Arsenic sensing using Al/Fe doped armchair graphene nanoribbons: Theoretical investigations
Introduction
The accessibility to clean water – free from toxicity is a fundamental requirement for sustaining healthy life on earth. World Health Organization has specified the permissible limits of various ions present in drinking water [1]. The concentration above these limits will affect the quality of drinking water. The long-term utilization of such contaminated water can have serious adverse effect on health and quality of life. In current scenario with growing population and looming water-crisis, maintaining the quality of water is of utmost importance. In this regard, developing sensitive and selective sensors becomes crucial for monitoring purposes.
Among various water pollutants, the arsenic contamination of ground water is a severe global problem [2]. Approximately, people in around 21 countries are suffering due to arsenic contamination of ground water. Ground water contains mostly As(III) while As(V) is present in aerobic conditions. Adsorption has been one of the simplest, cheapest and most effective methods of arsenic removal [3]. Among the low-cost adsorbents, iron compounds – oxides, oxyhydroxides and hydroxides are the most efficient followed by activated alumina. In current times, a number of studies have reported good efficiency of 2D materials for the removal of harmful chemicals [[4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15]]. For example, reduced graphene oxide based magnetite nanocomposite synthesized by Chandra et al. could most efficiently remove arsenic species under natural conditions [16]. Similarly, graphene oxide based nickel ferrite composites have been synthesized for arsenic removal from aqueous media [17]. A recent study reported the use of iron-oxide based graphene-nanocomposite with different iron-oxide content for the same purpose [18]. The adsorption of arsenic and arsenous acid on graphene and other adsorbents has also been investigated through DFT studies. Dzade et al. investigated in detail, the adsorption of both arsenic and arsenous acid on unsolvated as well as solvated surfaces of ferrihydrite [19]. Through DFT and molecular dynamics simulations, Arriagada et al. studied the different aspects of arsenous acid adsorption in various orientations over pristine graphene and graphene decorated with aluminium, phosphorous, silicon and iron. They found aluminium doped graphene to be most efficient adsorbent closely followed by iron doped graphene [20]. The efficiency of graphene doped with first row transition metals (Sc–Zn) for the removal of As3+ species has also been explored [21]. Gazzari et al. studied in-depth the bonding character of adsorptive interactions of arsenous acid with different topologies of Fe-doped graphene sheet (FeG). Based on HOMO (Highest Occupied Molecular Orbital)-LUMO (Lowest Unoccupied Molecular Orbital) differences, they speculate FeG to be potential material for designing sensors for arsenic detection [22].
The high specific surface area of graphene not only makes it an excellent adsorbent but also most suitable for sensing. The extended pi-electron cloud is sensitive to changes in chemical environment influencing the conductance of the nanosheet. These changes in conductance are measured in the form of current-voltage characteristics leading to sensing capabilities of graphene [23]. The graphene based electrical solid-state sensors for monitoring water quality can either be field-effect transistors (FETs) or chemiresistive sensors [24]. Graphene due to ambipolar electric field effect is highly sensitive to both n-type and p-type doping analytes [25,26]. A number of graphene based sensors have been fabricated for the determination of pH, detection of heavy metals, organic and biological contaminants in the water, with encouraging results [27]. Another class within graphene based nanomaterials is of graphene nanoribbons (GNRs). GNRs are formed by tailoring the graphene sheet along the edges and are of two types:armchair graphene nanoribbon (AGNR) and zig-zag graphene nanoribbon (ZGNR). Both of these have different properties. ZGNR is always metallic while AGNR can be metallic or semiconducting based on its width [28]. AGNRs are divided into three classes based on number of atoms along the width i.e. 3N, 3N+1 and 3N+2. Among these 3N+2 type is metallic while the other two are semiconductors. The electronic behaviour of GNRs can be modulated by controlling the width, by passivation of edges or by varying the position of defects and dopants [29]. The tuneable electronic properties make GNRs to be promising materials for sensing applications. A recent experimental study reports GNRs to exhibit good sensing properties towards volatile organic compounds [30]. A comparative first-principles study of sensing capabilities of graphene and GNR towards phenol and methanol reports latter to be better [31]. More experimental and theoretical studies have reported GNRs to be good sensors towards NO2, O2 and SO3 gas molecules [32].
Based on encouraging reports of good sensing capabilities of GNRs, we in present study analyze adsorption and in particular, the sensing ability of pristine and doped AGNRs towards arsenous and arsenic acid with an aim to explore the possibility of developing a metal-doped AGNR based electrical sensors for arsenic detection in water. As aluminium and iron compounds are known to be effective adsorbents for arsenic, we have selected aluminium doped AGNR (Al-AGNR) and iron doped AGNR (Fe-AGNR) with width 9 (9-AGNR) for our study. 9-AGNR is a semiconductor and belongs to 3N class of AGNR.
Section snippets
Computational details
The computational studies presented in the paper have been performed using OpenMX (Open source package for Material eXplorer) version 3.8 [33,34]. OpenMX is based on density functional theory (DFT), norm-conserving pseudopotentials, and pseudo-atomic localized basis functions. The exchange-correlation interactions are computed using generalized gradient approximation with Perdew−Burke−Ernzerhof functional (GGA-PBE). For geometry optimization C6.0-s2p2d1, H6.0-s2p1, O6.0-s2p2d1, As9.0-s2p2d2f1,
Results and discussion
The band structures, DOS and optimized geometries of different AGNRs are shown in Fig. 2. The band structure of 9-P-AGNR has a band gap of 0.79 eV as reported in previous studies [40]. The density of state (DOS) studies also verify the semiconducting behaviour of 9-P-AGNR. From here onwards, 9-P-AGNR is referred to as P-AGNR. A symmetric band gap is observed on both sides near the Fermi level. Asymmetric substitutional doping of P-AGNR with Al and Fe introduces a curvature in nanoribbon with
Conclusion
The present study explores electrical sensing capability of graphene based nanomaterials i.e. 9-AGNRs towards arsenic detection. The cheapest solution for arsenic removal is adsorption and the well-known low-cost adsorbents for the purpose are activated alumina and various iron compounds (oxides, oxyhydroxides and hydroxides). The aim of the present study has been to investigate whether the introduction of iron and aluminium in AGNRs make these systems electrically more responsive towards
Author statement
Lovleen Kaur: Methodology, Visualization, Investigation, Validation, Result interpretation, Writing- Original draft preparation.
Suman Mahendia: Discussed the results and commented on the manuscript.
Sangeeta Saini: Conceptualization, Methodology, Supervision, Validation, Result interpretation, Writing- Original draft preparation.
Anurag Srivastava: Discussed the results and commented on the manuscript.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Authors acknowledge Centre for Advanced Research in Material Science, Kurukshetra University, Kurukshetra funded by RUSA 2.0 Grant from MHRD, New-Delhi, India. LK acknowledges CSIR, New Delhi for Junior Research Fellowship.
References (44)
- et al.
Arsenic removal from water/wastewater using adsorbents-A critical review
J. Hazard Mater.
(2007) - et al.
Suitability of graphene monolayer as sensor for carcinogenic heavy metals in water: a DFT investigation
Appl. Surf. Sci.
(2020) - et al.
Two-dimensional GaTe monolayer as a potential gas sensor for SO2 and NO2 with discriminate optical properties
Superlattice. Microst.
(2019) - et al.
High-performance iron oxide–graphene oxide nanocomposite adsorbents for arsenic removal
Colloids Surf. A Physicochem. Eng. Asp.
(2017) - et al.
Interaction of trivalent arsenic on different topologies of Fe-doped graphene nanosheets at water environments: a computational study
J. Mol. Liq.
(2019) - et al.
Graphene for amino acid biosensing: theoretical study of the electronic transport
Appl. Surf. Sci.
(2017) - et al.
High gas-sensing selectivity of bilaterally edge-doped graphene nano-ribbons towards detecting NO2, O2 and SO3 gas molecules: ab-initio investigation
Appl. Surf. Sci.
(2020) I.T.H.E. First, Guidelines for Drinking-water Quality
(2008)A review of the source, behaviour and distribution of arsenic in natural waters
Appl. Geochem.
(2002)- et al.
Removal of fluoroquinolone from aqueous solution using graphene oxide: experimental and computational elucidation
Environ. Sci. Pollut. Res.
(2018)