Catherine Marichy

Giorgio Ercolano

Gianvito Caputo

Marc-Georg G Willinger

Deborah Jones

Jacques Rozière

Nicola Pinna

Sara Cavaliere

ALD SnO2 Protective Decoration Enhances the Durability of a Pt Based Electrocatalyst

établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Research on proton exchange membrane fuel cell (PEMFC) electrocatalysts has been mainly focused on understanding and improving their activity towards the kinetically limiting oxygen reduction reaction (ORR) at the cathode (and methanol/ethanol oxidation reaction at the direct alcohol fuel cell anode). Significant advances in this regard have been achieved by tuning the size and morphology of the Pt nanocatalyst and elaborating alloys. [1] However, performance degradation over time has emerged as a critical aspect complementary to the electrocatalyst efficiency, and has been extensively studied. [2] This issue, together with the low abundance of Pt in the Earth's crust and thus its cost, has a great impact on hindering the commercialization of PEMFC and the consequent development of a sustainable hydrogen-based economy. The two predominant and interacting processes affecting electrocatalyst lifetime are the corrosion of the carbon-based support and the agglomeration and detachment of the Pt nanoparticles leading to the loss of active surface area under specific cell operating conditions. At potential higher than 0.207 V vs. RHE (reversible hydrogen electrode), carbon is oxidized into CO2. [3] At potentials encountered in normal PEMFC operation (0.6 -0.9 V) the kinetics of the oxidation reaction are sluggish, while under dynamic processes, such as start-up and shut down, it is accelerated as a direct consequence of high potential values reached by the cathode, for example due to local fuel starvation [START_REF] Reiser | [END_REF] (≥ 1.2 V). Furthermore, the presence of Pt particles accelerates the phenomenon catalyzing the reaction by providing highly reactive transient oxygen radicals. [5] Carbon corrosion results in detachment/agglomeration of catalyst nanoparticles and a decrease in active surface area and performance, as well as in an increase in hydrophilicity and loss of porosity of the catalyst layer which negatively affect the mass-transport of gases and water management. [2b] Concerning the degradation of the nanocatalyst, it must be considered that under standard conditions platinum is thermodynamically unstable at pH values lower than 0 and at potentials greater than 1.0 V, and that the increase in potential and temperature is detrimental for the catalyst stability. [6] Together with the detachment related to support oxidation, three other mechanisms are reported in literature: [2e, 7] Pt nanocrystal migration and coalescence, and Pt dissolution and re-precipitation on the support (electrochemical Ostwald ripening) or in the membrane ("Pt band"). Poisoning of the Pt surface with contaminants from the fuel and air, such as COx, NOx, SOX, H2S, NH3 and small organics, leads to the loss of electrocatalyst activity and fuel cell performance. [8] Several strategies are employed to mitigate the degradation of PEMFC electrodes. To enhance the stability of the Pt based electrocatalyst, several alloys with noble and non-noble metals in binary and ternary catalysts have shown to be an effective route against dissolution and detachment. [9] Use of core-shell nanoparticles and tuning of the catalyst morphology have also proved to be elegant approaches to improve the performance of Pt-based electrocatalysts. [10] In order to avoid support corrosion, novel carbon nanostructured materials e.g. carbon nanotubes and nanofibers have been developed demonstrating improved stability. [11] In this regard electrospinning has emerged as a straightforward and readily up-scalable method to prepare 1D nanomaterials applicable in fuel cell electrodes. [12] Another approach is to replace carbon by alternative materials such as transition metal oxides, e.g. TiO2 and SnO2, with intrinsic high electrochemical stability. [13] The interaction of such oxides with platinum may also promote electrocatalytic activity through the so-called strong-metal-support-interaction. [14] Nevertheless, the drawback of metal oxides in general, is their low electrical conductivity that can in some cases be overcome by doping [15] or by using carbon based composite materials. [16] In this work a promising composite electrocatalyst support material was elaborated based on electrically conducting carbon nanofibres (CFs) prepared by electrospinning and decorated with non-conducting stabilizing SnO2 using atomic layer deposition (ALD). In particular, the protecting tin oxide was deposited directly onto the Pt decorated CFs. This approach has been recently applied in heterogeneous catalysis, where porous Al2O3 ALD film stabilized Pd particles [17] and in electrocatalysis where ZrO2 was deposited around Pt particles previously protected with an organic layer. [18] Morphology, surface analysis, electrocatalytic properties towards ORR and the electrochemical degradation of such novel electrocatalysts were investigated. The addition of SnO2 permitted a remarkable increase of the catalyst durability without reducing Pt activity. So far ALD has been coupled to electrospinning to prepare a Pt electrocatalyst on fibers [19] . Here ALD allows the protection of both the electrocatalyst and the support, while keeping intact their intrinsic catalytic activity and electrical conductivity, respectively. The unhindered activity may result from the very low and controlled amount of material deposited on the one hand, and the preferential growth of tin dioxide on the carbon fibers on the other hand.

Results and discussion

The CFs comprise electrospun polyacrylonitrile fibers stabilized at 280 °C and graphitized under inert atmosphere at 1000 °C. The as-obtained fibers present an ID/IG ratio in Raman spectroscopy of 1.7 comparable to that of commercial carbon nanotubes. [20] Investigation of the electrical properties using a four probe method demonstrates electrical conductivity comparable to that of carbon black Vulcan XC-72, a conventional electrocatalyst support. [21] Pt nanoparticles (NPs) were deposited onto the fibers using a microwave assisted polyol method. [22] TEM images (Figure 1) show a quite good Pt dispersion with a few aggregates. The size distribution (see Table SI.1 in Electronic Supplementary Information ESI and Figure 1b) is centered at 2.3 ± 1.0 nm, while a domain size of 2.9 nm was determined by XRD. A small amount of SnO2 was deposited in a controlled manner using a non-aqueous sol-gel ALD approach. [23] The number of ALD cycles was set for ~1 nm thick SnO2 coating on Si reference wafer. No noticeable change on Pt nanoparticle distribution (Figure 1 and Table SI.1) was observed after deposition. It was previously demonstrated that the SnO2 deposition approach used leads to granular rather than continuous coating, especially on graphitized carbon. [23][24] However, no clear evidence of SnO2 is visible in TEM images due to the very low amount of SnO2 deposited and the amorphous state of the oxide. [22] Indeed, the HRTEM images in Figure 2 show that after ALD the Pt surface remains clean and comparable to uncoated CFs. Dark field STEM image recorded on coated samples (Figure 2d) reveals tiny clusters (red arrows), almost not visible in bright field (Figure 2c), dispersed onto the carbon, which could be attributed to SnO2 XPS analyses were performed on SnO2-coated samples to confirm the presence of the metal oxide and the Pt loading. Table SI.2 reports the weight percentage of Pt, Sn, O and C in the sample. In the high resolution scan across the Sn 3d region of Figure 3a the two Sn3d5/2 peaks at 486.9 eV and 495.3 eV confirm the presence of tin in an oxidized state. [23,25] The calculated stoichiometric ratio Sn/O in our samples, utilizing the O 1s peak at 530.7 eV attributed to the metal oxide, is 0.54, in good agreement with value reported in the literature [15a] and confirms the presence of tin in the oxidation state (IV). [26] Platinum, tin, oxygen and carbon were also observed in the survey spectrum. Looking at the high resolution scan across the Pt 4f region (Figure 3b) mostly Pt in 0 oxidation state is detected. It is worthy to note a very small shift of the two Pt4f5/2 and Pt4f7/2 peaks to lower binding energy compared to Pt/CFs, which can be attributed to a slight increase of the local electron density due to charge transfer from SnO2 to Pt resulting from strong metal-metal oxide interaction. [27] In order to evaluate the impact of the presence of tin oxide on the electrocatalyst accessibility and performance, cyclic voltammetry (CV) in a N2 saturated 0.5 M aqueous H2SO4 was performed and is presented in Figure 4a. Similar profiles are observed for Pt/CFs with and without SnO2. Both electrocatalysts clearly showed H adsorption and desorption peaks at 0.05-0.3 V [28] as well as PtO formation and reduction peaks at 0.7-0.9 V. The Pt electrochemically active surface area (ECSA) was determined from H adsorption and desorption: no significant change of ECSA is noted between Pt/CFs (27 m 2 /gPt) and SnO2-decorated Pt/CFs (29 m 2 /gPt). Similar and comparable values have been previously reported for other carbon nanofiber based Pt catalysts with similar loading. [11c, 29] Thus, the presence of SnO2 does not seem to influence the overall electrochemical behavior of the samples, proving that the coating does not prevent reacting species from reaching the catalyst. One can therefore conclude that the deposited SnO2 particles does not cover the Pt NPs, but must be preferentially deposited onto the carbon support. This is also supported by the fact that a retarded nucleation process on noble metal substrates was already demonstrated in the literature. [30] Indeed an onset of deposition was noted on a Pt support; [30a] in the case of HfO2 ALD from HfCl4 and H2O, 30-50 cycles are required to initiate the growth. [30c] This behavior has been attributed to the relative inertness of noble metals toward hydroxylation that is required for the creation of anchoring sites. [30b] No oxide is present to initiate the growth and different mechanisms that on oxide or silicon may occur at the early stage, e.g. it was shown that Pt surface provides a different bonding environment for ALD HfO2. [31] Furthermore a significant lattice mismatch between Pt and metal oxide may also restrict the nucleation of grains leading to a nucleation delay. [30b] Considering the growth rate and the low number of cycles performed here (20 cycles), no real growth on the Pt NP surface may occur as the offset may have not been reached, even though deposition of few SnO2 clusters on the metal particles cannot be completely excluded. On the other hand, the functional groups available on the surface of carbon fibers promote the nucleation of SnO2 even after only few cycles. [32] Therefore, SnO2 should grow preferentially from oxygen functional groups present onto the carbon substrate in proximity to the Pt catalyst nanoparticles, permitting a strong metal-metal oxide interaction without significant shielding effect. A schematic representation of the electrocatalyst surface is shown in Figure 5. To confirm that the electrocatalyst activity is not hindered by the presence of tin dioxide, ORR was performed in an O2 saturated 0.5 M aqueous H2SO4 at different rotating electrode speeds (Figure SI.2). No loss of the performance was noted in the presence of the metal oxide as shown by the ORR mass activities (Table SI.3). The calculated number of electrons involved in the oxygen reduction mechanism using the Koutechy-Levich analysis is ~ 4 for both electrocatalysts as expected for Pt, suggesting a mechanism that does not involve production of H2O2. [33] Furthermore, the corresponding kinetic currents involved were calculated and are reported in the Tafel plot in Figure 4b. Even though at low current density similar kinetic currents are noted for unprotected Pt/CFs and SnO2/Pt/CFs, a significant decrease in potential is observed for Pt/CFs compared to the SnO2 decorated electrocatalyst. This suggests a beneficial effect of SnO2-coated fibers at higher potential values, which we attribute to the proximity of platinum to the metal oxide and its promoting catalytic effect (Figure 5). In order to evaluate the durability of the electrocatalyst, an accelerated degradation protocol was applied by cycling from 0.6 to 1.2 V at 100 mV/s for 10,000 cycles and monitoring the electrochemical surface area decrease every 100 th cycle performing a CV from 0.05 to 1.2 V at 50 mV/s. Figure 6 presents the ECSA as a function of the cycle number and shows a reduced ECSA loss for the SnO2-decorated catalysts compared to pristine Pt/CFs electrocatalysts. In a previous study, the significant ECSA loss and thus catalyst degradation over cycling has been defined as the major issue for electrospun CFs. [21] SnO2-decorated Pt/CFs samples maintained an active surface area around 20 m 2 /gPt by the end of the cycling, while the loss of Pt active surface on unprotected carbon fibers was much more significant. The loss is halved with addition of SnO2 as reported in Table SI. 4 and thus a positive influence of SnO2 decoration with respect to degradation over cycling is clearly demonstrated. This result is in agreement with the high electrochemical stability reported in the literature of the metal oxide, used either as additive or as replacement for conventional carbon-based electrocatalyst supports. [15a, 34] To further confirm the protecting role of the tin oxide component on the Pt/CFs, an accelerated corrosion test was performed in conditions providing information on degradation under fuel starvation and reverse current at the cathode side (1.4 V/RHE, 80 °C, 0.5 M H2SO4, 2h). The corrosion is quantified in terms of loss of material by the effect of electrochemical oxidation. [35] For carbon based materials the corrosion reaction is well known: C + H2O → CO2 + 4H + + 4e -Ref [3b] From integration of the oxidation currents over time (oxidation charge) it is possible to estimate the carbon loss into CO2 from the Faraday law. Figure 6b presents the currents obtained versus time for ALD SnO2 protected and unprotected samples. It is evident that the oxidation charge is lower for the former (3.2 C/mg, carbon loss 12.6 %) than for the pristine CFs (5.3 C/mg, carbon loss 16.2 %). This accelerated test clearly proves that the metal oxide is able to cover and partially protect the carbon support from corrosion (see Figure 5). Finally, TEM studies were performed on the 5 % Pt loaded CF catalysts with and without SnO2 after CV prolonged cycling (Figure 7a,c). It is evident that the amount of Pt remaining on the fibers after 10,000 cycles is much higher on the SnO2 coated CFs (Figure 7b) than on the non-protected CFs (Figure 7a). A better dispersion of the particles is also observed in the presence of the oxide. For both samples, growth of Pt nanoparticles is noted with a size distribution (Table SI.1) increasing from ~2 nm before to either 7 nm or 4.9 nm after cycling for Pt/CFs and SnO2/Pt/CFs, respectively, indicating that Ostwald ripening is almost suppressed by SnO2 surrounding the noble metal particles (Figure 5). It must be also noted that a narrower particle distribution is obtained in the presence of the metal oxide (Figure 7b,d). Therefore the improved durability is probably related not only to the protection of carbon from corrosion but also to a better stability, adhesion and confinement onto CFs of Pt NPs in presence of SnO2.

Experimental

Polyacrylonitrile (PAN, Mw=150,000, Sigma Aldrich) based carbon fibers were prepared combining electrospinning with thermal treatment as already reported. [21] 8 % (w/w) PAN solution in N,N-dimethylformamide (DMF, 98%, Sigma Aldrich) was feed to a metallic needle via a syringe pump with a flow rate of 1 ml/h. An electric field of 15 kV was applied between the needle and a metallic rotating drum collector (from Linari Engineering) placed 10 cm away. As-prepared PAN fibers were collected in the form of non-woven mats. Fiber carbonization was realized by a twostep thermal treatment. First an oxidative stabilization was performed at 280 °C for 1 h followed by a carbonization for 1 h under N2 at 1000 °C using a heating ramp of 1 °C/min. CFs were loaded at 20 % (w/w) with Pt NPs synthesized by a microwave assisted polyol synthesis. [15a] Thermogravimetric analysis was performed in air up to 800 °C (10 °C/min) using a Netzsch TG 439 thermobalance to determine the Pt loading on Pt/CF electrospun fibers. After Pt deposition, the differently heat-treated CFs were coated with SnO2 by nonaqueous ALD. [23] Based on approaches used for CNT coating, [36] Pt/CFs were contained during the deposition inside of a "tea bag" made of Kevlar mat. Tin tert-butoxide and acetic acid were used as metal and oxygen source, respectively. [23] Depositions took place in exposure mode home-made reactor at 175 °C and 20 ALD cycles were performed. Structural characterization was performed by X-ray diffraction on a PANAlytical X'pert powder diffractometer equipped with CuKa radiation (λ = 1.542 Å). The Pt crystallite size was estimated by the Scherrer equation using the Pt(111) diffraction line at 39.7°. Bright field TEM images were acquired on a Philips CM 200 LaB6 microscope operated at 200 kV. Phase contrast and STEM images were acquired on a Jeol-ARM200F equipped with a cold field emission gun and operated at 200 kV. X-ray photoelectron spectroscopy was performed using a Physical Electronics PHI 5700 spectrometer with a nonmonochromatic Mg Kα radiation (300 W, 15 kV, hν = 1253.6 eV) as excitation source. Spectra were recorded at a 45° take-off angle by a concentric hemispherical analyzer operating in the constant pass energy mode at 25.9 eV, using a 720 µm diameter analysis area. Core level C 1s, O 1s, Pt 4f and Sn 3d signals were recorded. Powdered solids were mounted on a sample holder without adhesive tape and kept overnight in a high vacuum chamber before they were transferred inside the analysis chamber of the spectrometer. Each region was scanned with several sweeps until a good signal to noise ratio was observed. The pressure in the analysis chamber was maintained below 10 -7 Pa. PHI ACCESS ESCA-V6.0 F and Multipak 8.2b software packages were used for acquisition and data analysis. A Shirleytype background was subtracted from the signals. Recorded spectra were always fitted using Gauss-Lorentz curves in order to determine the binding energy of the different element core levels more accurately. The accuracy of the binding energy (BE) values was within ±0.1 eV. Electrochemical analyses were carried out in a three-electrode cell comprising a gold (chronoamperometry) or glassy carbon (other voltammetric characterizations) rotating disk electrode (RDE) (working electrode geometric area 0.196 cm 2 ), a reversible hydrogen electrode (RHE, reference electrode) and a platinum wire (counter electrode), and a Pine bipotentiostat model AFCBP1. All the potential values are referred to the RHE. Catalyst ink was prepared by mixing 10 mg Pt/CF catalyst with 108.5 µl of 5 % (w/w) aqueous/alcoholic solution of Nafion, 300 µl of ethanol and 30 µl of DI water. After 20 min of sonication, 7 µl of ink was deposited onto the electrodes and dried for 10 min to obtain a total Pt loading of 32 µg on the RDE tip. CV was performed in 0.5 M H2SO4 solution saturated with either N2 or O2 on glassy carbon electrode after deposition of the electrocatalyst. In particular ECSA determination was performed by CV in 0.5 M H2SO4 solution saturated with N2 cycling between 0.05 and 1.2 V (vs RHE) at a speed of 50 mV/s while ORR tests were performed by linear sweep voltammetry in 0.5 M H2SO4 saturated with O2 between 0.2 and 1.2 V (vs RHE) at a scan speed of 20 mV/s and RDE rotating speeds of 400, 900, 1600 and 2500 RPM. Cyclic voltammetry based accelerated degradation tests were performed by cycling between 0.6 and 1.2 V at 100 mV/s for 10,000 cycles measuring the ECSA every 100 th cycle at 50 mV/s. Potentiostatic accelerated stress tests were performed by holding the gold working electrode potential at 1.4 V vs RHE for 2 h in 0.5 M H2SO4 at 80 °C. Pt/CFs before and after SnO2 ALD were characterized by TEM using a LaB6 Philips CM 200 microscope working at 200 kV.

Conclusions

By combining original synthetic approaches, i.e. electrospinning, microwave-assisted synthesis and atomic layer deposition, a novel electrocatalyst was elaborated with significantly improved stability over cycling. The addition of SnO2 permitted a remarkable increase of the catalyst durability and even a slight increase in the Pt activity. Regarding the different characterizations presented in this work, it can be safely concluded that ALD of SnO2 allows the protection of both the electrocatalyst and the support, while keeping intact their intrinsic catalytic activity and electrical conductivity, respectively. Lower corrosion of the carbon support, moderate aggregation of Pt particles and improved stability, adhesion and confinement on CFs of Pt NPs were observed when the electrocatalyst is decorated with tin oxide. The protection of Pt/CFs with metal oxide halves the degradation of the electrocatalyst over prolonged electrochemical cycling. Furthermore unhindered activity of Pt was observed suggesting no growth on the noble metal and preferential grow of tin dioxide on the carbon fibers although metal -metal oxide interaction seems to occur due to the proximity between these CF-supported components. It must be stressed that the successful selective SnO2 decoration is only based on the difference in reactivity and density of anchoring sites of the Pt and CFs, without need of a protective organic layer around Pt, for example. Finally, this work certainly paves the way to the elaboration of modified carbon-based electrodes for fuel cells and related energy applications.

  Figure1. a, c) TEM images and b, d) particle distribution obtained from TEM analysis of a,b) Pt/CFs, c, d) SnO2/Pt/CFs before cyclic voltammetry.

Figure 2

 2 Figure 2. a, b HRTEM images of Pt/CFs and SnO2/Pt/CFs before cyclic voltammetry. c, d STEM images of SnO2/Pt/CFs in bright and dark field.

Figure 5 .

 5 Figure 5. Schematic representation of the SnO2(blue)/Pt(yellow)/CFs (black) surface.

Figure 3 .

 3 Figure 3. XPS spectra of SnO2/Pt/CFs (full line) and Pt/CFs (dotted line). High resolution scans across a) the Sn 3d and b) Pt 4f edges, respectively.

Figure 4 .

 4 Figure 4. Cyclic voltammetry at 50 mV/s in a 0.5 M H2SO4 solution saturated with N2. b) ORR Tafel plot for uncoated (dotted line) and SnO2-decorated carbon fibers (full line).

Figure 6 .

 6 Figure 6. a) ECSA of Pt/CFs (dotted line) and SnO2/Pt/CFs (full line) calculated from cyclic voltammetry at 50 mV/s in a N2 saturated 0.5 M H2SO4 solution every 100 cycles performed at 100 mV/s. b) Oxidation/corrosion characteristics for Pt/CFs (dotted line) and SnO2/Pt/CFs (full line) at 1.4 V/RHE.

Figure 7 .

 7 Figure 7. TEM images a,c) and b,d) particle distribution from TEM analysis of a,b) Pt 5% -CFs and c,d) SnO2-Pt 5% -CFs after 10,000 potential cycles.

Acknowledgements

The authors acknowledge R. M. Silva and I. Jiménez-Morales for their experimental support. The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 306682.


V Oborin
email: oborin@icmm.ru

M Bannikov

O Naimark

T Palin Luc

Scaling Invariance of Fatigue Crack Growth in Gigacycle Loading Regime

The role of the collective behavior of defect ensembles at the crack tip and the laws of fatigue crack propagation in R4 high strength steel have been studied under conditions of symmetric tension-compres sion gigacycle loading at 20 kHz. At every stage of the fatigue crack growth, replicas from the sample side sur face were taken and studied by the method of three dimensional relief profilometry (using NewView inter ferometer profilometer) so as to study the scaling invariant laws of defect related structure evolution.

The task of assessing the working resource of important structures, in particular, those for aircraft engines, poses qualitatively new basic problem related to evaluation of the reliability of materials under con ditions of cyclic loading in excess of 10 6 -10 10 cycles, which refer to the field of so called gigacycle fatigue. This interest is related to the fact that the resource of loading for many important parts operating under conditions of cyclic loading exceeds the so called multicycle range. the behavior of materials in the range of gigacycle fatigue reveals some qualitative changes in the laws governing both the nucleation of cracks (in the bulk of a sample) and their propagation, which are related to changes in the mechanisms of fatigue crack nucleation and propagation. In the range of gigacycle loading, the fatigue curve exhibits discon tinuities and the behavior shows evidence of a signifi cant increase in the role of environment, so that the problem acquires an interdisciplinary character.

The stages of material fracture in the range of giga cycle loading are classified based on the structural signs of damage related to a broad spectrum of spatial scales, including persistent slip bands (PSBs), fatigue striations, microcracks (formed as a result of PSB crossing), and grain boundary defects. The main damage refers to the defect scales within 0.1 μm-1 mm, which are significantly smaller than those detected by the standard methods of nondestructive testing used for the conventional monitoring of reli ability, in particular, during the exploitation of build ings.

An effective method for investigating the role of initial structural heterogeneity, monitoring the accu mulation of defects on various scales (dislocation ensembles, micropores, microcracks), and determin ing critical conditions for the transition from dispersed to macroscopic fracture is offered by the quantitative fractography. This technique reveals the characteristic stages of fracture (crack nucleation and propagation), thus providing a base for evaluating the temporal resource of materials and structures under conditions of gigacycle loading.

The approach to characterization of the fracture surface morphology in terms of spatiotemporal invari ants was originally proposed by Mandelbrot [START_REF] Mandelbrot | The Fractal Geometry of Nature[END_REF]. This method is based on an analysis of the relief of a frac ture surface, which exhibits the property of self affin ity as manifested by the invariant characteristics of the surrace relief (roughness) over a broad spectrum of spatial scales. On the other hand, these characteristics reflect a correlated behavior of defects on various scal ing levels.

The universal character of kinetic laws establishing a relationship between the growth rate dl/dN of a fatigue cracks and a change in the stress intensity coef ficient ΔK has been extensively studied both experi mentally and theoretically. The power laws originally established by Paris [START_REF] Paris | [END_REF] (and presently referred to as the Paris law) reflect the automodel (self similar) nature of development of fatigue cracks. This law is related to a nonlinear character of damage develop ment in the vicinity of the crack tip (called the "pro cess zone" [START_REF] Paris | [END_REF]):

(1) where C and m are the experimentally determined constants. For a broad class of materials and wide range of crack propagation velocities under multicycle fatigue conditions, the exponent is typically close to m = 3-4.

dl/dN C ΔK ( ) m , =
The universal nature of the Paris law was inter preted [3] based on the self similar laws of damage development and fracture focus formation in the form of "dissipative structures" representing ensembles of defects localized on the spectrum of spatial scales. The formation of these structures reveals a critical charac ter of the transition from dispersed to macroscopic fracture as manifested by the structural scaling transi tions [START_REF] Naimark | Advances in Multifield Theories of Continua with Substructure[END_REF]. According to these notions, the propagation of cracks is related to establishing a long range corre lation interaction in multiscale ensembles of dissipa tive structures. This interaction which can be charac terized by a certain correlation scale, above which the interaction proceeds to a scale that determines the subsequent increment in the length of the propagating crack (size of the "process zone"). This assumption concerning the critical conditions for the aforemen tioned transition was used in interpretation of the experimental data so as to explain the self similar sce nario of fatigue crack propagation in a steel sample under conditions of gigacycle loading.

The samples of R4 high strength steel (with a room temperature fatigue limit of 600 MPa for 10 6 cycles at 10 Hz) were tested under fatigue loading conditions with symmetric tension-compression cycling at 20 kHz (gigacycle loading regime) on an original setup [START_REF] Bathias | [END_REF]. The testing machine consisted of the following main parts: (i) generator, which con verted 50 Hz oscillations into an ultrasonic electric sinusoidal signal with a frequency of 20 kHz;

(ii) piezoelectric transducer, which generated longitu dinal ultrasonic waves and produced mechanical action at a frequency of 20 kHz; and (iii) ultrasonic waveguide, which increased the amplitude of mechan ical stresses in the (working) central part of the sample.

At the initial stage, a fatigue crack with a length of ~1.5 mm was nucleated, the subsequent growth of which was controlled by varying the amplitude of oscillations. The corresponding stress intensity coeffi cient ΔK was calculated by the following formula:

(2

)
where E is the Young's modulus, ν is the Poisson ratio, U 0 is the amplitude of oscillations, Y is the polynomial factor, and w is the sample width. For a given sample geometry (Fig. 1) the polynomial factor was as follows:

After every step of the fatigue crack growth, replicas from the sample side surrace were taken in order and to study the morphology of defect structures at the crack tip. Figure 2 shows the typical surface relief observed on a sample replica, which was obtained using a high resolution NewView interferometer. This profilometer ensured a vertical resolution of 0.1 nm and a lateral resolution of 0.5 μm. These patterns were analyzed using the methods of correlation analysis for determining the conditions of scaling invariance in the ensembles of structures, which were assumed to gov ern the subsequent stage of crack development.

One dimensional profiles obtained for the surrace of replicas were used to construct autocorrelation functions (ACFs) of the following type

The first nonzero value of the ACF was assumed to determine the critical scale l sc for establishing long range correlation interactions in the ensembles of defects formed in a process zone scale L pz (Fig. 2). The values of the critical scale l sc for various stages of crack propagation are presented in the table.

ΔK E 1 ν 2 - π l U 0 Y l/w ( ), = Y l/w ( ) 0.635 l/w ( ) 1.731 l/w ( ) 2 + = -3.979 l/w ( ) 3 1.963 l/w ( ) 4 . + Ψ r ( ) f x ( )f x r - ( ) x
Manifestations of the self similar nature of the fatigue crack growth were studied using methods of the theory of similarity and dimensionality [6,7]. The crack growth rate was defined as a = dl/dN (where l is the crack length and N is the number of cycles) and studied as for correlation with the following parame ters: a 1 = ΔK, stress intensity coefficient; a 2 = E, Young's modulus; a 3 = l sc , correlation scale in the ensemble of defects; a 4 = L pz , the scale related to the process zone. where α is a universal exponent.

Using relation (6), which constructed based on the results experimental investigation of the fatigue crack growth kinetics with allowance for the calculated l sc values, it is possible to estimate the exponent as α 2.3, which corresponds to the slope of the straight line in the rectifying coordinates (Fig. 3). A difference of the exponent α ~ 2.3 from values obtained in the regimes of multicycle fatigue testing suggests that there are certain specific features in the formation of frac ture regions in the vicinity of crack tip under condi tions of gigacycle loading.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Schematic diagram and characteristic dimensions of the initial sample (in millimeters).

  Using the Π theorem and taking into account the dimensionality of variables [dl/dN] = L, [ΔK] = FL ⎯3/2 , [l sc ] = [L pz ] = L, and [E] = FL -2 , the kinetic equation for the crack growth (3) dl dNΦ ΔK E l sc L pz , values ΔK/(E ) Ӷ 1 and L pz /l sc ӷ 1 suggest an intermediate asymptotic character of the crack growth kinetics for Eq. (4) in the following form:(5) where = l/l sc . Introducing the parameter C = (L pz /l sc ) β , we can reduce the scaling relation (3) to the following form analogous to the Paris law:(6)

Fig. 3 .

 3 Fig. 3. Rectified plot of relation (6).

Acknowledgments. This study was supported in part by the Russian Foundation for Basic Research, Project nos. 08 01 00699, 09 01 92005 NNS_a, and 09 01 92441 KE_a.


Kevin Fournier
email: kevin.fournier@ehesp.fr

Cleo Tebby
email: cleo.tebby@ineris.fr

Florence Zeman
email: florence.zeman@ineris.fr

Philippe Glorennec

Denis Zmirou-Navier

Nathalie Bonvallot
email: nathalie.bonvallot@ehesp.fr

Multiple exposures to

Keywords: semi-volatile organic compounds, benchmark doses, cumulative risk assessment, reproduction, mixture, toxicity

Introduction

Semi-volatile organic compounds (SVOCs) include numerous molecules belonging to different chemical families such as phthalates, polycyclic aromatic hydrocarbons (PAHs), musks, polybromodiphenyl ethers (PBDEs), polychlorobiphenyls (PCBs) or pyrethroid insecticides [START_REF] Weschler | Semivolatile organic compounds in indoor environments[END_REF]. They can be defined as "organic compounds with vapour pressures between 10 -14 and 10 -4 atm (10 -9 to 10Pa)" and whose boiling point is between (240 to 260°C) and (380 to 400°C) (NF ISO 2006) [START_REF] Weschler | Semivolatile organic compounds in indoor environments[END_REF]. They are used for their technical properties in a large variety of building materials and consumer products (plastics, paints, cleaning agents, biocides, furniture, etc.), and are also emitted by combustion processes. Due to their widespread usage and chemical properties, their presence is ubiquitous in indoor environments, in both settled dust and air (gaseous phase and particulate matter) (Mercier et al., 2011, Blanchard et al., 2014). Many SVOCs are suspected of having endocrine disruption mechanisms, leading to potential effects on male reproduction. Among them, phthalates are considered anti-androgenic compounds, responsible for an inhibition of steroidogenesis [START_REF] Svechnikov | Inhibitory effects of mono-ethylhexyl phthalate on steroidogenesis in immature and adult rat Leydig cells in vitro[END_REF], leading to a decrease in anogenital distance and nipple retention, as well as an increase in the incidence of hypospadias and cryptorchidism in rats exposed during the prenatal period (Gray et al., 2000). A significant decrease in serum testosterone levels was observed in rodents following oral exposure to BDE-99 [START_REF] Alonso | Effects of BDE-99 on hormone homeostasis and biochemical parameters in adult male rats[END_REF], benzo[a]pyrene (B(a)P) [START_REF] Liang | Neonatal exposure to benzo[a]pyrene decreases the levels of serum testosterone and histone H3K14 acetylation of the StAR promoter in the testes of SD rats[END_REF] or cypermethrin [START_REF] Jin | Cypermethrin exposure during puberty induces oxidative stress and endocrine disruption in male mice[END_REF]. In addition, in rats, cypermethrin decreases expression of the androgen receptor after 2 weeks of oral exposure [START_REF] Liu | Effects of beta-cypermethrin on male rat reproductive system[END_REF].

The effects of bisphenol A (BPA) on testosterone synthesis may be controversial, yet further studies have shown BPA to have negative effects on this hormone. For example, Salian et al. observed a significant decrease in testosterone concentration in rats pre and postnatally exposed M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT [START_REF] Salian | Perinatal exposure of rats to Bisphenol A affects the fertility of male offspring[END_REF]. Della Seta et al. observed the same phenomenon following exposure from postnatal day 23 to postnatal day 30 (Della Seta et al., 2006).

In humans, authors have demonstrated in vitro endocrine disruption properties for a mixture including phthalates and BPA [START_REF] Christen | Antiandrogenic activity of phthalate mixtures: validity of concentration addition[END_REF] and also for DEHP and MEHP alone (Desdoits-Lethimonier et al., 2012). SVOC endocrine properties have also been suggested through epidemiological studies. Hauser et al. observed a dose-dependent negative association between monobutyl phthalate (MBP) and sperm concentration and motility in a population of 463 male partners of subfertile couples (Hauser et al., 2006). Others groups found similar results between MBP and MEP exposure, and sperm mobility / concentration (Duty et al., 2003); metabolites of long-chained phthalates (MEHP and MiNP) and testosterone production [START_REF] Meeker | Urinary metabolites of di(2-ethylhexyl) phthalate are associated with decreased steroid hormone levels in adult men[END_REF]; MBP and MEHP and serum-free testosterone [START_REF] Pan | Decreased Serum Free Testosterone in Workers Exposed to High Levels of Di-n-butyl Phthalate (DBP) and Di-2-ethylhexyl Phthalate (DEHP), A Cross-Sectional Study in China[END_REF]; flame retardant (PBDEs) and serum testosterone concentration [START_REF] Johnson | Associations between brominated flame retardants in house dust and hormone levels in men[END_REF], and sperm quality [START_REF] Abdelouahab | Polybrominated diphenyl ethers and sperm quality[END_REF]; BPA and male sexual function [START_REF] Li | Occupational exposure to bisphenol-A (BPA) and the risk of self-reported male sexual dysfunction[END_REF] or semen quality [START_REF] Meeker | Semen quality and sperm DNA damage in relation to urinary bisphenol A among men from an infertility clinic[END_REF]. Alteration of protein expression can represent important key events in a modes of action (MOAs), or molecular initiating event in an adverse outcome pathways (AOPs), leading to an adverse outcome [START_REF] Chepelev | Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity[END_REF]. Sonich-Mullin defined MOA as a "biologically plausible series of key events leading to an effect" [START_REF] Sonich-Mullin | IPCS conceptual framework for evaluating a mode of action for chemical carcinogenesis[END_REF]). An AOP is conceptually similar to a MOA but includes an initial point of interaction of a chemical with biological systems (Meek et al., 2014). It is difficult to know and understand the entire MOA/AOP leading to reprotoxic effects but with a view of the preview information, we can consider the alteration of protein synthesis (e.g. testosterone) as a potential early key event leading to reprotoxic effects.

As underline by Chepelev, protein expression analysis could contributed in health risk assessment [START_REF] Chepelev | Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity[END_REF]. Thus, Cumulative Risk Assessment (CRA) could be used to address this

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concern, with a view to assessing whether environmental exposure levels to SVOCs pose a risk, and to help set maximum exposure levels not to be exceeded in indoor environments. A variety of CRA methodologies have already been suggested and recently reviewed (Fournier et al., 2014a). Some of them, including toxic equivalency factors (TEF) and relative potency factors (RPF) approaches have been used to identify relative toxic potencies on various chemical mixtures. This is the case of dioxins and PCBs [START_REF] Ahlborg | Toxic equivalency factors for dioxin-like PCBs[END_REF]; polychlorinated dibenzo-p-dioxins (PCDD) [START_REF] Ome | Scientific criteria document for standard development, No. 4-84. Polychlorinated Dibenzo-p-Dioxins (PCDDs) and Polychlorinated DibenzoFurans (PCDFs)[END_REF]; pesticides (Jensen et al., 2013) and PAHs [START_REF] Nisbet | Toxic equivalency factors (TEFs) for polycyclic aromatic hydrocarbons (PAHs)[END_REF].

These approaches are based on the dose additivity assumption [START_REF] Loewe | Effect of combinations: mathematical basis of problem[END_REF] as suggested by the US EPA (US EPA, 2002) and consider a common mode of action (US EPA, 2000). This assumption does not take into account the possibility of toxicological interactions that are not, or are rarely expected with exposure to low doses of contaminants (ATSDR, 2004).

These approaches were extended to other SVOCs including phthalates, fungicides or pyrethroids [START_REF] Christiansen | Mixtures of endocrine disrupting contaminants modelled on human high end exposures: an exploratory study in rats[END_REF]Hannas et al., 2011;[START_REF] Kortenkamp | Combined exposures to anti-androgenic chemicals: steps towards cumulative risk assessment[END_REF][START_REF] Wolansky | Relative potencies for acute effects of pyrethroids on motor function in rats[END_REF], but none of them is based on real exposure, where a variety of chemical families are encountered.

The aim of this work is to estimate RPFs based on comparable benchmark doses (BMDs) for multiple reprotoxic contaminants present in indoor environments. The choice of the BMD rather than the NOAEL/LOAEL as an indicator of the toxicity was decided to reduce uncertainty due to data heterogeneity (EFSA, 2006).

Material and Method

Selection and grouping of indoor SVOCs

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The selection of chemicals was made on the basis of different measurement campaigns in French dwellings (Mandin et al., 2014a(Mandin et al., , 2014b ; ;Blanchard et al., 2014), where 66 compounds selected from a previous ranking [START_REF] Bonvallot | Health ranking of ingested semi-volatile organic compounds in house dust: an application to France[END_REF] were simultaneously analysed in a range of environmental media (air, gas phase or particle matter, settled dust) using a multi-residue method [START_REF] Mercier | Analysis of semivolatile organic compounds in indoor suspended particulate matter by thermal desorption coupled with gas chromatography/mass spectrometry[END_REF][START_REF] Mercier | A multi-residue method for the simultaneous analysis in indoor dust of several classes of semi-volatile organic compounds by pressurized liquid extraction and gas chromatography / tandem mass spectrometry[END_REF]. SVOCs were selected where they were detected in more than 10% of the investigated houses (from 30 to 285 according to the campaign).

SVOC grouping was based on our previously described approach (Fournier et al., 2014b).

Briefly, hazard identification, for each chemical, was performed by means of a literature review on its reprotoxic effects. To be eligible, the toxicological studies (in vivo or in vitro) should describe the target organs or cells, or the mechanisms of action on the male reproductive system or organs. SVOCs were then grouped by common effect, mode and/or mechanism of action.

According to the data, and in order to estimate RPFs, we chose to select the group including the largest number of SVOCs, and for which a biological pathway is known.

Benchmark doses derivation

The BMD is defined as a dose (or concentration) producing a predetermined change in the response rate of an effect (known as the benchmark response or choice of BMR, iii) fitting models using experimental data, and iv) selection of the best fitting model.

For each compound, we based our BMD calculation on one selected study, describing the most robust dose-response dataset. This kind of approach was also applied recently by Chepelev in

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order to derive BMDs for the protein expression involved in testicular toxicity [START_REF] Chepelev | Application of benchmark dose modeling to protein expression data in the development and analysis of mode of action/adverse outcome pathways for testicular toxicity[END_REF].

Selecting dose-response datasets

For each SVOC, available dose-response datasets were collected and selected on the basis of a compromise between the amount of data available and comparability of the data between compounds. The following criteria were used: i) availability of data for at least 3 dose levels and 1 control group; ii) same species (though not necessarily the same strain); iii) same window of susceptibility (but not necessarily the same exposure duration); iv) same exposure route; v) availability of raw data or means and standard errors of the means (SEM) or standard deviations (SD) for each selected response. Where SDs were not provided in the publication and could not be collected from the authors, a graphical estimation was made as described by the US EPA (US EPA, 2005). If only SEMs were given, these were converted to SDs using the following equation:

, where n is the sample size.

Choice of BMR for a common effect

The response chosen should be linked to a reproductive effect and related to a maximum number of SVOCs in order to consider a CRA. The Benchmark Response (BMR) is associated with the BMD as a change in response relative to background [START_REF] Crump | A New Method for Determining Allowable Daily Intakes[END_REF]. According to the data, this response could be continuous (e.g., relative change from the control) or dichotomous (e.g., presence or absence of an effect) (US EPA, 2012). In case of RPF derivation, the response should either be linked to a specific mechanism of action or a consequence of a common mode of action (a biological pathway leading to an adverse effect on the reproductive system). Because this

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response occurs at organism or cellular scale, it is a continuous response. Response rates in each dataset were expressed as a proportion of the background response rate (i.e. background=1).

Where the adverse effect threshold is unknown, the BMRs used in this study will be default values recommended by the US EPA (e.g., a decrease of 1 control SD for continuous datasets and 10% for dichotomous dataset) or a response level that would be qualified as adverse.

Selection of the best fitting model

BMDs were computed using the PROAST software (www.rivm.nl/proast v32.2). The data was continuous summary data (raw data was rarely available) and the Hill family of models was selected for modelling the dose-response relationships, as follow in equations 1 to 4 (2 to 4 parameters):

+ - = x b x a y 1 + - = d d d x b x a y 1 ( ) + - + = x b x c a y 1 1 ( ) + - + = d d d x b x c a y 1 1
Where x is toxic compound concentration, a is the background response, b is the concentration of the compound inducing 50% of the effect, d is the slope, and a*c is the response to an infinite dose. The best fitting model from the Hill family was selected according to the procedure described by Slob [START_REF] Slob | Dose-response modeling of continuous endpoints[END_REF] with the likelihood ratio test. This tests whether increasing the number of parameters in a model results in a statistically significant improvement to fit.

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RPF estimation

RPFs were estimated using the previously-derived BMDs, according to the equation below:

Where RPF i is the RPF of the compound "i"; BMD i is the BMD of the compound "i"; BMD ref is the BMD of the reference compound.

RPFs express the potency of a compound "i" according to the reference compound. This reference compound can be the most toxic compound within a group of compounds, or the most documented for the selected effect.

Results

Fifty-eight SVOCs were selected based on the criteria described in the previous section, and are presented in table 1. Of these, 23 were documented as having male reprotoxic properties regardless of the mode or mechanism of action. A more precise description lead to the identification of 3 groups having different modes of action and potentially acting via different biological pathways. These pathways are summarized in figure 1 (adapted from Fournier et al.

2014a).

The group including the largest number of SVOCs -and for which the biological pathway is known -is the group whose effect is described as decreasing the concentration of steroidogenesis enzymes, resulting in a lower testosterone level; 18 SVOCs were concerned.

Benchmark Doses Derivation

Selection of Dose-Response Datasets

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Dose-response datasets meeting our selection criteria were available for just 6 of the 18 compounds acting on steroidogenesis enzymes. The response measured in the toxicological studies was the serum concentration of testosterone after oral-route exposure of adult male rodents. Lindane, dieldrin, alpha-endosulfan, chlorpyrifos-ethyl, deltamethrin, triclosan, 4-tertoctylphenol and BDE-99 were excluded because there was no available dose-response relationship for this effect (only one-and two-tested doses, respectively). Four other SVOCs were excluded (permethrin, DBP, DiBP, DiNP) due to lack of comparable data (exposure of rodents during different windows of susceptibility, i.e. pre-or post-natal).

The central estimation (BMD) was used as the basis for calculation of RPFs rather than the BMDL (Benchmark Dose Lower Bound = lower limit of a one-sided confidence interval on the BMD) which integrates uncertainty to experimental data, as suggested by the US EPA in 2010 (US EPA, 2010).

Table 2 briefly summarizes the selected study protocols and the decrease in serum testosterone relative to control results. In each case, dose-response data was obtained in adult rats orally exposed through sub-chronic to chronic exposure (15 to 150 days). There are 9 orders of magnitude between the highest dose tested (for DEHP) and the lowest one (for BPA).

Choice of Response and BMR

Serum testosterone concentration was measured in all studies. A decrease in this response was observed according to dose. It is reasonable to consider that this decrease may be linked to adverse effects such as cryptorchidism, hypospadias or male fertility impairment, depending on the window of susceptibility, as suggested by a group of experts of the United Nations Environment Programme (UNEP) and WHO (WHO/UNEP, 2013). Two different BMRs were chosen: a 10% and a 50% decrease in response compared to control serum testosterone. We

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consider a decrease of 50% of the serum testosterone to be significant (equivalent to the highest documented standard deviation in our selected SVOCs). The use of a BMR equivalent to 1 control standard deviation from the control mean is recommended by the US EPA (US EPA, 2012). The use of 10% as a BMR is intended to compare contaminants' toxicity at lower doses, though authors consider this effect size not meaningful. Eisenberg and colleagues observed a 10% difference in testosterone concentration between fertile and infertile men (Eisenberg et al., 2011). Furthermore, a 10% decrease in serum testosterone corresponds to the lowest documented standard deviation in our selected SVOCs.

BMD Estimations

The corresponding BMD 10 and BMD 50 are shown in table 3 (associated graphs are shown in supplementary data). Equation 2, with 3 estimated parameters and a null response at infinite doses, was selected for BPA. Equation 3, with 3 estimated parameters, slope equal to 1 and a non-null response at infinite doses, was selected for DEHP. Equation 1, with 2 free parameters, slope equal to 1 and a null response at infinite doses, was selected for the other four SVOCs.

Since the response at infinite doses is equal to 0, BMD 50 is the dose resulting in a 50% decrease relative to the background response. Resulting RPFs for a 10% (RPF 10 ) and 50% (RPF 50 ) decrease are shown in table 4. The control values were included in the BMD calculations.

Discussion and Conclusion

In this study, we derived BMDs for 6 SVOCs pertaining to different chemical families to which people are exposed in indoor environments, leading to RPF for BBP, BPA, B[a]P, DEP, DEHP

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and cypermethrin. We have adapted the traditional risk assessment approach (NRC, 1983) by adding a grouping step, depending on SVOCs' effects, as suggested in our previous work (Fournier et al, 2014b). This was done on the basis of their mode of action. In a second step, we calculated BMDs for the 6 SVOCs for which we were able to obtain sufficient information, which in turn allowed RPFs to be derived.

The RPFs calculation is based on the dose additivity assumption because it seems to best describe the reality of mixture toxicity. In fact, the toxic equivalency and dose additivity models have already proved their potency in the mixture effects prediction. For example, [START_REF] Rider | A mixture of seven antiandrogens induces reproductive malformations in rats[END_REF] tested different hypotheses for predicting mixture reproductive effects in male offspring rats exposed during the period of sexual differentiation [START_REF] Rider | A mixture of seven antiandrogens induces reproductive malformations in rats[END_REF]. They compared the observed responses from a mixture of 4 pesticides and 3 phthalates with predicted responses generated using a toxic equivalency approach and dose addition, response addition or integrated addition models. They validated the dose additivity assumption and showed that toxic equivalency and dose addition models provide the best fit to their observed responses even for chemicals from different families which do not necessarily act via the same cellular mechanism of action. There were several reasons for basing our RPF calculation on a 10% and 50% decrease in testosterone synthesis (BMD 10 and BMD 50 ), defined respectively as RPF 10 and RPF 50 . First of all, as mentioned above, we do not know which level of inhibition of testosterone is harmful to human health. In this case, the US EPA recommends the use of an endpoint that is equivalent to a decrease of 1 control SD (US EPA, 2012). In our case, we have chosen to apply respectively the smallest and the largest of the documented control SDs (near 50% for BBP and 10% for BPA) for the choice of BMR.

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We chose cypermethin as the index compound because its range of tested doses is intermediate among those tested for the other SVOCs. The difference in ranges of tested doses and toxicity between contaminants yields a large range of RPF values (a factor of 10 9 between BPA and BBP for RPF 10 , a factor of 10 6 between B[a]P and BBP). The choice of the reference compound, however, modifies neither the toxicity of each contaminant nor the order of their potency for the effect of interest.

According to the RPF 10 , BPA shows the most toxic among the considered SVOCs (7,033,679 times more potent than cypermethrin for this effect) and BBP the least toxic (10.5 times less potent than cypermethrin). According to the RPF 50 , B(a)P seems to be the most toxic (1,630 times more potent than cypermethrin for this effect) and BBP the least one (10.5 times less potent than cypermethrin).

For a 50% reduction in testosterone levels, we can observe that B(a)P is more toxic than BPA, while this latter is most potent at 10% of the effect. According to our data, BPA is the most potent of of the study SVOCs at low doses. This is due to the difference between BPA and the other SVOCs in terms of the slope of the curves (inclusion of the "d" parameter, see equation 2).

Our data does not allow to derive a BMD 50 (and RPF 50 ) for DEHP because, according to the Hill equation used by PROAST, when the DEHP concentration is infinite, the response (decrease in serum testosterone concentration) only approaches 0.43 (=BMD 43 ). The derivation of a BMD 50 for the DEHP could be performed with other data which investigated the same response, but specifically in pubertal rats [START_REF] Noriega | Pubertal administration of DEHP delays puberty, suppresses testosterone production, and inhibits reproductive tract development in male Sprague-Dawley and Long-Evans rats[END_REF]. According to this data, the BMD 10 would be 102.45 mg/kg bw/day and the BMD 50 922.07 mg/kg bw/day.

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We see here that the BMD 10 based on adult data from Tonk et al. is 20 times lower than the BMD 10 based on pubertal rat from Noriega et al. This comparison shows that the toxic potency of DEHP compared to other compounds could be modified regarding to the window of exposure, leading difficult the extrapolation of the "pubertal" BMD 50 to an "adult" BMD 50 .

In our case, three SVOCs (B[a]P, DEP and BBP) had parallel dose-response curves compared to the reference compound's curve (cypermethrin) with a slope equal to 1 and a response at infinite concentrations equal to 0. On the other hand, for DEHP, at infinite concentrations, the response only approaches 0.43 rather than 0 and for BPA, the slope was different from 1. In these cases, the dose-response curves were not parallel compared to the reference. Thus, from a statistical point of view, the RPFs for B[a]P, DEP and BBP are more reliable than those for DEHP and BPA.

The main limitation of this work in a perspective of CRA for chemicals humans are exposed to, is the lack of available and comparable data in the scientific literature. Among the 58 SVOCs that were considered, others than the one we could include might be reprotoxic, but no study has been published to date. Only 23 have been documented as having reprotoxic properties. Of these, 18 are able to decrease testosterone synthesis. At the final step, the literature provided sufficient comparable information for BMD calculation only for 6.

This limitation of the available information was recently underlined by Wignall et al. in their standardization of BMD calculations [START_REF] Wignall | Standardizing benchmark dose calculations to improve science-based decisions in human health assessments[END_REF]. Another impediment is the lack of comparability of the data in terms of the range of tested doses, windows of exposure, animal strain, time of exposure, etc. The most striking example is the tested doses range, from 0.000005 mg/kg bw/day for BPA, to 1000 mg/kg bw/day for DEHP, suggesting that BPA is the most

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potent toxic SVOC of our group for the study effect (abatement of serum testosterone concentration); however, its action remains a subject of controversy in the literature. Our requirements in term of data comparability (same species, same window of exposure, etc.) and obviously the lack of data availability limit the datasets for our RPF computations. The more precise and comparable we require our data to be, the less such data is available.

There is no data to compare with in the literature regarding RPFs derived from a variety of chemical families. Among phthalates, RPFs were derived for DEHP and BBP acting on testosterone synthesis [START_REF] Benson | Hazard to the developing male reproductive system from cumulative exposure to phthalate esters--dibutyl phthalate, diisobutyl phthalate, butylbenzyl phthalate, diethylhexyl phthalate, dipentyl phthalate, and diisononyl phthalate[END_REF]Hannas et al., 2011). In his CRA, Benson derived RPF for 6 phthalates including DEHP and BBP. For DEHP, the endpoint was smallness -or absence ofmale reproductive organs. For BBP (and the 4 other phthalates), the endpoint was decrease in foetal testosterone production. The resulting RPFs were 1 and 0.21, based on the IC95 lower bound of the BMD 10 or the IC95 lower bound of the BMD corresponding to one standard deviation for DEHP and BBP respectively. According to this method, DEHP appears to be 5 times more potent than BBP, which is in line with our findings (10 times more potent according to BMD 10 ). This difference in potency might be explained by the use of different toxicity indicators (BMDL versus BMD), the use of two different endpoints (small or absent male reproductive organs for DEHP and a decrease in testosterone production for BBP), and a different window of exposure (prenatal period for Benson, adult age for our work). For RPF calculations, it is very important to use comparable data and the same endpoint in order to conduct a robust CRA. Also, future experiments should strive to standardise protocols (animals tested, time of exposure, etc.) as well as the ranges and number of doses tested, which should be as close as possible to human real exposures, allowing us to establish a dose-response curve.

Our approach takes into account actual population exposures, compounds from different chemical families, and common effects and modes of action of SVOCs. For these reasons, we think it is realistic and useful for future CRA studies. Research must continue in this direction to improve the consideration of actual exposures in CRA. 1 (Gray et al., 2000); 2 (Pan et al., 2006); 3 (Borch et al., 2006); 4 (Pereira et al., 2008); 5 [START_REF] Abdelouahab | Polybrominated diphenyl ethers and sperm quality[END_REF]; 6 (Alonso et al., 2010); 7 (D'Cruz et al., 2012); 8 (Chung et al., 2011); 9 (Kuriyama and Chahoud, 2004); 10 (Saradha et al., 2009); 11 (Ronco et al., 2001); 12 (Zhang et al., 2007); 13 (Hu et al., 2011); 14 (Singh and Pandey, 1990); 15 (Schein and Thomas, 1975); 16 (Fiorini et al., 2004); 17 (Farag et al., 2010); 18 (Ismail and Mohamed, 2012); 19 (Kumar et al., 2009); 20 (Sainath et al., 2011); 21 (Wilson et al., 2004); 22 (Hannas et al., 2012); 23 (Mograbi et al., 2003); 24 (Posnack et al., 2015); 25 (Liu et al., 2005); 26 (Tonk et al., 2012); 27 (Nagao et al., 2000); 28 (Pereira et al., 2008); 29 (Jiang et al., 2007); 30 (Borch et al., 2004); 31 (Shi et al., 2010); 32 (Jayachandra and D'Souza, 2014) Based on (Mandin et al., 2014a) ; (Mandin et al., 2014b); (Blanchard et al., 2014)

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Highlights

Semi-volatile organic compounds (SVOCs) detected in more than 10% of French dwelling were selected SVOCs were grouped according to their reprotoxic mode of action Benchmark Doses and Relative Potency Factors based on a decrease in testosterone level in male rodent were derived The main limitation is the lack of comparable toxicological data.

  More recently, Hannas et al. have calculated RPFs for 5 phthalates. In contrast toBenson, they undertook the in vivo tests on the same endpoint (decrease of foetal testosterone production) in their own laboratory, making their data more comparable. They measured foetal testosterone production and the expression of steroidogenesis enzymes after 5 days of in utero exposure for each phthalate. The potency estimations were based on the derived effective doses 50 (ED 50 ), dose responsible for 50% decrease of the foetal testosterone, equivalent to a BMD 50 . In this case, DEHP appears to be one of the least potent phthalates for this effect, in contrast to our data. This could be explained by the level of response associated with the chosen indicators (10% versus 50%) or by the difference of window of exposure. In this case, only DEHP is similar to the compounds included in our study so no potency comparison can be made.While Benson concludes that DEHP is one of the most toxic phthalates within its chemical group (2.5 and 4 times more potent than DiNP and DiBP respectively) using different endpoints, Hannas finds that DEHP is approximately equipotent with DiBP and DiNP (RPFs of 0.06, 0.11 and 0.15 for DiNP, DEHP and DiBP respectively) for the same endpoint.

Figure 1 :

 1 Figure 1: Adverse outcome pathway of 23 indoor semi volatile organic compounds (SVOCs) on the reproductive, adapted from (Fournier et al., 2014b).

Table 1 : Selected Semi Volatile Organic Compounds as candidates for grouping (detected in more than 10% of the French dwellings investigated)

 1

	Chemical families			Name
	Phthalates		DEHP, DEP, DBP, BBP, DiBP, DiNP, DMP
	Polybromodiphenyl	BDE-28, BDE-47, BDE-85, BDE-99, BDE-100, BDE-153, BDE-154,
	ethers (PBDEs)	BDE-209
	Polychlorobiphenyls	PCB-28, PCB-31, PCB-52, PCB-77, PCB-101, PCB-105, PCB-118,
	(PCBs)		PCB-138, PCB-153, PCB-180
	Polycyclic	aromatic	acenaphtene, anthracene, benzo(a)pyrene, fluorene, phenanthrene,
	hydrocarbons (HAPs)	fluoranthene,	pyrene,	benzo(a)anthracene,	chrysene,
			benzo(k)fluoranthene, benzo(b)fluoranthene, indeno(1,2,3-cd)pyrene,
			benzo(g,h,i)perylene, dibenzo(a,h)anthracene
	Pesticides		4',4 DDE,	4',4 DDT,	dieldrine,	alpha-endosulfan,	lindane,
			chlorpyrifos-ethyl, diazinon, cyfluthrine, cypermethrine, deltamethrine,
			permethrine, oxadiazon, tributylphosphate
	Others		4-tert-butylphenol, 4-tert-octylphenol, bisphenol A, galaxolide, tonalide,
			triclosan

Table 2 : Available information in the literature on reproductive effects for the 6 Semi Volatile Organic Compounds retained for BenchMark Dose calculation

 2

	SVOC	Tested animals	Number of animals	Time of exposure	Route of exposure	Tested doses bw/day) (mg/kg	Response (standard control) (relative to deviation)	Reference
						0	1 (0.46)
	BBP	Adult SD rats	25	105 days Oral	20 100	1.03 (0.54) 0.77 (0.37)	Nagao et al., 2000
						500	0.54 (0.31)
						0	1 (0.1)
	BPA	Adult Wistar rats	6	45 days	Oral	0.000005 0.00005 0.05	0.84 (0.05) 0.74 (0.05) 0.62 (0.04)	D'Cruz et al., 2012
						0.5	0.44 (0.06)
						0	1 (0.31)
	B[a]P	Adult SD rats	9	90 days	Oral	0.001 0.01	1 (0.29) 0.64 (0.17)	Chung et al., 2011
						0.1	0.25 (0.12)
	DEP	Adult Wistar rats	6	150 days Oral	0 2.85 0.57 1.425	1 (0.13) 0.41 (0.025) 0.69 (0.11) 0.63 (0.056)	Pereira et al., 2008
						0	1 (0.42)
						1	0.79 (0.17)
	DEHP	Adult Wistar rats	5	40 days	Oral	3 100 10 30	0.70 (0.27) 0.62 (0.32) 1.15 (0.50) 0.52 (0.30)	Tonk et al., 2012
						300	0.47 (0.16)
						1000	0.48 (0.18)
						0	1 (0.35)
	Cyper-methrin	Adult SD rats	12	15 days	Oral	6.25 12.5 25	0.84 (0.35) 0.79 (0.19) 0.65 (0.33)	Hu et al., 2011
						50	0.49 (0.16)

SVOCs: Semi Volatile Organic Compounds; SD: Sprague Dawley

Table 3 : Benchmark dose 10 and benchmark dose 50 for the 6 selected SVOCs SVOC Number of Hill parameters BMD10 (mg/kg bw/day)

 3

	BMD50
	(mg/kg bw/day)

SVOCs: Semi Volatile Organic Compounds; BMD 10 : Benchmark Doses responsible of 10% of the selected effect

Table 4 : Relative Potency Factor 10 and Relative Potency Factor 50 calculations from BenchMark Doses for 6 Semi Volatile Organic Compounds detected in more than 10% of French dwellings and acting on testosterone synthesis in adult male rats

 4

	SVOC	RPF 10	RPF 50
	B[a]P	1597	1630
	BPA	7033679	181
	DEP	22.63	22
	DEHP	1.08	/
	Cypermethrin	1	1
	BBP	0.095	0.095

SVOCs: Semi Volatile Organic Compounds; RPF 10 : Relative Potency Factors for 10% of the selected effect

Acknowledgements

The authors acknowledge Laurent Bodin, Christophe Rousselle (ANSES, France) for their helpful advice, Elisa C. M. Tonk and Aldert H. Piersma for providing the raw data from experiments on DEHP and The French Ministry of Environment for the funding.

Funding information

This work was supported by the French Ministry of Ecology: Primequal [Environnement Intérieur et Approches Innovantes], programme 190, THUR-BSAF action 13, sub-action 08

Della Seta, D., Minder, I., Belloni, V., Aloisi, A.M., Dessì-Fulgheri, F., Farabollini, F., 2006. Pubertal exposure to estrogenic chemicals affects behavior in juvenile and adult male rats. Hormones and behavior 50, 301-7. -Lethimonier, C., Albert, O., Le Bizec, B., Perdu, E., Zalko, D., Courant, F., Lesné, L., Guillé, F., Dejucq-Rainsford, N., Jégou, B., 2012

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