Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes)

Accepted Manuscript Title: Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes) Author: K. Hamdi M. H´ebrant P. Martin B. Galland M. Etienne PII: DOI: Reference:

S0925-4005(15)30369-5 http://dx.doi.org/doi:10.1016/j.snb.2015.09.062 SNB 19047

To appear in:

Sensors and Actuators B

Received date: Revised date: Accepted date:

24-3-2015 7-9-2015 11-9-2015

Please cite this article as: K. Hamdi, M. H´ebrant, P. Martin, B. Galland, M. Etienne, Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene, toluene and xylenes), Sensors and Actuators B: Chemical (2015), http://dx.doi.org/10.1016/j.snb.2015.09.062 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Mesoporous silica nanoparticle film as sorbent for in situ and real-time monitoring of volatile BTX (benzene,

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toluene and xylenes) K. Hamdia,b, M. Hébranta, P. Martinb, B. Gallandb, M. Etiennea,*

CNRS and Université de Lorraine, Laboratoire de Chimie Physique et Microbiologie pour

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a

Institut National de Recherche et de Sécurité (INRS), 54500 Vandoeuvre-lès-Nancy, France

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b

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l'Environnement (LCPME), UMR7564, 54600, Villers-lès-Nancy, France

Abstract

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A strategy is described for the real time and selective monitoring of benzene, toluene and pxylene (BTX) in air. Rapid preconcentration and recovery have been achieved with films

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made of mesoporous silica nanoparticles assembled layer-by-layer on a quartz plate. The

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resulting nanoparticle films displayed high transmittance and allowed the detection of toluene up to 1 ppm within a minute and a regeneration of the sensor in less than 30 s. The sensor response increased while increasing the concentration of benzene (detection at 252 nm), toluene (detection at 267 nm) or p-xylene (detection at 274 nm) in the polluted air from 1 to 100 ppm. The order of sensitivity, i.e. p-xylene > toluene > benzene, was correlated with their respective molar extinction coefficients. The BTX adsorption on mesoporous silica nanoparticle films has been analyzed with the Freundlich adsorption model. The repeatability of the detection was good in intraday (2%) and extra-day (4%) experiments with a given sensor. The ability to detect toluene in the presence of volatile compounds often encountered in working environments (i.e., methyl ethyl ketone, ethanol, acetone and cyclohexane) has been shown. The introduction of a gas dryer before the measurement cell allowed application

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of the sensor in humid atmosphere. This sensor could be used to alert if permissible values of exposure to toluene and p-xylene have been reached during work. Keywords: sensor, real-time detection, volatile organic compounds, BTX (benzene, toluene,

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xylenes), mesoporous silica nanoparticle

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1. Introduction

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Volatile Organic compounds (VOC) are major air pollutants. They are directly implicated in the photochemistry of the ozone layer and can affect human health. Exposure to

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VOC may happen in indoor or outdoor environments, sporadically or over a longer period of time in domestic or professional conditions. Among VOC, monoaromatic compounds such as

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benzene, toluene or xylenes (often referred to as BTX) have carcinogenic, narcotic and neurotoxic properties [1–7]. A long exposure to monocyclic aromatic pollutants at workplaces

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is reported to have detrimental influences on health [5,6,8,9]. For this reason, the legislations

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set permissible exposure limit (PEL) either in domestic or professional environments. Table 1 gives an overview of PEL in the workplaces in France (R4412-149) and European countries (CE 1272/2008) as well as threshold limit value (TLV) in the American legislation (TLVACGIH). For example, benzene PEL for 8 hours exposure is 1 ppm (part per million of air). To determine with a sufficient accuracy the level of exposure is thus of great importance. Ideally, it should be monitored in a real time in order to provide a proper analysis of risk and to implement and validate suitable safety instructions. The most common approaches currently applied to measure VOC in ambient air, workplace atmospheres and cities streets involve an active (forced convection) or a passive (diffusion) sampling [10,11] followed by gas phase chromatographic analysis [12–16]. The principle of this sampling is to adsorb VOC on a highly porous material before thermal desorption [17] or solvent recovery [18]. The analysis time is usually in the range of one hour 2 Page 2 of 39

for active sampling and more for passive sampling. As a consequence of the methodology, these measurements are neither performed in situ nor in real time. Some efforts have been made to improve this critical sampling step by using solid phase micro-extraction that allows to decrease the overall analysis time compared to classical sorbents [19,20]. However, it has

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been shown that the time of preconcentration was inversely proportional to the VOC content. For example, 3 hours were necessary to reach an equilibrium in the presence of 1 ppm of

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toluene [20].

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One important issue is to develop affordable and in situ technique for BTX detection. In this respect, some research groups made efforts to go to real time instruments by replacing

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VOC sampling and chromatographic analysis by other detection means. For example, a nanocomposite film adsorbent made of polymer and carbon nanotubes was deposited over an

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acoustic wave sensor. This device allowed rapid, repetitive and sensitive determination of toluene, but no selectivity versus other monocyclic molecules was reported [21]. A more

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complex strategy has been proposed, using flow injection analysis with a biosensor based on

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living bacteria. In this case, only benzene was detected thanks to the selective metabolism of benzene by the chosen bacterial strain [22].

Among the different sorbents that have been studied, there is a specific interest for

silica based porous materials, because of favorable adsorption kinetic and selectivity. For instance, surface photovoltage technique has been combined with phenyl-modified mesoporous silica thin films for the detection of toluene in the range of 100-800 ppm [23]. SBA16 mesoporous silica was used as adsorbent in a microfluidic sampler before to perform thermal desorption and FTIR detection. The device allowed the selective determination of benzene, toluene or xylenes with a sampling period of 2.5 minutes, inducing a typical analysis time of 30 minutes [24]. The same research group also reported a similar device but using UV detection instead of FTIR. The selective determination of BTX was obtained in less than a

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minute. However the thermal desorption step appeared to be rather slow and the authors had to concentrate the released vapor phase by a cold trap to obtain a good sensitivity, which make the overall approach technically more difficult to implement [25]. An in situ UV spectrometric determination of BTX was also proposed through a

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transparent mesoporous silica monolith (~2 mm thick) used as sorbent. This approach allowed the detection of low BTX concentrations, i.e. 60 ppb (part per billion of air). However the

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pollutant trapping was found to be irreversible, making this approach unsuitable for real time

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sensing [26]. By using mesoporous silica thin disks displaying bigger pores, the same group could report the reversible detection of BTX [27]. And following the same strategy, but using

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many disks to increase the BTX uptake, Hue et al. showed that 20 ppb of benzene could be successfully detected within 40 minutes of exposure [28].

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Our goal was to develop a suitable device allowing in situ and selective determination of BTX in real time (ideally an accurate response within 5 minutes) in order to monitor

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eventual exposure peak to such pollutants on a work place (on-site). This information is

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critical in order to provide proper safety actions allowing safer working conditions. The porosity of the sorbent is critical in the sorption process of VOC. To introduce the maximum of porosity in the material while maintaining a sufficient transparency would allow a faster regeneration of the sorbent for rapid and repetitive detections with the same sensor. The bonding energies for aromatics adsorption on silica surface are weak, which

means that desorption reactions are expected to be possible in rather mild conditions. This is an important criterion considering the goal of a rapid regeneration of the sensing material for continuous operations. Nanoporous silica is thus an excellent candidate as sensing material for aromatic compounds, as illustrated by several reports in the literature [23–28]. We report here the fabrication of a transparent silica sorbent for the direct and selective UV determination of BTX. Toluene has been used as model pollutant for most of the

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experiments. Benzene and p-xylene have also been tested in order to evaluate the selectivity of the sensor. The experimental set-up that allowed direct detection of BTX has been first implemented and tested with a monolithic silica sorbent as sensitive material. Synthesis of mesoporous silica nanoparticles and their deposition as porous nanoparticle film on quartz

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have been then performed. The relation between the thickness of the film, the transmittance of the modified quartz plate and the sensitivity of the sensor have been studied. The regeneration

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of the sensitive material has been evaluated and calibration curves for benzene, toluene and p-

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xylene have been established and analyzed with the Freundlich adsorption model. Finally, the interference from water and organic molecules found in professional environments have been

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studied. 2. Materials and methods

tetramethoxysilane

(TEOS,

(TMOS,

99

98 %),

%), methyltriethoxysilane

(MeTEOS,

99

%),

methyltrimethoxysilane

(MeTMOS,

98

%),

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Tetraethoxysilane

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2.1. Chemicals

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hexamethyldisilazane (HMDS, ≥ 99 %), cetyltrimethylammonium chloride (CTACl, ≥ 98 %) and triethylamine (TEA, ≥ 99 %) have been used as received. Artificially polluted atmospheres have been prepared with anhydrous pure toluene (99.8 %), benzene (99.8 %), mxylene (99%), o-xylene (98 %), p-xylene (99 %), anhydrous cyclohexane (99.5 %), methyl ethyl ketone (MEK, ≥ 99 %), anhydrous ethanol (≥ 99.8 %) and acetone (≥ 99.9 %). All chemicals have been provided by Sigma Aldrich-France. 2.2. Elaboration of the sensing materials 2.2.1. Silica monolith The protocol for silica monolith synthesis has been adapted from Calvo-Muñoz et al. [26]. The molar ratio of the synthesis was TMOS/MeTMOS/ethanol/water (1:1:8:8). Silica precursors have been added in the ethanol-water mixture. The pH of the mixture has been

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brought to 1.8-2 range by adding hydrochloric acid. The mixture has been then left under stirring for 24 hours. Ammonia has been added to the solution with the molar ratio [NH3]/[Si] = 7.5 10-4 and 200 µl of the solution has been immediately dropped in a MICROSTESTTM microwell plate. After gelation, the monoliths have been placed in a ventilated oven at 40 °C

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for 1 hour and then stored in a glass flask prior use. The cylindrical transparent monoliths were concave with 3.5 mm diameter and an average thickness of 1 mm measured on the edge

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of the pellets.

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2.2.2. Silica nanoparticles synthesis and nanoparticle film deposition

Mesoporous silica nanoparticles have been prepared by adapting a protocol from

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Möller et al. [29]. The synthesis has been carried out using the molar mixture TEOS/TEA/CTACl/EtOH/H2O (1:1.3:0.31:7.8:137). 1.966 g of CTACl have been dissolved

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under stirring in 49.33 ml of ultrapure water. 7.14 g of pure ethanol and 2.64 g of TEA have been then added. The mixture has been heated up to 60 °C. 4.46 ml TEOS has been added

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dropwise to the mixture within 2-3 minutes. The solution has been kept at 60 °C under

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vigorous stirring for 60 minutes and allowed to cool to room temperature. A white pale suspension has been obtained. The role of CTACl in this protocol was to create the porosity in the material. An acidic mixture of 10 g concentrated hydrochloric acid HCl (37 %) in 100 ml of pure ethanol has been used for the removal of this surfactant from the pores. The extraction procedure has been carried out twice. The extraction solution mixed with the nanoparticles suspension has been sonicated for 15 minutes before centrifugation at 10000 rpm. The solid phase has been re-suspended and a second extraction has been performed. The solid fraction has finally been dispersed in 50 g of pure ethanol in order to obtain a suspension with 10 % w/w of mesoporous silica nanoparticles. Hybrid silica particles have been obtained by following the same protocol, by replacing a molar fraction of TEOS, from 5 to 20 %, by MeTEOS.

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The final suspension of silica nanoparticles has been dip-coated on a clean 8x9x1 mm quartz plate with 10 mm min-1 withdrawal speed. Quartz plates have been cleaned with ethanol and treated with sodium hydroxide and dried at 130°C prior the deposition. From to 1 to 10 layers, films have been dried one minute in ambient air between each dip-coating and a final curing

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at 130 °C has been applied for one hour. For the preparation of 30 and 50 layers films, dipcoating has been performed successively 10 times and a curing at 130 °C has been applied for

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1 h. This protocol has then been repeated 3 or 5 times. Surface grafting of the nanoparticle

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film has been achieved by exposure to HMDS vapor and treatment at 100 °C for 12 hours

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[30].

2.3. Characterization

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Specific surface areas have been determined by nitrogen gas sorption volumetry

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(Sorptomatic 1990 apparatus). The Brunauer–Emmett–Teller (BET) theory has been used to

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interpret the adsorption isotherms. Silica samples have been degassed at 150 °C for 24 h before nitrogen sorption analysis. TEM observations have been made by an FEI CM200 analyzer. A drop of the template-extracted nanoparticles suspended in ethanol have been deposited on a holey carbon-Cu grid. Film thickness has been determined by profilometry. Average nanoparticle size has been determined by dynamic light scattering (DLS) with a Malvern Zetasizer instrument. Optical transmittance has been determined in the spectral range of 190nm-400nm (Oceanoptics QE65000 spectrometer). A Hitachi FEG S4800 highresolution scanning electron microscope (SEM) coupled to a wavelength-dispersion spectrometer (WDS) has been used to characterize the nanoparticle films. 2.4. Experimental bench and standard evaluation experiment A scheme of the experimental bench is shown in Figure 1. In the sampling cell (Fig. 1B), the material of sensing, either a monolith or a nanoparticle film, was exposed continuously to UV 7 Page 7 of 39

light emitted from the D2000 Oceanoptics source. The signal was collected by the Oceanoptics QE65000 spectrometer every 25 milliseconds and an average spectrum was saved every 5 seconds. A synthetic polluted-air generation chamber (42 L) was connected to the sampling cell with Teflon tubes. For sampling the pump was delivering a flow rate of 0.1

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L min-1. The regeneration of the adsorbent was made with a second circuit at a flow rate of 4.7 L min-1. In order to evaluate the sensor for the BTX detection, a series of exposition (1, 3

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and 5 min) and regeneration (1 min) cycles to toluene at 20 ppm concentration in dry air were

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performed. The fluidic system was basically similar to the one used by Tran-Thi et al [27]. The measuring cell has been initially designed for the monolithic pellets before to be adapted

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to the quartz plates. It was composed of two brass blocks in which a slot of 8 mm width and 1 mm thickness was incised in order to introduce the quartz plate (Figure 1B).

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The zero absorbance values have been defined on the sorbent material before each experiment. ∆Absorbance values have been calculated by the difference between the average

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values of the maximum absorbance on the 3 and 5 minutes exposure peaks and the minimum

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values preceding the corresponding peak.

Preliminary control experiments have been performed to ensure the good quality of the

data on low toluene concentrations. SnO2 detectors have been calibrated in both the generation chamber and in the circuit in order to ensure that the amount of toluene flowing in the measurement cell was the same as the one generated. It has been controlled that the response of the SnO2 detector did not vary with the flow conditions and the relative humidity. A photoionization detector (PID) in the generation chamber allowed to measure the concentration of the pollutant in the generation chamber and to ensure that this concentration did not vary during the measurement.

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In the study on water interference, a portable air dryer (PD series-50 tubing- and 30 cm length, Perma Pure LLC, USA) has been added to the experimental bench in order to remove humidity from the air entering the measurement cell.

3. Results and discussion

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3.1. Characteristics of the sensor with silica monolith

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Experiments have been first conducted with using a silica monolith as sensing material in the measurement cell. BET analysis of nitrogen adsorption isotherm gave a specific surface

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area of 642 m² g-1 and an average pore size of 1.0 nm ± 0.1 nm (see Table 2). The optical transmittance in the region 225-275 nm was in the range of 5%, which was sufficient for the

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detection of adsorbed aromatic compounds. Figure 2A shows the difference in the measured

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spectra, before (baseline, curve a) and after 1 min of contact with an air enriched with 50 ppm of toluene at room temperature (curve b). As the baseline was defined with the monolith in the

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measurement cell, the typical spectrum of toluene was observed in the presence of this

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molecule, characterized by well-defined absorbance peaks at 260 nm and 267 nm. Note that no signal was observed if 50 ppm toluene was simply flowing through the cell in the absence of the silica monolith for preconcentration. In our studies, 267 nm wavelength was systematically used for the continuous monitoring of toluene adsorbed on silica materials. Figure 2B presents the continuous monitoring of toluene (50 ppm) with this sensor.

The silica monolith was first exposed to clean air (not containing toluene) for 4 min, before being exposed to air with toluene for 1 min. Arrows (a), (b) and (c) correspond to the spectra reported in Figure 2A. In the absence of toluene (from 0 to 240 s) the response was constant at an absorbance value close to zero. The exposition to toluene led to a rapid increase of the absorbance up to 2.9x10-2 unit after 1 min. As our target in this study was a determination every 5 min, the sensor had to be regenerated rapidly before a new measurement. This cleaning step was obtained by flowing a clean air through the measurement cell for 4 min at a 9 Page 9 of 39

higher flow rate (4.7 L min-1). The measured absorbance decreased rapidly, down to 9x10-3 unit. However, total recovery of the sensor was not observed in this experiment. Curve c in Fig. 2A shows that the absorbance measured after “regeneration” was indeed ascribed to some toluene molecules trapped in the material.

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A new exposition to toluene for 1 min induced again an increase of the absorbance. This cycle was repeated seven times. The average signal intensity after one minute of

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exposure was 3.9x10-2 unit with this monolith. These results are perfectly in agreement with

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previous reports [26,28]. It is supposed that incomplete desorption was due to the large thickness of the monolith that induced diffusion pathways that were not compatible with the

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time scale of the experiment. A better regeneration was however reported before for the UV detection of p-xylene in thin mesoporous silica disks displaying bigger pores [27]. Replacing

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the monolith with a nanoparticle film to decrease the time of diffusion into the materials could also be an option in order to reach a faster response and a total regeneration of the sensor.

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3.2. Mesoporous nanoparticles synthesis and nanoparticle films deposition

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Stöber process is a chemical synthesis allowing the uniform growth of spherical

particles by the hydrolysis of alkoxysilanes and their subsequent condensation [31]. This protocol has been adapted in the past to the synthesis of mesoporous nanoparticles in the presence of cetyltrimethylammonium chloride (CTACl) as template [29]. Figure 3 reports a TEM characterization of nanoparticles obtained for this study. The particles displayed a diameter of 50 to 60 nm with well-defined mesopores. The distance between two pores was estimated by TEM to be comprised between 2.9 and 3.6 nm. The porosity was obtained in the material by extraction of CTACl in HCl – ethanol solution. After two successive extractions, the material displayed a specific surface area higher than 1000 m2 g-1 (Table 2). DLS analysis (Figure 3B) revealed a hydrodynamic diameter distribution displaying a maximum around 200 nm without any dilution of the silica nanoparticles suspension. The

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difference observed between the TEM and DLS results may be attributed to a multiple diffusion phenomenon rather than an aggregation phenomenon. Indeed after dilution, the distribution of the average diameter decreased down to 100 nm. This hydrodynamic diameter measured in solution was still bigger than the diameter measured by TEM, but was in

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agreement with data reported before on this material [29]. Nanoparticle films have been prepared by successive dip-coating from an alcoholic

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suspension of these particles (~10 % w/w). The continuity and cohesion of the assembly of

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silica nanoparticles in a film was determined by SEM (Figure 4A). X-ray diffraction experiment on a film gave a peak at 2Ɵ=1.7°, characteristic of a vermicular structure with a

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mean inter-reticular distance of 5.2 nm. The thickness of this film varied from 600 nm to approximately 4 µm (Figure 4B), depending on the number of layers (one layer being

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obtained with one dip-coating step). However, thicker films, i.e. higher number of layers, led to cracks into the films, which was detrimental for their optical quality and mechanical

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stability (see Figures S1&S2 in the supplementary material). The non-linear growth of the

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film thickness could be ascribed to this limited stability. Films prepared with 3 layers displayed a homogeneous thickness (see Figure S3 in the supplementary material) and, for this reason, have been chosen for the evaluation of the analytical performances of the BTX sensor. It has been observed in this section that films could be produced from mesoporous nanoparticles. The following section will describe their application as sensing material for BTX detection.

3.3. Effect of thickness on the response of silica nanoparticle films Figure 5A shows the variation of absorbance measured at 267 nm in the presence and in the absence of toluene with a quartz plate coated with a nanoparticle film with 1.8 µm thickness. Toluene concentration was fixed at 20 ppm and the sensor was exposed

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successively for 1, 2 and 5 min to a dry air polluted by toluene at 0.1 L min-1 before to be regenerated by purging at 4.7 L min-1 with a dry clean air. A steady state response to toluene was reached in about 60 s and a total desorption was obtained after 30 s of purge. At the opposite, with a silica monolith, the absorbance was increasing continuously due to the very

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high surface available for adsorption (Figure 2B). With a nanoparticle film, an equilibrium was thus more rapidly reached between the air and the surface. A good ratio between signal

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and noise was achieved. The variation of absorbance was close to 0.01, i.e. the same order of

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magnitude as the variation reported in Figure 2B with a silica monolith (tested with slightly higher toluene concentration, 50 ppm). Figure 5B shows the UV spectra measured between

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210 and 300 nm in the presence of (a) 60 ppm of benzene, (b) 20 ppm of toluene and (c) 20 ppm of p-xylene. These spectra are well defined and considering proper signal processing it

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should be possible to achieve selective detection of these molecules in a complex environment. Moreover, the different p-xylene molecules are also displaying differences in

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possibility for individual analysis.

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their spectroscopic response (see Figure S4 in the supplementary material), which opens the

In the absence of toluene, the optical transmittance at 267 nm was decreasing with the

number of layers in the films from 87 % (A=0.0604) for 1 layer to 40 % for 50 layers (A=0.398 see Figure 6A). For comparison, in the same conditions, the transmittance of the silica monolith was close to 5% (A≈1.40, dotted line in Figure 6A). A high transmittance allows in principle a better signal-to-noise ratio with a low intensity portable UV lamp. Nanoparticle films are thus suitable candidates as sensing material. The films have been then tested for the detection of toluene. ∆Absorbance has been first plotted versus the number of layers (Fig. 6B). The trend of this variation is clearly similar as the one observed in Fig. 6A for absorbance, the response of the sensor (∆Absorbance) increasing with the number of layers. Inset in Fig. 6B shows that there is a linear correlation between the sensitivity of the 12 Page 12 of 39

sensor and the thickness of the nanoparticle film deposited on quartz, ∆absorbance increasing by 0.006 per µm. The thickness of the film was not increasing regularly with the number of layers, the growth being higher for the 10 first layers. 3 layers (i.e. 3 successive dip-coatings) allowed to reach thicknesses comprised between 1.5 and 2 µm and could be prepared rapidly.

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The relative variability between the signals obtained with one film in the same experiment was less than 2 %. A film stored within three months without particular care and used on the

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same detection scheme allowed repetition of the sensor response with less than 4 % variation.

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Three films prepared from 3 layers of the same batch of nanoparticles allowed repeatable

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sensor response with less than 20 % variation.

3.4. Calibration curve

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Figure 7 shows the experimental curve for a three layers film exposed to toluene concentration from 1 to 100 ppm, the inset represents the ∆A as a function of a SnO2 sensor

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response used as a control. In these experiments, the exposure was done for 2 min and the

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purge for 1 min for the same concentration and 2 min between two different concentrations. For a given concentration the signal was not increasing during consecutive

acquisitions. A slight drift of the baseline was observed for the highest concentration but, since the SnO2 sensor behaved the same, it has been assumed that this residual signal was due to residual traces of toluene in the circuit and not to a partial desorption of the toluene from the nanoparticle film. Both the SnO2 sensor and the one developed here were behaving the same, i.e. giving a non-linear response as a function of the toluene concentration. SnO2 detected easily 1 ppm of toluene, but contrarily to our UV detection, without selectivity. With the sensor developed in this work 2 ppm of toluene were easily detected. In these conditions, considering the difficulty to generate accurately low pollutant concentrations, 1 ppm may be assumed as the LOD.

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The sensor was responding non-linearly to benzene (Fig. 8, curve a), toluene (Fig. 8, curve b) and p-xylene (Fig. 8, curve c) from 1 to 100 ppm. The order of sensitivity, i.e. pxylene > toluene > benzene, was correlated to the molar extinction coefficient determined in hexane solution (0.1 mM), respectively 862 (at 274 nm), 240 (at 269 nm) and 215 (at 255 nm)

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l mol-1 cm-1. Non-linearity of SnO2 sensors is commonly admitted [32]. If we assume that the variation of absorbance was here following the Beer-lambert law, one comes to the

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conclusion that these adsorption isotherms of BTX was not linear. In other words, the

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trapping efficiency varied nonlinearly with the concentration of pollutant. This behavior can be modeled by adapting the Freundlich equation, considering that the absorbance was

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proportional to the ratio of the number of occupied adsorption sites to the number of

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unoccupied ones (Equation 1).

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Equation 1

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The Freundlich isotherm is generally used for sorbent having a heterogeneous surface. K account for the affinity constant at P=0 and α characterize the interaction between the sorbent and the adsorbed molecule (α=1 means that the sites are independent and Freundlich model resumes then to the Langmuir one, α<1 indicates that the adsorption energy decreases with the number of adsorbed molecules). A fit between experimental and calculated values allowed to determine K and α (Table 3). Here, K characterized the affinity of the pollutant with the intrapore or interstice environment when the pollutant was trapped either in the pore or inside the interstice. Dipolar moment of benzene, p-xylene and toluene are respectively 0, 0.02 and 0.31 Debye [33]. The fact that benzene and p-xylene displayed similar K values (respectively 19.5 and 12.6), higher than toluene (2.2) indicates that the affinity of these non protic molecules with the mesoporous silica layer was linked to their polarity in vapor phase. α was fairly similar for p-xylene and toluene, lower than for benzene. The point of interest is 14 Page 14 of 39

that α was lower than 1 in all cases. Indeed, BTX adsorption may occur in mesoporous silica nanoparticle film at different energy levels since the sites of adsorption are displaying different curvatures and accessibilities. This interpretation is reinforced by a recent molecular simulation study of the adsorption of benzene on atomistic silica surfaces and nanopores [34].

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The orientation of the adsorbed benzene molecules should depend on the hydroxylation state of the material, and may form an angle between 90° to 50° with the silica surface.

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These results are very encouraging since the sensor already fulfill the requirement for

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detection of toluene and p-xylene, as PEL in Europe and TLV in USA are respectively 50 and

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20 ppm (see Table 1). Some improvement are still required for benzene detection.

3.5. Selectivity towards BTX in the presence of other pollutants

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Since BTX molecules are not found alone in the polluted air, toluene detection has been tested in the presence of other pollutants. National Institute for research and safety

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(INRS-France) have performed measurement campaigns in the worker environment of

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different industries in France [35,36] in order to establish a list of volatile organic compounds that were encountered. It was shown that aromatic molecules were often found together with alcohols, ketones and aliphatic hydrocarbons. Therefore the response of the sensor to 20 ppm toluene (a in Fig. 9) was compared to the response to toluene in the presence of 40 ppm cyclohexane (b), ethanol (c), acetone (d) and MEK (e). Cyclohexane had no impact on the detection of toluene, neither on the intensity nor on the aspect of the UV absorbance spectrum (compare curves a&b, Fig. 9B). The presence of MEK, ethanol or acetone led to an increase in the absorbance signal, but this increase was mainly due to a general increase in the background signal and did not prevent the observation of the toluene signal (curves c-e, Fig. 9B). Experiments have been performed in order to evaluate the possibility to subtract the spectrum of the interfering solvent alone from the spectrum measured in the presence of both

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toluene and an interfering solvent. Figure S5 in the supplementary material provides the spectra measured after 60 s exposure to 40 ppm hexane or 40 ppm ethanol and those measured in the presence of 20 ppm toluene and 40 ppm of solvent. The absence of interference from hexane was confirmed (Fig. S5A). However, the absorption measured with

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only 40 ppm ethanol (Fig. S5B, curve a) was higher than the one measured in the presence of 40 ppm ethanol and 20 ppm toluene (Fig. S5B, curve b). Kinetic has to be considered here, as

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toluene adsorption was favored compared to the ethanol adsorption during the first steps of

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the adsorption on the nanoparticle film. Similar results were obtained with MEK and acetone. These data confirm the interest of low exposure time for the detection of BTX in real

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atmosphere and they open an interesting outlook for kinetic selectivity and chemometric analysis of the sensor response for the discrimination of BTX response in workers

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environment.

Finally the interference of humidity was considered. Figure 10 reports the detection of

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20 ppm toluene in dry air (curve a) and in the presence of humid air (curve b, 50 % humidity,

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i.e. ~12000 ppm H2O). As it can be observed, the presence of water induced a dramatic degradation of the sensor response. Different strategies have been considered to remove this major interference. One strategy was based on the methylation of the mesoporous particles in order to promote the adsorption of toluene in humid atmosphere. Hybrid silica particles have been modified for this purpose by co-condensation of 5, 10 or 20 % methyltrimethoxysilane with tetraethoxysilane. However, films prepared with these particles show a lower sensitivity to toluene in dry air than the original nanoparticle film, the sensitivity being here related to the available specific surface area (see Table S1, Figure S6&7 and Figure S8A in the supplementary material). And none of these materials could perform a detection of toluene in humid

atmosphere.

Mesoporous

silica

nanoparticles

were

then

grafted

with

hexamethyldisilazane, but the resulting sensor completely lost its sensitivity to toluene, even

16 Page 16 of 39

in dry air (see Figure S8B in the supplementary material). To conclude, surface functionalization was not a suitable strategy for introducing selectivity to toluene in the presence of water. Finally, the application of the sensor in humid air was made possible by the introduction of a gas dryer before the measurement cell. The resulting signal is reported in

ip t

Figure 10, curve c. In these conditions, the response of the sensor to humid air was similar to the one measured in the presence of dry air (curve a). This last result demonstrate the

cr

applicability of the sensor in real environment, i.e. in the presence of humidity, by using a

us

drying step before the measurement cell, without sacrificing the time response.

an

4. Conclusions

Films prepared from mesoporous silica nanoparticles have been successfully applied

M

to the preconcentration of benzene, toluene and p-xylene for their continuous monitoring in an air artificially polluted. For toluene, the sensor allowed rapid response up to 2 ppm toluene, a

d

steady state response being reached within a minute. The regeneration of the surface was also

Ac ce pt e

very rapid, typically less than 30 s with nanoparticle films of 1.5 to 1.8 µm. The sensor displayed good repeatability within 3 months. This novel approach allowed solving some problems encountered with silica monoliths displaying a good sensitivity but only a poor regeneration of the sensor. Nanoparticle films combine the advantages of large surface area and enhanced airflow throughout the material and provide suitable transparency for spectroscopic analysis. The sensitivity that has been reached in this work was yet sufficient for qualification of toluene and p-xylene polluted and non-polluted air according to actual legislation on permissible values of exposure. Some improvement are still required for benzene, which could be achieved by increasing the thickness of the film. The presence of cyclohexane had no impact on the detection of toluene and the presence of MEK, ethanol and acetone induced an increase in the absorbance signal. First observations indicate that a kinetic

17 Page 17 of 39

selectivity could be involved at short exposure time. The major interference coming from humidity was removed by using a gas dryer without sacrificing the time response. Further work is currently conducted in order to optimize the sensor for on-site analysis of air in

ip t

industrial environments.

cr

Acknowledgments

The authors wish to thank Dr. Jaafar Ghanbajaa (Institut Jean Lamour, Nancy, France) for the

us

TEM analysis, Pierrick Durand (CRM2, Nancy) for DRX experiments and Aurélien Renard

an

(LCPME) for nitrogen adsorption experiments. These works were funded by the National

5. References

M

Institute for research and safety INRS-France.

L. Fishbein, An overview of environmental and toxicological aspects of aromatic hydrocarbons. I. Benzene, Sci. Total Environ. 40 (1984) 189–218. doi:10.1016/00489697(84)90351-6.

[2]

L. Fishbein, An overview of environmental and toxicological aspects of aromatic hydrocarbons III. Xylene, Sci. Total Environ. 43 (1985) 165–83. doi:10.1016/00489697(85)90039-7.

[3]

L. Fishbein, An overview of environmental and toxicological aspects of aromatic hydrocarbons II. Toluene, Sci. Total Environ. 42 (1985) 267–88. doi:10.1016/00489697(85)90062-2.

[4]

IRAC (lnternational Agency for Research on Cancer), IARC monographs on the evaluation of carcinogenic risks to humans: supplement 7, world health organization, Lyon, France, 1987.

[5]

C. Gericke, Multicenter field trial on possible health effects of toluene III. Evaluation of effects after long-term exposure, Toxicology 168 (2001) 185–209. doi:10.1016/S0300-483X(01)00408-5.

[6]

D. Neubert, Multicenter field trial on possible health effects of toluene. II. Crosssectional evaluation of acute low-level exposure, Toxicology 168 (2001) 159–83. doi:10.1016/S0300-483X(01)00407-3.

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F. Pariselli, M.G. Sacco, J. Ponti, D. Rembges, Effects of toluene and benzene air mixtures on human lung cells (A549), Exp. Toxicol. Pathol. 61 (2009) 381–6. doi:10.1016/j.etp.2008.10.004.

[8]

Y.L. Won, Y. Ko, K.H. Heo, K.S. Ko, M.Y. Lee, K.W. Kim, The Effects of LongTerm, Low-Level Exposure to Monocyclic Aromatic Hydrocarbons on Worker’s Insulin Resistance, Saf. Health Work. 2 (2011) 365–74. doi:10.5491/SHAW.2011.2.4.365.

[9]

H. Fujimaki, S. Yamamoto, Tin-Tin-Win-Shwe, R. Hojo, F. Sato, N. Kunugita, K. Arashidani, Effect of long-term exposure to low-level toluene on airway inflammatory response in mice, Toxicol. Lett. 168 (2007) 132–9. doi:10.1016/j.toxlet.2006.11.008.

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[7]

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[10] M.D. Wright, N.T. Plant, R.H. Brown, Diffusive Sampling of VOCs as an Aid to Monitoring Urban Air Quality, Environ. Monit. Assess. 52 (1998) 57–64. doi:10.1023/A:1005818606755.

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[11] G. Pilidis, S. Karakitsios, P. Kassomenos, BTX measurements in a medium-sized European city, Atmos. Environ. 39 (2005) 6051–65. doi:10.1016/j.atmosenv.2005.06.044.

M

[12] S. Zhang, T. Zhao, X. Xu, H. Wang, C. Miao, Determination of BTEX Compounds in Solid–Liquid Mixing Paint Using the Combination of Solid Phase Extraction, Thermal Desorption and GC-FID, Chromatographia. 71 (2010) 1131–5. doi:10.1365/s10337010-1577-y.

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d

[13] D. Wai-Mei Sin, Y. Wong, W. Sham, D. Wang, Development of an analytical technique and stability evaluation of 143 C3–C12 volatile organic compounds in Summa® canisters by gas chromatography–mass spectrometry, Analyst. 126 (2001) 310–21. doi:10.1039/b008746g. [14] J.L. Wang, S.W. Chen, C. Chew, Automated gas chromatography with cryogenic/sorbent trap for the measurement of volatile organic compounds in the atmosphere, J. Chromatogr. A. 863 (1999) 183–93. doi:10.1016/S00219673(99)00965-6. [15] S. Tumbiolo, J.F. Gal, P.C. Maria, O. Zerbinati, Determination of benzene, toluene, ethylbenzene and xylenes in air by solid phase micro-extraction/gas chromatography/mass spectrometry, Anal. Bioanal. Chem. 380 (2004) 824–30. doi:10.1007/s00216-004-2837-1. [16] Y. Chen, J. Pawliszyn, Time-weighted average passive sampling with a solid-phase microextraction device, Anal. Chem. 75 (2003) 2004–10. doi:10.1021/ac026315+. [17] R.H. Brown, What is the best sorbent for pumped sampling-thermal desorption of volatile organic compounds? Experience with the EC sorbents project, Analyst. 121 (1996) 1171-5. doi:10.1039/an9962101171.

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[18] P. Schneider, I. Gebefügi, K. Richter, G. Wölke, J. Schnelle, H.E. Wichmann, J. Heinrich, Indoor and outdoor BTX levels in German cities, Sci. Total Environ. 267 (2001) 41–51. doi:10.1016/S0048-9697(00)00766-X. [19] J. Nicolle, V. Desauziers, P. Mocho, Solid phase microextraction sampling for a rapid and simple on-site evaluation of volatile organic compounds emitted from building materials, J. Chromatogr. A. 1208 (2008) 10–5. doi:10.1016/j.chroma.2008.08.061.

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ip t

[20] P. Mocho, J. Nicolle, V. Desauziers, Modelling of adsorption kinetics and calibration curves of gaseous volatile organic compounds with adsorptive solid-phase microextraction fibre: toluene and acetone for indoor air applications, Anal. Bioanal. Chem. 392 (2008) 97–104. doi:10.1007/s00216-008-2249-8.

us

[21] I. Sayago, M.J. Fernández, J.L. Fontecha, M.C. Horrillo, C. Vera, I. Obieta, I. Bustero, New sensitive layers for surface acoustic wave gas sensors based on polymer and carbon nanotube composites, Sensors Actuators B Chem. 175 (2012) 67–72. doi:10.1016/j.snb.2011.12.031.

an

[22] Y.H. Lanyon, G. Marrazza, I.E. Tothill, M. Mascini, Benzene analysis in workplace air using an FIA-based bacterial biosensor, Biosens. Bioelectron. 20 (2005) 2089–96. doi:10.1016/j.bios.2004.08.034.

d

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[23] B. Yuliarto, Y. Kumai, S. Inagaki, H. Zhou, Enhanced benzene selectivity of mesoporous silica SPV sensors by incorporating phenylene groups in the silica framework, Sensors Actuators B Chem. 138 (2009) 417–21. doi:10.1016/j.snb.2009.02.026.

Ac ce pt e

[24] Y. Ueno, A. Tate, O. Niwa, H.S. Zhou, T. Yamada, I. Honma, High benzene selectivity of mesoporous silicate for BTX gas sensing microfluidic devices, Anal. Bioanal. Chem. 382 (2005) 804–9. doi:10.1007/s00216-004-2974-6. [25] Y. Ueno, T. Horiuchi, O. Niwa, H.S. Zhou, T. Yamada, I. Honma, Portable automatic BTX measurement system with microfluidic device using mesoporous silicate adsorbent with nano-sized pores, Sensors Actuators B Chem. 95 (2003) 282–6. doi:10.1016/S0925-4005(03)00540-9. [26] M.L. Calvo-Muñoz, T.T. Truong, T.H. Tran-Thi, Chemical sensors of monocyclic aromatic hydrocarbons based on sol-gel materials: kinetics of trapping of the pollutants and sensitivity of the sensor, Sensors Actuators B. 87 (2002) 173–83. [27] T.-H. Tran-Thi, R. Dagnelie, S. Crunaire, L. Nicole, Optical chemical sensors based on hybrid organic–inorganic sol–gel nanoreactors, Chem. Soc. Rev. 40 (2011) 621–639. doi:10.1039/C0CS00021C. [28] J. Hue, M. Dupoy, T. Bordy, R. Rousier, S. Vignoud, T.H. Tran-Thi, C. Rivron, L. Mugherli, Y. Bigay, P. Karpe, M. Charbonnier, Benzene Detection by Absorbance in the Range of 20 ppb-100 ppb Application: Quality of Indoor Air, Procedia Eng. 47 (2012) 232–5. doi:10.1016/j.proeng.2012.09.126.

20 Page 20 of 39

[29] K. Möller, Jtran. Kobler, T. Bein, Colloidal Suspensions of Nanometer‐Sized Mesoporous

Silica,

Adv.

Funct.

Mater.

17

(2007)

605–12.

doi:10.1002/adfm.200600578

ip t

[30] N. Tasaltin, D. Sanli, A. Jonáš, A. Kiraz, C. Erkey, Preparation and characterization of superhydrophobic surfaces based on hexamethyldisilazane-modified nanoporous alumina. Nanoscale Res. Lett., 6 (2011) 487. doi:10.1186/1556-276X-6-487.

us

cr

[31] W. Stöber, A. Fink, E. Bohn, Controlled growth of monodisperse silica spheres in the micron size range, J. Colloid Interface Sci. 26 (1968) 62–9. doi:10.1016/00219797(68)90272-5. [32] N. Bărsan, R. Ionescu, A. Vancu, Calibration curve for SnO2-based gas sensors, Sensors Actuators B Chem. 19 (1994) 466–9. doi:10.1016/0925-4005(93)01041-2.

M

an

[33] H. Kanai, V. Inouye, L. Yazawa, R. Goo, H. Wakatsuki, Importance of Debye and Keesom interactions in separating m-xylene and p-xylene in GC-MS analysis utilizing PEG stationary phase., J. Chromatogr. Sci. 43 (2005) 57–62.

d

[34] B. Coasne, C. Alba-Simionesco, F. Audonnet, G. Dosseh, K.E. Gubbins, Adsorption and structure of benzene on silica surfaces and in nanopores, Langmuir. 25 (2009) 10648–59. doi:10.1021/la900984z.

Ac ce pt e

[35] J. Triolet, Panorama de l’utilisation des solvants, Hygiène Sécurité Du Trav. 199 (2005) 65–97. [36] N. Bertrand, F. Clerc, Panorama des expositions professionnelles organiques volatils entre 2003 et 2010, Hygiène Sécurité Du Trav. 225 (2011) 31–44.

21 Page 21 of 39

Figure captions Figure 1. (A) Schematic representation of the setup for generation and detection of VOC containing air and (B&C) of the measurement cell containing the sensing material and allowing transport of air (without or without pollutants) and UV irradiation and detection for

ip t

BTX determination. An air dryer was introduced in the setup during the course of the

cr

experiment in order to remove the water interference.

us

Figure 2. (A) UV spectra of the adsorbed toluene on different stages of the detection: (a) baseline before first exposure to the pollutant, (b) after first exposition cycles and (c) the

an

residual toluene on the material after first regeneration. (B) Absorbance variation as a function of time during exposition and regeneration cycles using a silica monolith as sensitive

M

material in the presence of toluene at 50 ppm during exposition. λ=267 nm.

d

Figure 3. (A) TEM image of the synthesized silica nanoparticles. (B) Size distribution of the

Ac ce pt e

nanoparticles given by dynamic light scattering of (a) suspension of silica nanoparticles as synthesized and diluted by a factor (b) 2, (c) 4 and (d) 8.

Figure 4. (A) SEM image of a nanoparticle film prepared with three layers. (B) Influence of the number of layers on the thickness of the film assembly of mesoporous nanoparticles.

Figure 5. (A) Absorbance variation at λ=267nm wavelength as a function of time during exposition and regeneration cycles in the presence of 20 ppm toluene during the successive exposition period for 1, 2 and 5 min. (B) Spectra recorded in the presence of (a) 60 ppm benzene, (b) 20 ppm toluene and (c) 20 ppm p-xylene. Film thickness 1.8 ± 0.08 µm (three layers).

22 Page 22 of 39

Figure 6. Influence of the number of layers, deposited by dip-coating from the particle suspension, on (A) absorbance in absence of toluene and (B) variation of absorbance in the presence of 20 ppm toluene. λ=267nm. Inset shows the correlation between the thickness and

ip t

the variation of absorbance.

cr

Figure 7. Influence of the toluene concentration (ppm) on the variation of absorbance

us

measured at 267 nm. Film thickness 1.8 ± 0.08 µm (three layers). Inset shows the correlation

an

between the absorbance variation and the response of a SnO2 sensor (non-selective).

Figure 8. Influence of the concentration of (a) benzene, (b) toluene and (c) p-xylene on the

M

absorbance measured at (a) 252 nm, (b) 267 nm and (c) 274 nm. The line is representative of the best fit with equation 1 (adjusted parameter in Table 3). Film thickness 1.8 ± 0.08 µm

d

(three layers). Curves a and c have been performed with the same film. Curve b has been

Ac ce pt e

performed with two different films, including the one used for a and c.

Figure 9. (A) Sensor response to 20 ppm of toluene measured at 267 nm (a) in the absence of interfering pollutants and in the presence of 40 ppm of (b) cyclohexane, (c) ethanol, (d) acetone and (e) MEK. (B) Corresponding spectra. Film thickness 1.8 ± 0.08 µm.

Figure 10. Absorbance variation at λ=267nm wavelength as a function of time during exposition (3 min) and regeneration (1 min) cycles in the presence of (a) 20 ppm toluene in dry air, (b) 20 ppm toluene in 50 % humidity air and (c) 20 ppm toluene initially in 50 % humidity air and dried through a gas dryer before the sensor cell. Film thickness ~1.8 ± 0.08 µm (three layers).

23 Page 23 of 39

24

Page 24 of 39

d

Ac ce pt e us

an

M

cr

ip t

FIGURES

A Air dryer

injection

SnO2 sensor

cell

PID control Controled VOC content Pump

an C

M

Cell

Optical fiber

B

Generation chamber stirring

us

Spectrometer

cr

SnO2 sensor

Clean air

ip t

Pump

De lamp

waste

Adsorbing material

Ac ce pt e

Optical fiber

d

Air flow Quartz plate

Figure 1

25 Page 25 of 39

c a

0.00 210

240

270

0.10 b c

0.05

ip t

b

a

0.00 0

300

1800

us

Wavelength / nm

900

cr

0.04

0.02

B

0.15

Absorbance / a.u.

Absorbance / a.u.

A

Time / s

Ac ce pt e

d

M

an

Figure 2

26 Page 26 of 39

A

B 12

d

4 2

c

ip t

6

0 10

100

1000

us

50 nm

a b

8

cr

Intensity / %

10

Diameter / nm

Ac ce pt e

d

M

an

Figure 3

27 Page 27 of 39

A

B

1µm

4

ip t

3 2 1

cr

Thickness / µm

5

0

10

20

30

40

50

us

0

Number of layers

Ac ce pt e

d

M

an

Figure 4

28 Page 28 of 39

A 5 min

0.006 0.004 0.002 0.000

c 0.03 0.02

b

ip t

2 min

0.01

a

cr

1 min

0.008

B

0.04

Absorbance / a.u.

Absorbance / a.u.

0.010

0.00 0

500 1000 1500 2000

250

Time / s

300

us

Wavelength / nm

Ac ce pt e

d

M

an

Figure 5

29 Page 29 of 39

B 0.030

0.2

0.015 0.010 0.005 0.000

0.0 0

10

20

30

40

50

0

0.03 0.02 0.01 0.00

10

20

0

1

2

3

4

Thickness / µm

30

40

50

Number of layers

Ac ce pt e

d

M

an

Number of layers Figure 6

ip t

0.020

cr

0.4

0.025

∆ Absorbance

Absorbance of the monolith

us

1.4 1.2

∆ Absorbance / a.u.

Absorbance / a.u.

A

30 Page 30 of 39

0.010 0.005 0.000

5000

100 ppm

10000

an

0

ip t

0.0 0.5 1.0 1.5

SnO2 Signal / v

cr

0.00

us

0.015

0.01

20 ppm 40 ppm 60 ppm

0.020

0.02

7 ppm 10 ppm 15 ppm

0.025

Absorbance / a.u.

0.030

0.03

0 ppm 1 ppm 2 ppm 3 ppm 5 ppm

Absorbance / a.u.

0.035

M

Time / s

Ac ce pt e

d

Figure 7

31 Page 31 of 39

P/P0 -5

-4

1.0x10

ip t

5.0x10

cr

c

0.06

0.04

us

b 0.02 a

an

∆ Absorbance / a.u.

0.0 0.08

0.00 20

40

60

80

Ac ce pt e

Figure 8

d

[VOC] / ppm

100

M

0

32 Page 32 of 39

A

B 0.05

0.015

0.010

0.005

b

c

d

0.02 0.01 0.00 200

e

250

300

Wavelength / nm

cr

a

0.03

us

0.000

e d c b a

0.04

ip t

Absorbance / u.a.

∆Α bsorbance / au

0.020

Ac ce pt e

d

M

an

Figure 9

33 Page 33 of 39

ip t

0.010 b

0.005

0.000

a 0

500

1000

Ac ce pt e

d

M

an

Time / s Figure 10

cr

c

us

Absorbance / a.u.

0.015

34 Page 34 of 39

Table1. Permissible exposure limit (PEL) and threshold limit value (TLV) for benzene,

PEL France Law R4412-149

PEL Europe CE 1272/2008

TLV USA TLV-ACGIH

Benzene

1

1

0.5

Toluene

20

50

20

Xylenes

50

50

100

Ac ce pt e

d

M

an

us

cr

VOC

ip t

toluene and xylenes in 2014 (ppm).

35 Page 35 of 39

Table2. Summary table of the different characterizations of the different materials

Silica monolith Silica nanoparticle assembly

Specific surface areaa m² g-1

Pore diameter nm

Thickness µm

642

1.0 ±0.1a

~103

1014

2.9 -3.5b

0.1 – 4c

Ac ce pt e

d

M

an

us

cr

ip t

a: determined by analysis of nitrogen adsorption isotherms b: determined by TEM observations c: determined by profilometry

36 Page 36 of 39

Table 3. Fitting parameters obtained on benzene, toluene and p-xylene adsorption using the Freunlich equation and dipole moment at 20 °C of these molecules. K

α

Dipole moment at 20 °C (Debye) [33]

Toluene

2.2±0.4

0.49±0.02

0.31

Benzene

19.5±3.5

0.77±0.02

0

p-Xylene

12.6±0.6

0.56±0.02

0.02

Mathieu ETIENNE received his PhD in Electroanalytical

an

Chemistry from University Henri Poincaré (France) in 2001

us

cr

ip t

Molecule

before to work with Prof. Wolfgang Schuhmann at RuhrUniversität Bochum (Germany). In 2004, he joined the

M

Laboratory of Physical Chemistry and Microbiology for the

Environment (France) as CNRS researcher where he is currently

developing

researches

on

textured

and

d

functionalized materials for analysis, bioconversion and energy storage. He is also involved in the development of

Ac ce pt e

shearforce-regulated scanning electrochemical microscopy. He is the co-author of about 90 papers.

Khaoula HAMDI has received a MSc degree in green chemistry from the university of Avignon (France, 2011) and in material science from the university of Toulon (France, 2012). In 2012, she joined the Laboratory of Physical Chemistry and Microbiology for the Environment (France) as PhD student for studying silica materials (films and bulk materials) as sorbents for the detection of aromatic air pollutants under the supervision of Pr. Marc HEBRANT and Dr. Mathieu ETIENNE. Her main interests are developing new analytical tools for the detection of volatile organic compounds as well as hierarchically organized materials as sensing layers.

37 Page 37 of 39

Marc Hebrant received his PhD in Physical Chemistry from University Blaise Pascal (France) in 1989 before to join the CNRS in Nancy. He became professor in Analytical chemistry in 2002 at the University of Lorraine and joined at the same time the Laboratory of Physical Chemistry and Microbiology for the Environment (France). He is currently investigating new processes of metal ion extraction and pollutant removal

ip t

based on colloidal suspension and biosorbents. He is the coauthor of about 50 papers.

cr

Patrick Martin received his PhD in the national polytechnic institute of Lorraine (France) in 1985. He joined the National laboratory director. His laboratory develops and validates real time sensors for chemical pollutants in workplaces. He

an

developed CAPTIV-tool largely used in chemical risk

us

institute of research and safety (INRS France) in 1985 as a

assessment and ergonomic study in workplaces. He is

interested in developing new tools and technologies for risk

M

assessment and prevention in work environments.

Bruno GALLAND received his PhD in Physics from University

d

Paris XI - Orsay (France) in 2002. In 2002, he joined INRS, the French national institute for the prevention of occupational

Ac ce pt e

accidents and diseases. His research focuses on vapor and gas detection in workplaces. He is currently developing researches on miniature gas sensors and respiratory protective devices.

Fabrication of mesoporous silica nanoparticle films for BTX adsorption UV detection of toluene up to 1 ppm within a minute Regeneration of the sensor in less than 30 s The order of sensitivity was p-xylene > toluene > benzene Application in humid air by using a gas dryer before the measurement cell

38 Page 38 of 39

Nanoparticle film: adsorbing layer

BTX sensor

Fast response 0.010

BTX polluted air flux

UV (I0 )

UV (I)

Quartz deuterium lamp

Absorbance / a.u.

Mesoporous silica nanoparticles

20 ppm toluene

0.008 0.006 0.004 0.002 0.000 0

500 1000 1500 2000

Ac ce pt e

d

M

an

us

cr

ip t

Time / s

39 Page 39 of 39