 3 system (Mosheim, France). Standard NO2- and NO3- solutions were prepared in a concentration range between 1x10-3mol/L and 1x10-15 mol/L using the sequential dilution method.

Apparatus and methods All measurements were performed with an AUTOLAB/PGSTAT 302N (Utretcht, Netherlands) connected to a computer with a GPES software. An electrochemical cell based on a three electrodes system was employed. Ag/AgCl (0.1 mol L-1 KCl) electrode served as the reference electrode during measurements and a platinum wire as a counter electrode. Design of stochastic microsensors based on graphene powders The graphene nanopowder (NG) and reduced graphene oxide (rGO) powder were mixed with parrafin oil to form homogenous pastes. A protoporphyrin IX (PIX) of 10-3mol/L were added to each paste (in a ratio of 1:1 (v/w)) to form two modified graphene pastes. Each paste was placed into a plastic tube with an internal diameter of 125µm. The electric contact was obtained by inserting a silver wire into the graphene paste. Before each measurement the surface of the microsensor was cleaned with deionized water. When not in use, the stochastic microsensors 3



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were kept in the fridge at 4-8oC. Stochastic mode Stochastic mode is based on measuring the signatures (toff values) of nitrate and nitrite and the associated ton values for the recorded diagrams (Fig. 1), using the chronoamperometric technique. The measurements were carried out at a constant potential of 125 mV. The qualitative analysis of nitrite and nitrate was based on their signatures identified in the diagrams. The ton values were used for the determination of the quantitative parameter of the stochastic microsensors; 1/ton was graphically plotted against the concentrations of NO2- or NO3- (1/ton = a + bxConcanion) for each proposed microsensor. The unknown concentrations of nitrate and nitrite were determined using the calibration equation of each microsensor. All measurements were performed at room temperature. Samples Water samples were collected from various water sources such as: underground sources, freshwater springs, domestic waste water sources, geothermal waste water sources and surface river water sources. All water samples were collected and analysed using ISO certified methods for de assay of nitrate and nitrite, by the National Institute of Research and Development for Industrial Ecology, in Bucharest.

Results and discussions Response characteristics of graphene based stochastic microsensors The response characteristics of the proposed stochastic microsensors were determined using the stochastic mode. The response of the microsensors can be explained using channel conductivity; 4


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the process occurs in two steps: in the 1st step, the anion blocks the entrance in the pore for a period of time, which is called the signature of the anion (toff value); and in the 2nd step bounding and redox processes were taking part inside the channel, this step being characterized by the ton values. The response characteristics of the stochastic microsensors designed for the assay of nitrate and nitrite are shown in Table 2. For the simultaneous analysis of nitrite and nitrate, the microsensor based on PIX/rGO paste reached the lowest limit of determination (1nmol/L for nitrite and 1nmol/L for nitrate) and showed the highest sensitivity. The linear concentration ranges were wide enough for both anions to be able to be used for drinking water and waste water analysis. Also, this microsensor had better limits of determination for nitrite and nitrate, than those reported to date in the literature (Table 1). The signatures of nitrite and nitrate are different for the same microsensor proving that the proposed microsensors can be used for the simultaneous assay of nitrate and nitrite in water samples. The selectivity of the proposed microsensors was checked versus possible interfering species such as heavy metals (Cu, Cd, Hg, Pb), sulphate ions, and phenols; the heavy metals and phenols presenting different signatures when the stochastic microsensors based on graphene materials and PIX were used, proving that the microsensors are selective. The reproducibility of the construction as well as of the results for the stochastic microsensors were tested by construction of 3 microsensors and measuring their response characteristics daily for 10 days. The results obtained proved that the relative standard deviation (%) values obtained by comparing the slopes obtained for the 3 microsensors every day, as well as for the same

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microsensor when the slope was determined for 10 days, were less than 0.80%, proving that the construction is reliable, and that the sensor can be reliable used for at least 10 days. Analytical applications The main application of the proposed stochastic microsensors was fast screening of water samples for nitrite and nitrate. The signatures of nitrite and nitrate made possible their fast identification in the diagrams (toff values in Figure 1). Quantitative measurements were performed using the ton values obtained from nitrite and nitrate in the diagrams (Figure 1); the value of ton was alaways read immediately after the toff value defining the analyte found accordingly with the values from Table 2.

The proposed stochastic microsensors were used for the screening of 28 water samples for nitrate and nitrite. The samples were analysed with the stochastic microsensors as collected from the water sources. After the diagrams were obtained, the nitrate and nitrite were identified accordingly with their signatures (Figure 1, Table 2), and the ton value was read (Figure 1) and used to determine the concentrations of nitrates and nitrites in water samples. Certified results for the assay of nitrate and nitrite in water samples were obtained from the National Institute of Research and Development for Industrial Ecology, in Bucharest. The ISO method used were spectrophotometric methods of analysis: SR ISO 7890-3:2000 for nitrates and SR EN 26777:2002 for nitrites. The results obtained using the stochastic microsensors and the ISO standard methods were compared (Table 3). There was a good correlation between the new and standard methods used for the assay of nitrites and nitrates in water samples. The advantages of the new stochastic method were: no sample preparation was needed before the measurements; colored water can also be screened; the same microsensor can analyse both ions nitrate and 6


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nitrite with high reliability; screening tests can be performed in a continuous mode due to high stability and reliability of the proposed microsensors, the method being able to provide at any time in real time the results and warn the authorities about increased levels of concentration which may create problems especially for drinking water.

Conclusions Two stochastic microsensors based on graphene nanopowder and reduced graphene oxide modified with protoporphyrin IX, were used for pattern recognition of nitrite and nitrate in water samples. The proposed microsensors proved to be reliable for the simultaneous analysis of nitrite and nitrate due to high sensitivities and low limits of determination (better than those reported to date), and also the results obtained were in very good correlation with the ones obtained using the ISO standard methods.

Acknowledgements The authors gratefully acknowledge the Romanian National Authority for Scientific Research, UEFISCDI for financial support, under grants PN-III-P2-2.1-PED-2016-0181 and PN-III-P4-IDPCE-2016-0050, and the INCD-ECOIND and Roxana-Luisa Popescu-Mandoc for providing the water samples with certified results for nitrates and nitrites.

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Table 1. Methods proposed to date for the assay of nitrite and nitrate. Method

Visible

Limit of determination (µmol/L) Nitrite

Reference

0.32

[17]

0.11

[18] 11



Chemiluminescence Fluorescence Spectrophotometric Electrochemical

Page 12 of 19

0.25

[19]

0.22

[20]

0.17

[9]

0.02

[21]

0.20

[22]

0.43

[23]

Nitrate UV-VIS

Visible

Electrochemical

29.00

[24]

5.00

[25]

20.00

[26]

50.00

[27]

2.80

[28]

10.00

[29]

25.00

[30]

12


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Table 2. Response characteristics of stochastic microsensors used for the assay of nitrites and nitrates.

Microsensor based on

Signature of the analyte toff (s)

Equation of calibration* and correlation coefficient (r)

Linear concentration range (mol/L)

Sensitivity (s-1 mol/ L)

Limit of determination (µmol/L)

1.00 x 10-71.00 x 10-3

1.89x102

0.1

1.00 x 10-91.00 x 10-3

1.99x104

0.001

1.00 x 10 -81.00 x 10-3

3.49x10

0.01

1.00 x 10 -91.00 x 10-3

5.70x10

0.001

Nitrate PIX/NG

2.1

1/ton=0.03+1.89x102 x C r = 0.9987

PIX/rGO

2.1

1/ton=0.05+1.99x104 x C r = 0.9979 Nitrite

PIX/NG

0.9

1/ton=0.03+3.49x10 x C r = 0.9930

1/ton=0.03+5.70x10 x C PIX/rGO 1.4 r = 0.9990 *C is the concentration of nitrite = mol/L

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Table 3. Pattern recognition of both nitrites and nitrates in water samples.

Nr. crt.

1

2

3

4

5

6

7

Methods used

NO3- (mg/L)

NO2- (mg/L)

St. method

10.27

0.13

PIX/NG

10.24±0.04

0.17±0.02

PIX/r-GO

9.86±0.07

0.15±0.03

St. method

1.32

0.20

PIX/NG

1.59±0.02

0.18±0.04

PIX/r-GO

1.16±0.08

0.19±0.02

St. method

9.39

0.52

PIX/NG

9.67±0.03

0.50±0.02

PIX/r-GO

9.97±0.05

0.60±0.04

St. method

3.55

0.43

PIX/NG

3.21±0.02

0.52±0.06

PIX/r-GO

3.20±0.05

0.40±0.02

St. method

0.17

0.09

PIX/NG

0.14±0.03

0.08±0.01

PIX/r-GO

0.17±0.02

0.07±0.01

St. method

0.13

0.19

PIX/NG

0.12±0.05

0.19±0.02

PIX/r-GO

0.15±0.03

0.18±0.01

St. method

4.34

0.04

14


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8

9

10

11

12

13

PIX/NG

4.90±0.05

0.06±0.01

PIX/r-GO

4.82±0.03

0.05±0.01

St. method

6.16

0.10

PIX/NG

6.38±0.08

0.12±0.01

PIX/r-GO

6.21±0.05

0.13±0.03

St. method

0.95

0.07

PIX/NG

1.01±0.04

0.06±0.01

PIX/r-GO

0.94±0.04

0.06±0.01

St. method

9.79

0.08

PIX/NG

9.70±0.07

0.08±0.02

PIX/r-GO

9.18±0.03

0.09±0.01

St. method

2.43

3.95

PIX/NG

2.09±0.05

3.55±0.04

PIX/r-GO

2.40±0.03

3.96±0.02

St. method

28.12

0.003

PIX/NG

28.00±0.06

0.003±0.001

PIX/r-GO

28.70±0.07

0.004±0.001

St. method

16.82

0.010

PIX/NG

15.68±0.03

0.012±0.001

PIX/r-GO

16.20±0.02

0.009±0.002

St. method

20.23

0.062

PIX/NG

20.68±0.07

0.070±0.005

14

15



15

16

17

18

19

20

21

Page 16 of 19

PIX/r-GO

20.71±0.05

0.062±0.03

St. method

12.11

0.014

PIX/NG

12.70±0.04

0.017±0.003

PIX/r-GO

12.71±0.05

0.012±0.002

St. method

40.48

0.003

PIX/NG

40.24±0.08

0.002±0.001

PIX/r-GO

39.87±0.07

0.003±0.001

St. method

0.21

0.003

PIX/NG

0.28±0.02

0.004±0.001

PIX/r-GO

0.20±0.03

0.004±0.001

St. method

1.66

0.006

PIX/NG

1.60±0.02

0.007±0.002

PIX/r-GO

1.46±0.03

0.005±0.001

St. method

0.41

0.019

PIX/NG

0.42±0.02

0.017±0.002

PIX/r-GO

0.43±0.05

0.018±0.003

St. method

0.12

0.011

PIX/NG

0.14±0.04

0.010±0.002

PIX/r-GO

0.14±0.03

0.009±0.001

St. method

0.49

0.004

PIX/NG

0.46±0.07

0.003±0.001

PIX/r-GO

0.50±0.02

0.004±0.001

16


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22

23

24

25

26

27

28

St. method

2.70

0.28

PIX/NG

2.52±0.05

0.29±0.02

PIX/r-GO

2.80±0.06

0.27±0.03

St. method

1.67

15.80

PIX/NG

1.25±0.03

15.54±0.03

PIX/r-GO

1.62±0.02

15.24±0.04

St. method

1.88

0.034

PIX/NG

1.61±0.04

0.037±0.003

PIX/r-GO

1.85±0.03

0.031±0.002

St. method

1.66

0.004

PIX/NG

1.68±0.05

0.004±0.001

PIX/r-GO

1.62±0.07

0.003±0.001

St. method

0.26

0.09

PIX/NG

0.21±0.05

0.08±0.01

PIX/r-GO

0.22±0.03

0.10±0.02

St. method

15.09

0.14

PIX/NG

15.50±0.04

0.12±0.03

PIX/r-GO

15.14±0.03

0.13±0.05

St. method

21.22

0.04

PIX/NG

22.05±0.04

0.03±0.01

PIX/r-GO

20.90±0.03

0.05±0.01

*All values are the average of 10 determinations. 17



Page 18 of 19

(a)

(b) Figure 1. Pattern recognition of nitrites and nitrates in water samples using stochastic sensors based on (a) graphene nanopowder, and (b) reduced graphene oxide modified with protoporphyrin IX.

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Molecular Recognition of Nitrites and Nitrates in ... - ACS Publications

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