(PDF) Nanostructured and Selective Filter to Improve Detection of

Subscriber access provided by SUNY DOWNSTATE

Article

Nanostructured and selective filter to improve detection of arsenic on surface plasmon nanosensors Yulieth c Reyes, Luis Emerson Coy, Luis Yate, Stefan Jurga, and Edgar E González ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.6b00211 • Publication Date (Web): 25 Apr 2016 Downloaded from http://pubs.acs.org on April 26, 2016

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

ACS Sensors is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

Nanostructured and selective filter to improve detection of arsenic on surface plasmon nanosensors Yulieth C. Reyes1, Luis Emerson Coy2, Luis Yate3, Stefan Jurga2,4 and Edgar E. González1* 1

Pontificia Universidad Javeriana, Faculty of Engineering, Instituto Geofísico, Bogotá, 110231, Colombia

2

NanoBioMedical Centre, Adam Mickiewicz University, 61614 Poznan, Poland

3

CIC biomaGUNE, Paseo Miramón 182, 20009, San Sebastián, Spain

4

Department of Macromolecular Physics, Adam Mickiewicz University, 85 Umultowska str., 61-614 Poznan,

Poland Corresponding Author: [email protected]

ABSTRACT The development of a pretreatment system to assist surface plasmon sensor-based measurement of arsenic in water is described. The system proposed addresses important issues, regarding the reliable in-situ detection of arsenic in water. This system uses a primary filter made of non-activated cotton fibers for particulate matter and chemical retention agents without modifying the arsenic concentration in the water sample. A secondary filter was designed for retention of mercury, lead and other heavy metals retention without alteration of the arsenic concentration in the collected water samples to be sensed. This filter was made with amino-functionalized carbon nanotubes. The results of the operational assessment of this filter show a retention efficiency of 98% for suspended solids, 96% for mercury ions and 2% for arsenic, a remarkable improvement towards the accurate detection and quantification of arsenic in contaminated waters. Key words: Arsenic, nanofilter, nanosensor, surface plasmon resonance, carbon nanotubes. Environmental pollution is one of the most relevant problems to deal with in the twentyfirst century. The increase in concentration of heavy metals and other contaminants, in water for human consumption, have caused high environmental impact. Food security is,

1 ACS Paragon Plus Environment

ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

for example, dramatically affected by the effects of bio-accumulation on fauna and flora due to the presence of contaminants in water and sediments. Experimental processes and strategies to detect and measure contaminants in water for human consumption, especially heavy metals, have gained relevance in research. Their development has been propelled by the urgent necessity of carrying diagnosis tables out to devise plans aiming at mitigation and remediation1-4. Arsenic is a naturally occurring element in the earth’s crust. It is found as cobalt ore as well as combined with other elements such as sulfur and metals (iron, manganese, silver, tin and nickel) in the surface of rocks. It is introduced naturally into water bodies or anthropogenically, especially by coal combustion; insecticides and fertilizers use; industrial activity; mining; etc

5-7

. Arsenic may remain in the natural ecosystems for a long time. It

may also be present in the soil, ground water and host lithologies8. The above phenomenon represents a serious contamination problem in drinking water resources, which gives rise to severe consequences for public health8-10. The World Health Organization (WHO), as well as other regulatory entities, has set 10 ppb as the allowable level of arsenic in drinking water. Detecting arsenic at such level is a challenge in the development of portable and economic high-sensitivity detection systems. In this context, the science and the technology of nanomaterials may contribute to the measurement of arsenic given the measuring scales needed to quantify, measure, monitor or even remediate 11-13. For detecting heavy metals, principally arsenic, spectrometric, electroanalytical and chromatographic methods stand out among the conventional ones used in chemical analysis of water samples. These methods have some limitations in terms of their cost, portability, measurement time, sample pretreatment, etc. Besides, they imply to run some contamination and alteration risks due to the necessity of implementing protocols of packaging, conservation and transport of the sample from the place where it is collected to the laboratory. These operational and cost constraints trigger the development of economic, portable and sensitive systems to be used in-situ.


Page 2 of 22

Page 3 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

Surface plasmon resonance (SPR)-based sensors have shown the highest efficiency, sensitivity and precision in detecting and quantifying chemical and biological agents14-21. In nanoengineering, they are a widely accepted tool for characterization of interfaces; thin films and kinetic surface processes (specially hybridization reactions)22. They have also been successfully used for detection of contaminants, micotoxins, pesticides and allergenics in food; measurement of physical quantities; detection and biodetection of chemical products22-24. The use of surface plasmon-based sensors has, however, some constraints for detection of heavy metals ions in water from in-situ collected samples. The sensor operability depends on the changes of the refractive index; hence it could be altered by microorganisms, organic compounds, inorganic colloidal compounds, and chemical agents in the water sample to be sensed. These agents modify the dielectric function at the interface of the metallic substrate, and produce changes in the output signal so that the measurement of the analyte is prevented. In addition, the presence of other heavy metals, such as mercury and lead, in the collected water samples causes interference problems in the measurement. This is because the type of functionalization used in the sensors surfaces enables them to capture elements such as: mercury and lead, and thus, measurements not linked to the analyte itself, arsenic, are erroneously detected. As a solution to this problem, it is suggested to perform a selective pretreatment in the collected sample to eliminate micro and nanoparticulated material along with the heavy metal ions (mercury and lead), without affecting the arsenic concentration. A few papers on the detection and quantification of elements by SPR from in-situ collected water refer to a pretreatment of samples18-25. These studies have reported problems in the detection of heavy metal ions, as a result of the impurities in the nanostructured surface at the moment of contact with the sample. It was then concluded that sample pretreatment is essential to minimize the interference in the accurate measurement of the analyte concentration by SPR. There are no literature reports on the implementation or performance of a pretreatment system for SPR sensors. In this article, a system capable of filtering heavily contaminated


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

Page 4 of 22

waters for SPR based sensors is presented. The nanostructures filter proposed is tested in heavily polluted waters and its performance described. MATERIALS AND METHODS Sample collection and characterization It is important to characterize the type of environments to which a typical SPR sensor is exposed during measurements. Therefore, it requires identifying recollection places that are representative of those places where the SPR sensor will be used for detecting contaminants in water. Three collecting-sample places along the Bogota River Basin were selected (Fig 1).

1

2 3

Figure 1. pt. 1: Hydrometeorological station Puente la Virgen, pt.2. station Florida Park, , pt. 3: Hydrometeorological station Wetland Jaboque Source:Open Streen Maps ( http://www.openstreetmap.org/)

Point 1. (Puente) Puente La Virgen station, located in the Suba-Cota highway at latitude 4o 48´ 3.8” N, longitude 74o5´ 57.8” W and 2565m altitude (this station is the first point in the Bogota River Medium Basin).


Page 5 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

Point 2. (Parque) La Florida Park , in Engativa district, located at latitude 4o 44´ 2” N and longitude 74o8´ 36.8” W Point 3. (Humedal) Puente Humedal Jaboque station, located in La Florida park in Engativa district, among El Dorado airport, the Juan Amarillo River and the Medellin highway (this wetland is in the Salitre Basin). To select the collecting-sample places the following aspects were taking into account: i) the importance of the River Bogota for the country and its impact on agriculture given its pollution levels; ii) the relevance that these places have in order to evaluate the work environments for the surface plasmon sensors; and iii) the possibility implementing the pretreatment system to produce maps showing the pollution caused by arsenic or other metals (mercury and lead) of the River Bogota, using SPR sensors. In order to confirm the quantity of suspended solids analysis,

and arsenic concentration,

three samples were taken at pt.1, three at pt.2, and one at pt.3. Measurement of arsenic was crucial in order to carry out the necessary studies and for the further designing and constructing of the pretreatment system. Suspended solids analysis and measurement of arsenic were carried out by ANTEK S.A. laboratories, with receipt N° 30184. Standard Methods for the Examination of Water and Wastewater APHA/AWWA/WEF were used for the measurement of parameters in the laboratory. Electro thermal atomic absorption spectrometry (ETAAS) was the analytical technique used for detection of arsenic. Gravimetric drying at 103 – 105 °C (Table I) was the analytical technique used for measurement of the suspended solids parameter; it was carried out with the collaboration of the IDEAM accreditation by the resolution N° 0463 of April 09, 2013. Table I. Analytical technique employed by ANTEK SA and method for measuring parameters.

Description Suspended solids Arsenic

Analytical Technique Drying at (103-105)oC ETAAS

Method SM2540 SM3113B,SM3030

Evaluation of the effect of the water samples on the sensing surface


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

The characterization of the sensing surface (which is part of surface plasmon resonance sensor), to determine the effects caused by particulate matter and other chemical agents on it, was made with spectrophotometric techniques. For this characterization, it was used a Shimadzu UV-Visible Spectrophotometer-UV 2600 with Integrating Sphere Attachment for transmittance measurement in thin films. To carry out the experimental study of the effect an in-situ collected water sample has on the sensing surface, a flow cell was designed and constructed under the following specifications: two square cells (2.2 cm each side and 1 mm in depth) were carved in an acrylic plate (9 cm in length, 4.5 cm in width and 2 mm in depth) to work with two samples simultaneously. Each cell was covered with a glass foil and provided with access holes. A gold film was placed in the corresponding cell and exposed to a flow of collected water. Discharge and duration of the flow were the parameters controlled by setting a syringe pump, coupled to the system, as shown in Fig. 2. There was no difference in placing the sensing surface in gravitational field direction, downwards, or in the opposite direction, upwards.

Figure 2. Left: Experimental setup to evaluate the effects of exposure to the sensor gold surface to water samples taken in situ. Right: Structure of primary filter

Filter configuration The filter for retention of particulate matter (primary filter) is, in its first stage, a hollow polypropylene cylinder with holes on its surface for water flowing. The filter was covered with a 3.5 cm in length and 0.8 cm in width stainless steel mesh for retention of bigger particulate matter. In a second stage, the filter is a hollow polypropylene cylinder filled with cotton fibers as absorbent of micro and nanoparticles and chemical agents (Fig. 2). 6 ACS Paragon Plus Environment

Page 6 of 22

Page 7 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

This material offers the following advantages: i)high rate retention of solids in collected water samples; ii) capacity of being functionalized for selective retention of heavy metals26; iii) no retention of arsenic (when the cotton fibers are not activated); iv )low cost; v) easy operation; and vi) degradability. Activated carbon is widely used in water purification and filter designing, but its use does not accomplish the purposes of this work. Despite the high specific surface area of the activated carbon, given its microporous morphology, obstructions of the micropores during absorption is a limitation. Because of this constraint, the pretreatment system lifetime can be drastically reduced under the operation conditions of this work. Besides, activated carbon has some limitations in its selectivity to retain certain ions21,27. The use of carbon nanotubes has been a step forward in the processes of retention and adsorption of heavy metals and other chemical agents. Carbon nanotubes allow the design of filters given their capacity to eliminate numerous chemical agents (heavy metals, bacterial contaminants, etc.), their high specific surface areas, and their physical and chemical stability for extended periods of time use makes them ideal for sensing applications. When inserted in matrices that prevent them from moving in the environment, nanotubes are a remarkable alternative for configuring and implementing water pretreatment and water purification systems. Nevertheless, carbon nanotubes are considered, currently, high-risk material for the living beings and the environment; this consideration limits its use. It is vital to use them carefully and responsibly, following the manipulation safety and operability protocols of the containing system. As well as the activated carbon, carbon nanotubes have high specific surface area for adsorption processes. As long as these processes occur on the surface, no obstructions limit the access to the available places for pollutants capture; therefore, activated carbon and carbon nanotubes are appropriate in lifetime terms. Multi-walled carbon nanotubes were the chosen material to configure the barrier in the secondary filter, aimed at retaining the agents abovementioned. Despite the small quantities of carbon nanotubes synthesized for the secondary filter construction, they were


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

manipulated and stored under optimal security standards, and following the ASTM E253507 standards.

Carbon nanotubes were synthesized by the microwave-based selective heating method. In the synthesis, pure graphite was used as precursor material, silver nitrate as catalyst and a microwave oven (1500 W in power and 2.4 MHz in operating frequency) as source of energy for carbon volatilization27. Multi-walled carbon nanotubes (MWCNTs) from 50 nm to 100 nm in diameter were obtained. The nanotubes used in the configuring of the filter were 60 ± 9nm in diameter (Fig. 3a). When using catalyst in the synthesis, open nanotubes are obtained, making the access to the interior easier and, therefore, incrementing the number of available places for adsorption of heavy metal ions. To assess the efficiency of the filter in terms of its selectivity of heavy metal ions, it is crucial to have a carbon nanotubes sample pure enough to correlate the observed performances with the carbon nanotubes without the noise figures caused by carbonaceous products. The obtained MWCNTs contained carbonaceous products, such as amorphous carbon, fullerenes and graphitic nanoparticles. Thus, the carpets were purified after synthesis.

The purification of the carbon nanotubes was carried out by oxidative processes, specifically by a process using nitric acid and hydrochloric acid in conjunction with mechanical processes of centrifugation. The use of acid nitric provides the surface of the nanotubes with carboxyl groups (COOH); these contribute to improve the adsorption of mercury and other heavy metals. Carboxyl groups also increase the ion-exchange capacity and make the carbon nanotubes acquire a hydrophilic character. To have a completely dispersed sample that allows the construction of the filter, it was used the nonionic surfactant Triton X-100 in a ratio of 0.4% volume of nanotubes dissolved in 10 mL of deionized water. After sonicating the sample, a stable suspension was obtained, which was usable in the construction of the filter.


Page 8 of 22

Page 9 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

In order remove the liquid out of the suspension a vacuum filtration method of was used 28. In this procedure, a PES (polyether sulfone) membrane, 0.20 µm in pore size and 150 µm in thickness (PES 029025, Sterlitech Corporation), was used in a Buchner funnel. After the vacuum filtration, the solute was rinsed with isopropyl alcohol to remove the surfactant, and the circular film of nanotubes used to configure the secondary filter (386µm in thickness) was carefully removed. The resulting material was cut in a rectangular shape (4 cm x 1.88 cm) and placed into the detection system). A film of nanotubes, with mean size of 60 nm in diameter, was obtained and used in the filter construction. This film was cohesive enough to have a high mechanical stability when installed and used in the pretreatment system. In constructing the secondary filter, the film of carbon nanotubes was set between two layers of high-density propylene filter paper to avoid the movement of the carbon nanotubes out of the filter, and strengthen the barrier aimed at impeding the flow of waste material in the water into the flow cell. The secondary filter was rolled around a hollow cylinder with perforations on its surface, similar to the one used in the filter using cotton Filter architecture Fig. 3b shows the architecture of the pretreatment system. It is a primary filter followed by a secondary filter, a micropump that produces the flow of the in-situ collected water, and the connections caps.


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

Figure 3. a) Image showing the morphology of the purified MWCNTs obtained by scanning electron microscopy and their average diameter. b) shows a general scheme of pretreatment system with the location of the first and secondary filters, cylindrical support and nanotube film are shown.

Surface Plasmon Resonance Measurements The montage used to assess the feasibility of the filter, followed the Kretschmann configuration13-15, shown in Fig.4. The set up used a EK2000 control unit (Thorlabs) with a constant current control of a laser diode of 0-100mA and a tolerance factor of 0.1%. The photodetector was set between 20-125 with a bandwidth of 3 dB and 10kHz. The tension range was of 8-12V DC with a source limit of 130 mA. The laser diode used is a L808P10, wavelength λ = 808 ± 7nm, (Thorlabs) with a power of 10mW at 25OC. Additionally, the prism used was made of BK7 glass with a refraction index η = 1,51 ± 0,01. The prism is optically coupled to the system by immersion oil, with a refraction index η = 1,51 ± 0,01 and 1.25 mm of thickness. The gold thin film resides on top of the prism. Gold thin film Au(111) textured of 50 nm in thickness and 0.4 nm of roughness was deposited on commercial corning glass by sputtering method at room temperature using a adhesive Ti 10 ACS Paragon Plus Environment

Page 10 of 22

Page 11 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

layer with 5 nm thickness. The gold film was functionalized with a monolayer of dithiothreitol (DDT), following a reported protocol31.

Finally, the photodetector used

consisted in four cells with a signal range of 0-0.3V, bandwidth of 250kHz and amplification constant of k=10.000 14-15.

Figure 4. Surface Plasmon Resonance set up used to test the quality of the pretreatment system

RESULTS AND DISCUSSION The quantity of arsenic present in the samples taken at the collection points was below the recommended limit set by environmental authorities. Fig. 5 shows the quantity of suspended solid particles (SSP) and arsenic (As).


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

Figure 5. a) Concentration of suspended solids and b) arsenic in water samples taken at selected collection points.

We chose the collecting-sample place 3 (pt. 3 Humedal Jaboque) for the assessment of the pretreatment system because, according to the results, it presented the highest quantity of suspended solids, which were even higher than the recommended limit (600 mg/L). Transmittance measurements of the gold sensing surface allowed establishing the deposition of particulate matter and the adhesion of other agents in the in-situ collected water samples. Fig. S1 shows the transmittance curves for the glass substrate coated with the gold film that contained the sensing surface for samples in pt. 2. Curves were recordedfor a constant flow of 0.2 ml/s and at times (t) of 0, 5, 15, 25 and 50 minutes. At t = 0, which corresponds to the gold surface before being exposed to the water flow, the highest transmittance value (lowest absorbance) was recorded at a wavelength of 508 nm. At wavelengths near the UV and NIR spectrum the transmittance of the gold foil film dropped dramatically. This means that the gold foil film absorbs radiation efficiently at 12 ACS Paragon Plus Environment

Page 12 of 22

Page 13 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

those ranges of the electromagnetic spectrum. At t = 5, the highest peak for transmittance values was also recorded at a wavelength of 508 nm; however, it slumped from 1363 to 652 nm. This change represents a 48% transmittance loss (considerable absorbance increment) and points out the effects of untreated water samples on the sensing surface due to the chemical agents and particulate matter in it. The inset in Fig. S1a shows an exponential decay of the transmittance as the time at which the sensing surface is exposed to the water sample increases. As time increases, the sorption of chemical agents and deposition of particulate matter decreases drastically. A water sample of 500 ml collected in pt. 2 was used to assess the filter of cotton fibers. Arsenic was added to the sample in a ratio of 1ppm to determine if retention is performed once the sample has gone through it results are shown in Fig S2 These results support the selection of cotton fibbers for the construction of the primary filter since the 2% arsenic retention and the 98.8% solids retention. For mercury, about 22% retention is obtained by using the primary filter. With the secondary filter manufactured with carbon nanotubes functionalized with COOH groups only from the purification treatment as noted above, concentration measurements of arsenic, mercury and lead with

and without the filter

are

shown in Fig

6. These tests are performed with a flow of 2 mL/min for a time of 5 min (This is the minimum time has been identified for the sensor can measure). According to these results, arsenic maintains the concentration while mercury and lead reduce their concentration by approximately 50%, indicating that carbon nanotubes functionalized with COOH are not enough active to fully retain the mercury that enters the system. Thus, a further functionalization of the MWCNTs was performed.


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

Page 14 of 22

Figure 6. Concentrations of As, Hg and Pb before and after using the secondary filter. The measurements were made with EAAE.

As it has been reported, the carbon nanotubes have a high affinity for adsorption of mercury Hg (II) ions29. The adsorption capacity of carbon nanotubes is 440% greater than that of activated carbon. The Hg (II) can be found as mercury cation Hg2+ in aqueous solutions with pH below 2. By increasing the pH of the solvent, it is hydrolyzed to form HgOH+ until precipitate in mercury hydroxide Hg(OH)2 and finally spontaneously evolve into HgO (s). The adsorption capacity of Hg (II) dramatically depends on the pH of collected water as it affects the cleavage sites of nanotubes and precipitation and complexation of metal ions. At acidic pH, the surface can have net positive charge restricting the adsorption of positive ions of mercury. For alkaline pH, the surface is expected to have a net negative charge, which facilitates adsorption of positive ions of mercury. Thus, adsorption of Hg (II) increases with increasing pH to a maximum value near neutral and decreases as the pH is increased to a basic value. As it has been reported30 the optimal pH for removal of Hg with double-wall carbon nanotubes is close to the neutral value, i.e. between 6.5 and 7.5. The pH measurement of the water samples used, are close at 6.8, which favors the adsorption of mercury with carbon nanotubes. To improve the rate of adsorption of mercury in the secondary filter maintaining selectivity (unabsorbed As (III)),

carbon nanotubes were functionalized with ethylenediamine.

Ethylenediamine is an organic compound that dissolves in water to form a solution with basic pH. The functionalization was carried out following the protocol reported in 7). 14 ACS Paragon Plus Environment

29

(Fig.

Page 15 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

Figure 7. Oxidation and amino-functionalization of carbon nanotubes for sorption Hg2+

Filters designed with amino-functionalized nanotubes exhibit effective mercury sorption without retention of arsenic.Mercury retention obtained with this type of functionalization reaches values close to 96%. In the secondary filter, carbon nanotubes-made, total arsenic retention remains below 1,26 %; mercury retention increases to 55% and lead retention to 48%. An amino-functionalized nanotubes filter was used to improve mercury retention and allow only arsenic ions flow to the sensor cell. To verify the efficiency of this type of functionalization for mercury retention, an absorbance measurement of the gold surface was made with dithiothreitol under conditions of exposure and no exposure to filtered water (1000 ppb mercury before entering the filter). This method for detection of mercury using absorbance has been used to measure arsenic concentrations near 1ppb31. It may also be implemented to measure mercury with the same levels of sensitivity. The curve in Fig. S3 shows no change in the absorbance. This means the concentration of mercury in the filtered water sample is lower than 1ppb. Besides, it is verified that the sample did not absorb any particulate matter or other agents that may interfere in the absorbance change. In the same way that for mercury, selectivity for lead may be achieved as a water sample pretreated enough is obtained to make measurements using surface plasmon sensors. Finally, SPR measurements were performed using the proposed nanostructured filter coupled with the architecture described before in this article. It is important to determine the accuracy of the detection system used. Therefore, a mixture of 10 mL distilled water (19*MΩ*cm) with a of 5ppb As(III) was prepared. Fig. 8a shows the angular dependency of both the pristine surface, resonance angle 57O, and the exposed to the mixture with and angular shift of 0,5O after 5 minutes of recirculating flow of 2mL/min. This displacement is


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

well within the sensibility limits of our previously reported sensor14 and shows the accuracy of the system. Having determined the optimal resolution of the system, water from point 3 with an arsenic concentration 0.66 ppb was used, the SPM response was evaluated after the first filter and after both filters. Figure 8b and c show the results from such measurements respectively.


Page 16 of 22

Page 17 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

Figure 8. Plots of photodetector voltage vs angle of incidence for a) pure surface, straight line, and after exposure of 5pbb (As) control water, dashed line. b) Pure surface, straight and exposed to 0.6 pbb (As) contaminated water after first filter only. c) Pure surface, straight line, and after treatment to with 0.6 pbb (As) contaminated water using both filters, dashed.


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

The results clearly show that by only using the primary filter, on a 0.6 pbb contaminated water, the SPR signal has a shift 6 times bigger than that observed for a 5pbb controlled detection.

Remarkably enough the use of both filters results in much more accurate

detection of the As(III) concentration. Fig. 8c shows a displacement of 0.2O on the resonant angle and a change of voltage equivalent to 1:0.08. These results, conclusively show that the nanostructured filter provides a clean enough water sample to successfully detect As(III) in water with an total error of 8% from the nominal concentration. CONCLUSIONS The development of the pretreatment system required two filters that fulfill specific functions to allow the operation of the surface plasmon sensors in on-field measurements. The primary filter retained particulate matter and chemical agents; however, the quality of this retention was not enough to avoid the effect of interference factors on the sensing surface. The use of cotton fibers to construct the primary filter showed satisfactory results in terms of retention of particulate matter: 98% for suspended solids and chemical agents, such as lead and mercury ions. Nonetheless, the non-activated cotton fibers allow the flow of arsenic ions; it is not altering the arsenic concentration in the collected water samples, which is one of the most important specifications for the system to accomplish. The secondary filter, constructed with amino-functionalized carbon nanotubes, retains mercury up to 96%, and 2 % of arsenic, thus ensuring that the water sample is completely free of interferences caused by mercury ions at the moment of accessing the sensing surface. The SPR results showed that the pretreatment system allows measurements without a noise factors until values nearly to 5 ppb. These results lead to conclude that the pretreatment system is an efficient method of reducing contaminants and measuring heavily polluted waters without affecting the performance of the sensor and the accuracy of arsenic detection. Finally, with appropriate modifications, the pretreatment system developed can be used to sense other types of heavy metals in water and opens an important field of research and


Page 18 of 22

Page 19 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

development in remediation of water with sustainable systems, efficient, low cost and absence of environmental impact. Supporting Information Available: The following files are available free of charge. Y_R_et_al_ACS_Sensors_Supporting_Information.docx. Containing, Transmittance Spectra(S1), Concentration of suspended solids and Arsenide pre and after cotton filter (S2) and Absorbance Spectra (S3)

ACKNOWLEDGMENTS We would like to thank the Vice-Rectory of Research of the Pontificia Universidad Javeriana for funding the project N° 006288 whose results are in this work. S. Jurga acknowledge the partial financial support from the National Centre for Research and Development under research grant “Nanomaterials and their application to biomedicine”, contract number PBS1/A9/13/2012 REFERENCES [1] Milliman, S. R., Prince, R. Firm incentives to promote technological change in pollution control. Journal of Environmental economics and Management.17(3), 1989, 247-265. [2] Correll, D. L. The Role of Phosphorus in the Eutrophication of Receiving Waters: A Review. Journal of Environment Quality. 27(2), 1998, 261-266. [3] Bartolini, F., Bazzani, G. M., Gallerani, V., Raggi, M., Viaggi, D. The impact of water and agriculture policy scenarios on irrigated farming systems in Italy: An analysis based on farm level multi-attribute linear programming models. Agricultural systems Vol. 93, No. 1, 2004, pp. 90-114. [4]Quintero, L.A., Agudelo, E. A., Quintana Y., Cardona Gallo, S. A., Osorio Arias, A. F. Determinación de indicadores para la calidad de agua, sedimentos y suelos, marinos y costeros en puertos colombianos. Gestión y Ambiente 13(3), 2010, 51-64. [5] Jacks, G., & Bhattacharya, P. “Arsenic contamination in the environment due to the use of CCA-wood preservatives”, Arsenic in Wood Preservatives. Part, 1, 1998, 7-75.


ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

[6] Juillot, F., Ildefonse, P., Morin, G., Calas, G., De Kersabiec, A. M., Benedetti, M. Remobilization of arsenic from buried wastes at an industrial site: mineralogical and geochemical control. Applied Geochemistry.14(8), 1999, 1031-1048. [7] Pacyna, J. M., Pacyna, E. G. Anassessment of global and regional emissions of trace metals to the atmosphere from anthropogenic sources world wide. Environmental Reviews. 9(4), 2001, 269-298. [8] Smedley, P. L., Kinniburgh, D. . Are view of the source, behavior and distribution of arsenic in natural waters. Applied geochemistry. 17(5), 2002, 517-568. [9] Thornton, I. Sources and pathways of arsenic in the geochemical environment: health implications. Environmental Geochemistry and Health Special Pu, 113(1), 1996, 153-161.

[10] Nickson, R., McArthur, J., Burgess, W., Ahmed, K. M., Ravenscroft, P., and Rahman, M. Arsenic poisoning of Bangladesh groundwater. Nature, 1998, 395, 338. [11] Contreras, A. R., García, A., González, E., Casals, E., Puntes, V., Sánchez, A., Font, X., Recillas, S. Potential use of CeO2 , TiO2 and Fe3O4 nanoparticles for the removal of cadmium from water. Desalination and Water Treatment. 41(1-3), 2012, 296-300. [12] Casals, E., González, E., Puntes, V. Inorganic nanoparticles and the environment: Balancing benefits and risks. Comprehensive Analytical Chemistry. 59, 2012, 265-290. [13] Nath, P., Arun, R., & Chanda, N. A Paper based microfluidic device for the detection of arsenic using a gold nanosensor. RSC Adv. 4, 2014, 59558. [14] Salinas, S., Mosquera, N., Yate, L., Coy, E., Yamhure, G., Gonzalez, E., Surface Plasmon Resonance Nanosensor for the Detection of Arsenic in Water [online] Sensors & Transducers. 183, 2014, 97-102, ISSN: 2306-8515. [15] Salinas, S., Mosquera, N., Yate, L., Coy, E., Yamhure, G., Gonzalez, E., Autonomous Nanosensor System for Monitoring and Quantifying Arsenic in Water. NSTINanotech. Vol 3, 2014, 170-173. [16] Jain, C.K., Ali, I. Arsenic: occurrence, toxicity and speciation techniques. Water Research. 34 (17), 2000, 4304-4312 [17] Mulligan, C. N., Yong, R. N., Gibbs, B. F. Remediation technologies for metalcontaminated soils and ground water: an evaluation. Engineering geology. 60(1), 2001, 193-207.


Page 20 of 22

Page 21 of 22

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 51 52 53 54 55 56 57 58 59 60

ACS Sensors

[18] Forzani, E. S., Foley, K., Westerhoff, P., & Tao, N. Detection of arsenic in groundwater using a surface plasmon resonance sensor Sensors and Actuators, B: Chemical, 123(1), 2007, 82-88 [19] Litter, M. I., Armienta, M. A., Far´ıas, S. S. Metodolog´ıas anal´ıticas para la determinación y especiación de arsénico en aguas y suelos. IBEROARSEN,CYTED. Buenos Aires, Spanish. 2009. [20] Hashim, M. A., Mukhopadhyay, S., Sahu, J. N., Sengupta, B. Remediation technologies for heavy metal contaminated groundwater”, Journal of environmental management, 92(10), 2011, 2355-2388. [21] Srivastava, S. K., Verma, R., Gupta, B. D. Surface plasmon resonance based fiber optic sensor for the detection of low water content in ethanol. Sensors and Actuators B:Chemical,153(1),2011, 194-198. [22] Homola, J., Yee, S. S., Gauglitz, G. Surface plasmon resonance sensors: review. Sensors and Actuators B: Chemical. 54(1), 1999, 3-15. [23] Mullett, W. M., Lai, E. P., Yeung, J. M. Surface plasmon resonance-based immunoassays. Methods. 22(1), 2000, 77-91. [24] Frómeta, N. R., Biosensores: Un Acercamiento a La Resonancia del Plasmon Superficial. Revista CENIC. Ciencias Biológicas [online] 2005, 36 Available: ISSN 0253-5688 [25] Yantasee, W., Charnhattakorn, B., Fryxell, G. E., Lin, Y., Timchalk, C., Addleman, R. S. “Detection of Cd, Pb, and Cu in non-pretreated natural waters and urine with thiol functionalized mesoporous silica and Nafion composite electrodes”, Analytica Chimica Acta. 620(1-2), 2008, 55-63. [26] Zang, C., Zhang, D., Xiong, J., Lin, H., Chen, Y. Preparation of a Novel Adsorbent and Heavy Metal Ion Adsorption. Journal of Engineered Fabrics & Fibers (JEFF). 9(4), 2014, 165-170. [27] Ohta, K., Nishizawa, T., Nishiguchi, T., Shimizu, R., Hattori, Y., Inoue, S., Katayama, M., Mizu-uchi, K. and Kono, T. Synthesis of carbon nanotubes by microwave heating: Influence of diameter of catalityc Ni nanoparticles on diameter of CNTs. J. Mater. Chem. A 2, 2014, 2773-2780. [28] Tarleton, S., & Wakeman, R. Solid/liquid separation: principles of industrial filtration. Elsevier. 2005, p 56. [29] Soleimani, M., Afshar, M. G., Sedghi, A. Amino-Functionalization of Multiwall Carbon Nanotubes and Its Use for Solid Phase Extraction of Mercury Ions from Fish 21 ACS Paragon Plus Environment

ACS Sensors

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 51 52 53 54 55 56 57 58 59 60

Sample. ISRN Nanotechnology, vol. 2013, Article ID 674289, 8 pages, 2013.

doi:10.1155/2013/674289 [30] Shadbad, M. J., Mohebbi, A., Soltani, A. Mercury (II) removal from aqueous solutions by adsorption on multi-walled carbon nanotubes. Korean Journal of Chemical Engineering. 28(4), 2011, 1029-1034. [31]. Gao, C., Yu, XY., Xiong, S., Liu, J. and Huang, XJ. Electrochemical detection of arsenic (III) completely free from noble metal: Fe3O4 microspheres-room temperature ionic liquid composite showing better performance than gold. Analytical chemistry 85 (5) 2013, 2673-2680.

for TOC only


Page 22 of 22

(PDF) Nanostructured and Selective Filter to Improve Detection of

Recommend Documents