Agathe Hubau
email: a.hubau@brgm.fr

Michel Minier

Alexandre Chagnes

Catherine Joulian

Cédric Perez

Anne-Gwenaelle Guezennec

Anne-Gwenaëlle Guezennec

Continuous production of a biogenic ferric iron lixiviant for the bioleaching of printed circuit boards (PCBs)

Keywords: Bioleaching, Bio-oxidation, printed circuit boards, acidophilic

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

Introduction

The metal content of spent printed circuit boards (PCBs) can reach up to 35% (in weight), including precious and strategic metals even at greater concentrations than in primary resources.

For instance, gold and copper are 25 to 250 times and 20 to 40 times more concentrated in spent PCBs than in ores, respectively [START_REF] Tuncuk | Aqueous metal recovery techniques from e-scrap: Hydrometallurgy in recycling[END_REF]. Consequently, spent PCBs are becoming a valuable resource. At the same time, a lack of an appropriate treatment could be a cause of environmental pollution.

Today, high-grade PCBs are treated by pyrometallurgy to recover valuable metals but some metals, such as aluminium, iron and precious metals, are lost in the slag during this operation [START_REF] Cui | Metallurgical recovery of metals from electronic waste: A review[END_REF] and the energy-cost of such processes is high. Moreover, the presence of plastics raises two important issues: first, the emission of toxic dioxins and furans; and second, the presence of plastics can bring about uncontrolled temperature increases leading to smelter damages (Hagelüken, 2006). Currently, the addition of PCBs to smelter feed represents at most 15% of the mass, the rest being metal concentrates. For example, PCBs make up 14% of the total throughput in the Noranda process in Canada and 10% in the Umicore process in Belgium [START_REF] Cui | Metallurgical recovery of metals from electronic waste: A review[END_REF][START_REF] Ghosh | Waste Printed Circuit Boards recycling: an extensive assessment of current status[END_REF]. Due to this limitation, the quantity of PCBs that are treated annually remains low. Therefore, the design of energy-efficient and costeffective new processes for efficient metal recovery from PCBs is particularly important.

Techniques based on mechanical processes and hydrometallurgy are emerging as alternative solutions.

Within this framework, biohydrometallurgy is very promising. In the literature, some studies deal with the use of bioleaching for the treatment of spent PCBs by means of acidophilic microorganisms [START_REF] Brandl | Computer-munching microbes: metal leaching from electronic scrap by bacteria and fungi[END_REF][START_REF] Ilyas | Column bioleaching of metals from electronic scrap[END_REF]. The use of such micro-organisms, which are mainly iron and sulfur-oxidising, allows the extraction of various metals such as Cu, Ni and Zn. Although the mechanisms are not completely known, the following main reactions may occur: nFe 3+ + M 0 à nFe 2+ + M n+ (chemical)

(1)

4Fe 2+ + O2 + 4H + à 4Fe 3+ + 2H2O (biological) (2)
The main issue raised by research studies dedicated to the development of bioleaching processes for PCBs treatment is linked to the reproducibility of the results, mainly because of the large heterogeneity of PCBs that leads to large variation of sample composition. Most studies dedicated to acidophilic bioleaching of spent PCBs to date have been performed in simple shake flasks and the quantity of PCBs added for each batch test is often too low to be representative of the whole composition of the PCB sample. Moreover, the results are highly variable as important parameters, such as dissolved oxygen concentration, pH or microorganisms are diverse. Figure 1 illustrates the discrepancy in copper bioleaching yields reported in the literature for spent PCBs in shake flask and reactor studies.

Finally, the addition point of raw material after inoculation influences greatly PCB bioleaching efficiency. This parameter appears particularly important as PCBs may be responsible for the inhibition of microbial growth and activity [START_REF] Liang | Optimizing mixed culture of two acidophiles to improve copper recovery from printed circuit boards (PCBs)[END_REF]. Staggering the production of the lixiviant and the addition of the e-waste in a two-step process can greatly increase leaching rates (Yang et al., 2009;[START_REF] Guezennec | Co-processing of sulfidic mining wastes and metal-rich post-consumer wastes by biohydrometallurgy[END_REF]. However, this requires the establishment of a stable steady-state operation in the first stage where biomass production and ferrous iron biooxidation occur (Reaction 2). The literature shows that a vast number of iron bio-oxidation studies in continuous mode have been done to develop a large range of applications. Some studies are summarised in Table 1. In this Table, the study duration is the time before authors change any parameters once steady state is reached. Most of these works investigated multiple parameters to avoid kinetic limitations and to achieve the highest bio-oxidation rate. The first parameter is the characteristics of the influent, i.e. pH (Kaksonen et al., 2014a;[START_REF] Kinnunen | High-rate iron oxidation at below pH 1 and at elevated iron and copper concentrations by a Leptospirillum ferriphilum dominated biofilm[END_REF] and ferrous iron concentration [START_REF] Gómez | Kinetic study of biological ferrous sulphate oxidation by iron-oxidising bacteria in continuous stirred tank and packed bed bioreactors[END_REF] since these parameters influence significantly the kinetics of bio-oxidation. The second parameter is the composition of the gas flow to avoid any limitation in carbon dioxide (required for bacterial growth, as it is the sole carbon source available) and/or oxygen (required for microbial oxidation of ferrous iron, see Reaction 1). Bastías and Gentina (2010) improved their chemostat performance by enriching air with 4% CO2. [START_REF] Kinnunen | High-Rate Ferric Sulfate Generation by a Leptospirillum ferriphilum-Dominated Biofilm and the Role of Jarosite in Biomass Retainment in a Fluidized-Bed Reactor[END_REF] detected an oxygen limitation when using air and used a 99.5%O2/0.5%CO2 gas mixture to obtain a maximal oxidation rate of 26.4 g L -1 h -1 . This parameter is closely linked to the presence and the type of solid support, which will impact the gas-liquid mass transfer. First studies were performed without using solid support but performance was limited due to limited biomass and cell wash out at low hydraulic residence times (HRT; Halfmeier et al., 1993a). Consequently, many solid supports were developed and investigated [START_REF] Grishin | Fast kinetics of Fe 2+ oxidation in packed-bed reactors[END_REF], e.g. polystyrene (Karamanev and Nikolov, 1986), quartz sand (Halfmeier et al., 1993b), Ni-alloy fibres [START_REF] Gómez | Kinetic study of biological ferrous sulphate oxidation by iron-oxidising bacteria in continuous stirred tank and packed bed bioreactors[END_REF] and activated charcoal [START_REF] Kinnunen | High-Rate Ferric Sulfate Generation by a Leptospirillum ferriphilum-Dominated Biofilm and the Role of Jarosite in Biomass Retainment in a Fluidized-Bed Reactor[END_REF]. The goal was to obtain large surface areas and high numbers of attached cells without slowing down mass transfer. Activated charcoal was reported as one of the best solid supports in terms of biooxidation performance due to its porosity which enables the retention quantities of large biomass [START_REF] Jensen | Ferrous sulphate oxidation using Thiobacillus ferrooxidans: a review[END_REF]. [START_REF] Grishin | Fast kinetics of Fe 2+ oxidation in packed-bed reactors[END_REF] reported a maximal oxidation rate of 52.6 g L -1 h -1 in a bioreactor with 50 mL of activated charcoal.

However, due to the high concentrations of ferric iron, [START_REF] Ebrahimi | High-Rate Acidophilic Ferrous Iron Oxidation in a Biofilm Airlift Reactor and the Role of the Carrier Material[END_REF] suggested that the presence of jarosite precipitates in the bioreactor modifies the bio-oxidation rates and yields over long periods of time and affects mass transfer near the solid support. The formation of jarosite precipitates was extensively described (Kaksonen et al., 2014c); the following reaction occurs:

A + + 3Fe 3+ + 2SO4 2-+ 6H2O à AFe3(SO4)2(OH)6 + 6H + (3)
Where A + is a cation (potassium K + , sodium Na + , ammonium NH4 + , hydronium H3O + ).

During 6 months, Halfmeier et al. (1993) operated a fixed-bed reactor in continuous mode and revealed transport limitation and long-term stability issues. [START_REF] Kinnunen | High-Rate Ferric Sulfate Generation by a Leptospirillum ferriphilum-Dominated Biofilm and the Role of Jarosite in Biomass Retainment in a Fluidized-Bed Reactor[END_REF] highlighted the influence of jarosite accumulation on oxidation performance in a fluidized-bed reactor, with a majority of cells attached on jarosite, creating instabilities when removing these precipitates. They revealed some difficulties to maintain constant jarosite formation rate, and thus, to maintain stable performance [START_REF] Kinnunen | High-rate iron oxidation at below pH 1 and at elevated iron and copper concentrations by a Leptospirillum ferriphilum dominated biofilm[END_REF]. Recently, Kaksonen et al. (2014aKaksonen et al. ( , 2014c) ) investigated the use of these precipitates as solid support. [START_REF] Ebrahimi | High-Rate Acidophilic Ferrous Iron Oxidation in a Biofilm Airlift Reactor and the Role of the Carrier Material[END_REF] used this method to develop an airlift reactor that presented stable performance over long periods of time to establish a process of H2S removal. The use of a settler (Kaksonen et al., 2014a(Kaksonen et al., , 2014c) ) to remove excess sludge maintained stable performance.

This paper reports the performance and the limitations obtained for the bio-oxidation of ferrous iron in a bubble column run in continuous mode, which will be used as the first stage of a biolixiviant reactor for leaching spent PCBs. The influence of influent ferrous iron concentration on the bio-oxidation rate was studied over an extended period of time. The influence of the type and quantity of solid support and of the medium composition on biooxidation yield were investigated. The colonization of solid support was observed by cryogenic scanning electron microscopy to understand the phenomena that affect the stability of biooxidation performance. The main objective of the study was to determine the operating parameters which enabled stable and maximal performance over a period of several weeks.

Material and methods

2.1 Growth medium and bacterial culture. The inoculum used for the cultures was obtained from the BRGM-KCC microbial consortium subcultured on pyrite tailings [START_REF] Guezennec | Influence of dissolved oxygen on the bioleaching efficiency under oxygen enriched atmosphere[END_REF]. The predominant micro-organisms in the culture are affiliated to the acidophilic genera Leptospirillum, Acidithiobacillus and Sulfobacillus. Two culture media were used: 0Km medium consisted of (g L -1 ): 3.70 (NH4)2SO4, 0.81 H3PO4 85%, 0.48 KOH, 0.52 MgSO4.7H2O, while the culture medium 0Cm had the same composition but only 0.4 g L -1

(NH4)2SO4. Ferrous iron was added as FeSO4.7H2O to obtain ferrous iron concentrations ranging from 1 to 9 g L -1 . 1Km and 9Km denote 0Km culture media containing 1 and 9 g L -1

of ferrous iron, while 1Cm and 9Cm denote 0Cm culture media containing 1 and 9 g L -1 of ferrous iron respectively. Growth media were adjusted to pH 1.2 using concentrated H2SO4. Chemical Performance Polymers). The latter were used as received while the charcoal was washed with 5 mL g -1 of water and 1 mL g -1 of diluted sulfuric acid (pH 1.3), dried at 40°C for 20 hours and sieved to remove particles smaller than 1 mm prior to use. The bioreactor was inoculated with the BRGM-KCC culture at 10% v/v. The bubble column was first operated in batch mode in order to establish the biomass and then switched into continuous mode when the redox potential reached 900 mV vs. SHE. All experiments were performed in non-sterile conditions, to suit more accurately the industrial reality.

Experimental

Finally, biotic and abiotic shake flasks experiments were done to determine the chemical oxidation of ferrous iron by the activated charcoal itself. Flasks (250 mL) contained 100 mL 9Cm medium with 10 g of activated charcoal. Biotic tests were inoculated with 10% (v/v) BRGM-KCC. Abiotic shake flasks were autoclaved with activated charcoal, 9Cm medium was filter sterilized (0.2 µm syringe filter from ClearLine in cellulose acetate) and manipulations were performed under a laminar air flow hood.

Analytical techniques.

Oxygen and carbon dioxide concentrations in the off-gas from the bioreactor were analysed by using ADC MGA 3000 Multi-Gas Analyzer (Analytical Development Company Ltd). Total iron concentration was determined by flame atomic absorption spectroscopy (AAS) using a Varian SpectrAA-300. Ferrous iron concentration was determined by using the correlation between redox potential and total iron concentration as reported by Yue et al. (Yue et al., 2014). Estimated values of ferrous iron concentration deduced from this correlation were occasionally confirmed experimentally by performing cerium (IV) titration with a Metrohm titrode (Pt-pH) in sulfuric acid medium (Yue et al., 2016).

2.4 Bacterial community monitoring.

Cell counting.

The number of micro-organisms in the supernatant was monitored by counting on Thoma cell counting chamber. The same methodology was used to count attached cells on the solid support, after cell detachment performed by slowly shaking with a mixing shaker (Heidolph Reax 2) at minimum speed (24 rpm) 500 mg of solid support in 1.5 mL of fresh acidic medium (0Km with pH <2) with 0.25% v/v Tween 20 (from Sigma Aldrich), for 1 hour.

Cryogenic scanning electron microscopy (Cryo-SEM)

. This method was used to observe the attachment of cells onto the solid support without prior steps of preparation. Fresh aliquots of solids sampled from the bubble column were introduced on a copper frame with carbon paste. Samples were immersed into liquid nitrogen at -176 °C and a pressure depression enabled to reach -210 °C (slush nitrogen). From this point, samples were set under vacuum and transferred into the SEM (Hitachi S-4500 field-emission operated at 1 kV). They were warmed to -70 °C to remove ice that was formed on the sample due to moisture condensation and cooled to -105 °C for observations. Detection of secondary electrons was performed on the surface or inside samples after cryo-fracturing. Energy dispersive X-ray spectroscopy (EDX) was used to characterize the sample composition with SEM operated at 5 or 15 kV.

DNA extraction and capillary electrophoresis-single strand conformational polymorphism (CE-SSCP) monitoring of the bacterial community structure. The CE-SSCP

technique was used on polymerase chain reaction (PCR) product of 16S rRNA gene to obtain a diversity profile and to determine relative abundances of the detected bacterial strains.

Samples containing 0.5 mL solid support or 2 mL liquid phase were taken from the bubble column. Solid samples and pellets (from centrifugation of the liquid samples for 10 minutes at 14000 g) were washed by re-suspension in Tris buffer (100 mM, pH 8) until pH reached around 7. Genomic DNA was extracted with the FastDNA Spin Kit for Soil and using the manufacturer's protocol (MP Biomedicals) with a FastPrep ® -24 at a speed of 5 m s -1 for 30 s.

Amplification of the 16S rRNA gene from DNA extracts was performed with C-1000 thermocycler (Biorad) with the w49 forward primer and the 5′-end FAM-labeled w34 primer, as in [START_REF] Hedrich | Quantitative Monitoring of Microbial Species during Bioleaching of a Copper Concentrate[END_REF]. For CE-SSCP analysis, one microliter of 5-to 500-fold diluted PCR product, 0.4 μL of Genescan-600 LIZ internal standard (Applied Biosystems) and 18.6 µL of deionized formamide HiDi (Applied Biosystems) were heated for 5 minutes at 95 °C for denaturation and immediately cooled on ice for 10 minutes. Fragment analyses were conducted with the ABI Prism 310 (Applied Biosystems). The software GeneScan (Applied Biosystems) was used to realign the peak profiles based on internal standard migration, assign peak position and calculate relative abundances on the basis of peak areas.

Results

The influence of ferrous iron concentration on bio-oxidation

Activated charcoal produced from black granular coal was chosen as support for this work because high bio-oxidation rates can be achieved with this type of support [START_REF] Jensen | Ferrous sulphate oxidation using Thiobacillus ferrooxidans: a review[END_REF], especially due to its high specific area of 950 m 2 g -1 . It should be noted that the rate of the chemical oxidation of ferrous iron into ferric iron in the presence of activated charcoal is very low, as demonstrated by the studies of [START_REF] Kuznetsova | Promotion effect of carbon on the oxidation of ferrous ions by oxygen in the presence of sodium nitrite[END_REF] and Ahumada et al. (2002) with severe conditions (high temperature and O2 pressure). In our conditions, measures in sterile shake flasks in 9Cm medium gave a chemical oxidation rate reaching 65 mg L -1 h -1 with clean activated charcoal. This rate was much lower than the one in biotic shake flasks, with biooxidation rates easily reaching 240 mg L -1 h -1 . It confirms that this material is mainly acting as a solid support for bacteria, and its ability to catalyse ferrous iron oxidation is negligible compared to bio-oxidation.

In order to examine the kinetics of bio-oxidation at different influent ferrous iron concentrations, 15 g of activated charcoal were introduced in the bioreactor and the HRT was set to 12 h. This mass of activated charcoal corresponded to an apparent volume of 33 mL.

Table 2 shows the bio-oxidation yield and rate obtained in these conditions with ferrous iron concentration in the influent medium ranging from 1 to 9 g L -1 .

The maximum bio-oxidation rate obtained was 375 mg L -1 h -1 with an influent concentration of 4.5 g L -1 of ferrous iron. This maximal oxidation rate was very low compared to those reported in the literature. At higher influent ferrous iron concentrations, both the bio-oxidation yield and rate were lower. Moreover, substantial variations in these rates were observed with the same operating conditions.

Bio-oxidation performance as a function of HRT is presented for bioreactors with 1 and 9 g L -1 influent ferrous iron in Figure 3. For fixed operating conditions, performance were not stable even at 10 HRT. Consequently, each dot of the figure, which represents the bio-oxidation yield or rate for one fixed HRT, depicts the most common value obtained in these fixed operating conditions. Error bars depict the range of all other obtained values in such conditions. Figure 3 shows large discrepancies in bio-oxidation yield and rate when 9 g L -1 ferrous iron was used whatever the HRT. This was mainly due to precipitate formation on the solid support (see below). At 1 g L -1 ferrous iron, between 80% and 100% bio-oxidation yield was obtained for high HRT. However, when the HRT decreased below 4 hours, iron bio-oxidation yield decreased sharply. A maximum oxidation rate of 450 mg L -1 h -1 was obtained at 1 g L -1 ferrous iron and HRT of 2 hours.

The influence of the quantity of activated charcoal on bio-oxidation

In order to minimize the instabilities obtained at high influent ferrous iron concentrations, the impact of the quantity of solid support was investigated. The amount of activated charcoal influences the amount of biomass attached onto and into the solid, and therefore, the performance of the bioreactor. Table 3 shows the bio-oxidation rate for both influent ferrous iron concentrations (1 g L -1 and 9 g L -1 Fe 2+ ) at 6 h HRT.

The quantity of activated charcoal at 1 g L -1 did not seem to influence iron oxidation since 100% bio-oxidation was obtained in all cases at 6 h HRT. Higher oxidation rates were observed at influent ferrous concentration of 9 g L -1 when larger quantities of activated charcoal were used; however, the performance was still not stable. It is interesting to highlight that, at fixed HRT, the addition of activated charcoal into the bioreactor was responsible for an instantaneous increase in bio-oxidation yield and rate followed by a gradual decrease (data not shown). Figure 4 shows lower instabilities when larger amounts of activated charcoal were used at 9 g L -1 . The iron bio-oxidation yield gradually decreased with decreasing HRT and oxidation rate varied between 400 and 700 mg L -1 h -1 .

The influence of the growth media composition on bio-oxidation

Silverman and Lundgren (1959) detailed the composition of a growth medium (9K) adapted to the growth of acidophilic microorganisms, e.g. Acidithiobacillus ferrooxidans. [START_REF] Collinet-Latil | PhD thesis, Lixiviation bactérienne par Thiobacillus ferrooxidans et Thiobacillus thiooxidans d'un concentré de flottation arsénopyriteux aurifère (réfractaire à la cyanuration directe)[END_REF] modified this medium to obtain optimal bioleaching performance with the BRGM-KCC consortium. In the present study, this medium (0Km) was compared with the 0Cm medium, which contains the same quantities of KOH, H3PO4 and MgSO4.7H2O and ten times less (NH4)2SO4 in the presence of 1 g L -1 or 9 g L -1 ferrous iron and 15 g or 30 g of activated charcoal, respectively (Figures 5 and6).

Results obtained with both media were quite similar at 1 g L -1 ferrous iron but better performance were obtained with the 1Cm medium at low residence time (1.1 hour): the maximal oxidation rate increased from 450 to 900 mg L -1 h -1 when nutritive medium was changed from 1Km to 1Cm. Concerning the bioreactor with influent ferrous iron concentration of 9 g L -1 , reducing the quantity of ammonium ions allowed a more stable performance at high HRT, and enabled higher iron oxidation yields. The lower ammonium concentrations may have led to a reduction in jarosite precipitation, as explained below. In 9Cm medium, maximal oxidation rate reached 1400 mg L -1 h -1 at 6.3 hours HRT. In these conditions, bio-oxidation performance was within the range of the results presented in the literature (Table 1).

The influence of the solid support on bio-oxidation

The bio-oxidation rate in the presence of a highly porous support (activated charcoal) and a non-porous support (polyvynil chloride beads) is shown in Figures 7 and8 with an influent ferrous iron concentration of 1 g L -1 and 33 mL of solid support or 9 g L -1 and 66 mL of solid support, respectively. The same apparent volume was used to compare both supports and both bioreactors were first operated in batch mode during 45 h to favour the attachment of the biomass. At 1 g L -1 ferrous iron, similar performance was obtained with both supports at high HRT (HRT > 2 h). However, the bio-oxidation rate was obviously affected by the type of solid support at low HRT (1h): it sharply decreased from 900 mg L -1 h -1 to 500 mg L -1 h -1 with the use of PVC beads. The performance notably decreased at 9 g L -1 with PVC as less than 20% of influent ferrous iron was oxidized under such conditions whatever the residence time. The lack of porosity of PVC support was probably not favourable to the development of attached biomass in the bioreactor, since available surface area for cells attachment was low.

3.5

The characteristics of solid support and bacterial community structure during biooxidation 3.5.1 The influence of operating conditions on the solid support. Cryo-SEM was used to observe the colonization of activated charcoal particles by bacteria. Such a technique is particularly suitable for this study since it allows the observation of fresh biological materials as no dehydration step is required during sample preparation and it is possible to obtain highresolution images at low voltage. This method also enables the breaking of the charcoal particles into sub-particles without damaging the biofilm in order to observe the interior of porous material: an example of ore breakage was described by [START_REF] Kelly | Cryogenic scanning electron microscopy of fluid inclusions in ore and gangue minerals[END_REF].

Figures 9-11 show Cryo-SEM pictures inside and outside charcoal particles in biotic conditions in the presence of 1 and 9 g L -1 ferrous iron and in abiotic conditions in the presence of 9 g L -1 ferric iron in 0Km culture medium. Figure 9A shows the presence of many bacteria inside activated charcoal particles in the 1Km media. Cells seemed to be attached on the surface into the pores of the solid support. An organic substance was observed around these cells by Cryo-SEM but its fast degradation by the electron beam prevented the acquisition of any pictures. It was supposed that this substance was composed of extracellular polymeric substances. Only very few cells were observed in the presence of 9 g L -1 ferrous iron and none are visible on Figure 9B. Figures 9B and9C show the presence of an organic framework but this framework seemed different from the one observed in Figure 9A since its resistance against electron beam was greater. This organic framework is likely composed of bitumen substances given that charcoal is a bituminous compound.

Figure 10 shows the presence of precipitates onto the particle surface in all samples. These precipitates formed a layer on the solid support, which seemed to be more spread in samples colonized under biotic conditions in the presence of 9 g L -1 ferrous iron (Figure 10B) and in Erlenmeyer under abiotic conditions in the presence of 9 g L -1 ferric iron (Figure 10C) when compared to 1Km medium (Figure 10A). It is interesting to highlight that the activated charcoal surface seemed to be entirely coated by precipitates in the presence of 9 g L -1 iron (Figures 10B and10C) while less precipitate covered the charcoal surface in the presence of 1 g L -1 iron (Figure 10A), leading to the formation of small pores.

The edge of a representative charcoal particle after colonization in a growth medium containing 9 g L -1 ferrous iron is shown in Figure 11. Pseudocubic structures, which are attributed to ammonium jarosite precipitation (Kaksonen et al., 2014), were observed in the particle pores. It can be inferred that the precipitate was actually a mixture of ammonium jarosite (pseudocubic structure) and potassium jarosite since EDX analyses demonstrated the presence of potassium and sulfate (Figure 12).

Bacterial community structure. Microbial diversity profiles were determined in

bioreactors by 16S rRNA gene CE-SSCP. A comparison was performed between solid and liquid phases in bioreactors for two different influent ferrous iron concentrations (1 g L -1 with 15 g of activated charcoal and 9 g L -1 with 30 g of activated charcoal) for HRT ranging from 1 to 10 hours (Figure 13). Results implied that conditions in the bioreactor were unsuitable for the growth of Acidithiobacillus caldus, as it remained undetected despite this bacterium being a member of the BRGM-KCC consortium initially used to inoculate the bioreactor. This can be explained by the absence of reduced sulfur compounds in the bioreactor since Acidithiobacillus caldus is a sulfur-oxidizing bacterium. Likewise, Sulfobacillus thermosulfidooxidans was not detected in any samples. The temperature maintained at 36 °C in the bioreactor was probably too low since the optimal growth temperature is 51 °C for this bacterium (Watling et al., 2008).

Conversely, Leptospirillum ferriphilum and Sulfobacillus benefaciens, which are present in the BRGM-KCC consortium, were present in the solid and the liquid phases in the bioreactor but their relative abundance varied when the operating conditions changed. Especially, influent ferrous iron concentration seemed to have an influence on the bacterial growth since 9 g L -1

ferrous iron favoured the growth of Sulfobacillus benefaciens, with an average proportion of 60%, while 1 g L -1 favoured Leptospirillum ferriphilum growth, with an average proportion of 80%. This may be explained due to the higher affinity for the ferrous iron substrate and greater tolerance of ferric iron of L. ferriphilum over Sulfobacillus spp. [START_REF] Norris | Acidophile Diversity in Mineral Sulfide Oxidation[END_REF]. The proportions of these two organisms were similar in liquid and solid phases. Two unknown micro-organisms were detected in the bioreactor at 9 g L -1 ferrous iron for 3.5 and 5.1 hours. One of these was also detected in the other bioreactor at 1 g L -1 ferrous iron.

Finally, cell distribution between solid and liquid phases was determined in the same conditions as the previous characterization of diversity profiles. Figure 14 gives the distribution for both bioreactors. When influent ferrous iron concentration was 1 g L -1 , the number of cells remained stable for HRT varying between 1 and 3 hours; the cells were also well distributed between the solid and the liquid phases. For the same iron concentration and HRT of 6.4 hours, the number of cells increased noticeably (at least by 0.5 Log) and a large proportion of cells were attached onto activated charcoal. In the presence of 9 g L -1 ferrous iron in the influent, the increase in cell number at high HRT was less than on 1 g L -1 ferrous iron and the cells were more or less equally distributed between the liquid and the solid phases. For HRT of 6 hours, the total cell number was much lower compared to the results obtained at 1 g L -1 Fe 2+ whereas the cell number was of the same order of magnitude for lower HRT in both conditions. It must be noted that these data are only an estimate of the number of cells in the bioreactor given the low accuracy for cell counting (inaccuracy arose from the difficulty to collect all cells from activated charcoal and from counts on Thoma cell chamber).

Discussion

Observations with Cryo-SEM highlighted the fact that activated charcoal from the bioreactor containing 9 g L -1 ferrous iron was less colonized than in the presence of 1 g L -1 ferrous iron.

Furthermore, Cryo-SEM demonstrated that activated charcoal particles from 9Km bioreactor were entirely coated with precipitates, while particles from 1Km bubble column were only partially clogged. Consequently, one hypothesis is that instabilities in 9Km bioreactor performance resulted from the presence of precipitates, which coat the charcoal surface and cause difficulties for the bacterial attachment. For unchanged operating conditions (fixed HRT), this clogging phenomenon seemed to occur according to the following cycle: (i) High biooxidation yield and rate were observed since ferrous iron was intensively oxidized to ferric iron by the cells, which initially colonized the pores of activated charcoal; (ii) Activity of the bacteria decreased because of limitation of the diffusion of nutrients, carbon dioxide, oxygen and ferrous iron resulting from the accumulation of potassium jarosite and ammonium jarosite that coated the external charcoal surface (cf Reaction 3); (iii) Attrition between the particles was responsible for coating destruction, which led to an increase in bacterial activity, and therefore, an increase in bio-oxidation yield and rate until new jarosite precipitation phenomena occurred.

The age of solid support greatly affected the performance. It was thus difficult to determine accurately the cell distribution between the liquid and the solid phases since the clogging phenomenon and the high porosity of activated charcoal limited the cell collecting procedure.

This hypothesis could explain the difference in diversity profiles between both bioreactors:

Sulfobacillus benefaciens was able to take advantage of different energy and carbon sources, as it is a mixotrophic species [START_REF] Johnson | Sulfobacillus benefaciens sp. nov., an acidophilic facultative anaerobic Firmicute isolated from mineral bioleaching operations[END_REF]. If carbon dioxide and ferrous iron were not available due to the coating of the solid support, this species could use cellular waste to survive, at the expense of Leptospirillum ferriphilum, which is a strict autotroph [START_REF] Mi | Complete genome of Leptospirillum ferriphilum ML-04 provides insight into its physiology and environmental adaptation[END_REF].

It is consistent with results obtained when the growth medium composition was changed:

the decrease in ammonium concentration limited ammonium jarosite precipitation, thus limiting the coating of solid support. It enabled more stable performance. In these conditions, maximal oxidation rates were obtained at 1400 mg L -1 h -1 in the presence of 9 g L -1 ferrous iron in the influent. In the literature, it is reported that the stability of jarosite depends on the standard enthalpy of formation. Thus, potassium jarosite is more stable than sodium and hydronium jarosite, which are more stable than ammonium jarosite [START_REF] Gaboreau | Prediction of Gibbs free energies of formation of minerals of the alunite supergroup[END_REF][START_REF] Gramp | Monovalent cation concentrations determine the types of Fe(III) hydroxysulfate precipitates formed in bioleach solutions[END_REF]Kaksonen et al., 2014b). Modifying the potassium concentration in the medium could improve bacteria attachment onto the pores surface of the charcoal by avoiding potassium jarosite precipitation.

The nature of the support seemed to have a high impact on bio-oxidation performance since the use of non-porous polyvinyl chloride beads reduced the iron bio-oxidation yield to less than 20% while it reached 99% in the same conditions with activated charcoal. This was probably due to a difference in porosity, which influenced the number of accessible sites for cell attachment: with 33 mL, the accessible surface with activated charcoal is estimated to 14 520 m 2 while it is estimated to 0.048 m 2 with PVC beads. The zeta potential of solid supports may also play a role in the attachment of acidophilic cultures, as reported by Halfmeier et al. (1993b) : it is assumed that the adsorption of cells onto solid supports due to electrostatic and Van der Walls forces is the first step of the creation of biofilms. Acidophilic cultures, positively charged with protonation, will better adsorb to negatively charged surfaces.

Concerning these results, one way to improve the kinetics could be to change the solid support. A study with woven nylon performed by [START_REF] Svirko | Experimental Study of Ferrous Iron Biooxidation by Leptospirillum Ferriphilum in Different Biofilm Reactors[END_REF] give good results in terms of ferrous iron bio-oxidation rates, with 4 g L -1 h -1 . This might be explained by the creation of a framework that enables the biomass to get attached without affecting mass transfer.

The highest oxidation rate obtained in 9Cm was 1400 mg L -1 h -1 at HRT of 6.3 hours.

Concerning the 1Cm medium, the highest oxidation rate obtained was 900 mg L -1 h -1 at a minimum HRT of 1.1 h. To go further in the design of the bubble column, it is therefore mandatory to take into account the second stage of the bioreactor. If the bubble column must regenerate high concentrations of ferric iron due to the inhibition of bacterial activity in the second stage, it is necessary to test higher influent ferrous iron concentrations and minimize ferric iron precipitation. If the bubble column aims at the development of a fresh culture with planktonic cells, the use of activated charcoal is not recommended as cells are strongly attached onto the pores surface of solid support particles.

Conclusion

To recover metals from different resources, particularly spent printed circuit boards, the production of a biogenic lixiviant solution is of great interest. However, the monitoring of the process should be controlled and the stability of this production over long periods of time is necessary. In this work, a bubble column inoculated with BRGM-KCC microbial consortium in the presence of activated charcoal was used for ferric lixiviant generation. Results were not reproducible at 9 g L -1 in 0Km medium and were much lower than literature oxidation rates.

The use of higher quantities of activated charcoal did not improve the rates but the stability improved. The use of polyvinyl chloride beads as solid support decreased the oxidation rates.

However, with a modified medium containing a ten-fold lower ammonia concentration, maximal bio-oxidation rates were obtained with activated charcoal with long-term stability: 1400 mg L -1 h -1 with 9 g L -1 ferrous iron at HRT of 6.3 h and 900 mg L -1 h -1 with 1 g L -1 ferrous iron at the minimal HRT experimented, 1.1 h. These results were satisfactory since they were in the range of the kinetics found in the literature and they were maintained during extended periods of time. Cryo-SEM observations of activated charcoal particles demonstrated the presence of precipitates on the external surface of activated charcoal (ammoniojarosite and potassiojarosite). The clogging of charcoal pores was likely to explain the decrease of the bubble column performance, at 9 g L -1 particularly, by trapping cells into solid support.

Figure 1 :Figure 2 :Figure 3 :

 123 Figure 1: Copper leaching yields versus bioleaching time in bioreactors and shake flasks in printed circuit boards bioleaching studies reported in the literature.

Figure 4 :

 4 Figure 4: Ferrous iron bio-oxidation at various HRT in 9Km medium in the presence of 15 g and 30 g of activated charcoal. Error bars depict the range of all obtained values at fixed operating conditions.

Figure 5 :

 5 Figure 5: Ferrous iron bio-oxidation at various HRT in 1Km and 1Cm media in the presence of 15 g of activated charcoal. Error bars depict the range of all obtained values at fixed operating conditions.

Figure 6 :

 6 Figure 6: Ferrous iron bio-oxidation at various HRT in 9Km and 9Cm media in the presence of 30 g of activated charcoal. Error bars depict the range of all obtained values at fixed operating conditions.

Figure 8 :

 8 Figure 8: Ferrous iron bio-oxidation at various HRT in 9Cm medium in the presence of 52 g of PVC or 30 g of activated charcoal (apparent volumes = 66 mL). Error bars depict the range of all obtained values at fixed operating conditions.

Figure

  Figure 9: Cryo-SEM pictures inside of activated charcoal particles after colonization by acidophilic bacteria. Experimental conditions in 0Km in the presence of ferrous iron concentrations at 1 g L -1 (A) and 9 g L -1 (B). For (C), experiments were performed in an Erlenmeyer under abiotic conditions in the presence of 9 g L -1 ferric iron.

Figure

  Figure 10: Cryo-SEM pictures of the surface of activated charcoal particles after colonization by acidophilic bacteria. Experimental conditions in 0Km in the presence of ferrous iron concentrations at 1 g L -1 (A) and 9 g L -1 (B). For (C), experiments were performed in an Erlenmeyer under abiotic conditions in the presence of 9 g L -1 ferric iron.

Figure 11 :

 11 Figure 11: Cryo-SEM observations of the edge of a cryo-fractured particle of activated charcoal after colonization by acidophilic bacteria in 9Km in the presence of ferrous iron concentration of 9 g L -1 .

Figure 12 :

 12 Figure 12: Cryo-SEM observation at 15 kV and EDX cartography of the edge of a cryofractured particle of activated charcoal after colonization by acidophilic bacteria in 0Km in the presence of 9 g L -1 ferrous iron.

Figure 13 :

 13 Figure 13: Comparison of bacterial diversity profiles for different HRT in liquid and solid phases (incoming ferrous iron concentrations=1 and 9 g L -1 in 0Km medium).

Table 2 : Bio-oxidation performances obtained with different ferrous iron concentrations (HRT = 12 h; Mass of activated charcoal = 15 g).

 2

			Stirred tank reactor 5 L Column 1.35 L with Ni alloy	1.8	30	16 to 100 h 4 to 12.5 h	450 1100	1 HRT	Gómez and Cantero, 2003
			fibers
			Fluidized bed
	mixed culture with L. ferrooxidans	6.9	reactor 0.9 L with activated charcoal 320 mL or 365	1.1	37	0.2 to 0.6 h	26400	N.D.	Kinnunen and Puhakka, 2004
			mL
			Fluidized bed
	mixed culture with L. ferrooxidans	7 to 21	reactor 0.9 L with activated charcoal 285 mL Fluidized bed reactor 0.4 L with activated charcoal	1	35	3.4 to 4.8 h 1.9 to 3.4 h	10000	N.D.	Kinnunen and Puhakka, 2005
			120 mL
	mixed culture with L. ferrooxidans	5.6	Airlift 3 L with solid supports	0 to 1.8	30	0.25 to 4 h	8100	3 months	Ebrahimi et al., 2005
	L. ferriphilum	5	Stirred tank reactor 1 L	1.3	42	7.8 to 67 h	670	3+1 HRT	Ojumu et al., 2008
	L. ferriphilum	12	Stirred tank reactor 1 L	1.3	18 -45	7.8 to 67 h	900	3+1 HRT	Ojumu et al., 2009
	L. ferriphilum	12	Stirred tank reactor 1 L	0.8 to 2	42	10 to 66 h	950	3+1 HRT	Ojumu and Petersen, 2011
	L. ferrooxidans	9 to 18	Chemostat 1.25 L	1.8	33.5	10 to 33 h	1000	1 HRT	Bastías and Gentina, 2010
	mixed culture with L. ferrooxidans	15	Stirred tank reactor 2 stages with settling	1.0 to 2.2	23	6 to 45 h	1100	6 days	Kaksonen et al., 2014a
	mixed culture with L. ferrooxidans	15	Airlift 2 stages with settling	1.5	23	8 to 45 h	680 -810	5 HRT	Kaksonen et al., 2014c

Table 3 : Bio-oxidation rate (rb; mg L -1 h -1 ) and yield (yc; %) vs. activated charcoal mass at 6 h HRT for two different Fe 2+ concentrations.

 3

	Activated	[Fe 2+ ] at 1 g L -1	[Fe 2+ ] at 9 g L -1
	charcoal (g)	rb (mg L h -1 ) yc (%)	rb (mg L h -1 )	yc (%)
	15	165	100%	80-780	6%-55%
	30	165	100%	650-1000	40%-70%
	45	-	-	500-1500	35%-100%

Consequently, according to the age of the support, mass transfer (Fe 2+ , nutrients, O2 and CO2) from the liquid phase to the bacteria was reduced and oxidation kinetics were lower than expected. The microbial diversity profiles in the bioreactor were different in presence of 1 or 9 g L -1 of ferrous iron : mixotrophic cells were in higher proportions in 9 g L -1 bubble column, as mass transfer were limited due to the clogging whereas autotrophic cells (particularly Leptospirillum ferriphilum) were in higher proportions in 1 g L -1 bubble column. With this knowledge, operating conditions of such a bioreactor can be adapted to be adequate to the subsequent step of the process, i.e. the leaching of PCBs.

Acknowledgements

This work was supported by the Chair "Mines Urbaines" from ParisTech foundation supported by Eco-systèmes. Authors would like to thank Christopher G. Bryan for his careful reading of the paper.

Ahumada, E., Lizama, H., Orellana, F., Suárez, C., Huidobro, A., Sepúlveda-Escribano, A., Rodríguez-Reinoso, F., 2002. Catalytic Yang, Y., Chen, S., Li, S., Chen, M., Chen, H., Liu, B., 2014. Bioleaching waste printed circuit boards by Acidithiobacillus ferrooxidans and its kinetics aspect. Journal of Biotechnology, 173, 24-30. Yue, G., Guezennec, A.G., Asselin, E., 2016. Extended validation of an expression to predict ORP and iron chemistry: Application to complex solutions generated during the acidic leaching or bioleaching of printed circuit boards, Hydrometallurgy, 164, 334-342. Yue, G., Zhao, L., Olvera, O.G., Asselin, E., 2014. Speciation of the H2SO4-Fe2(SO4)3-FeSO4-H2O system and development of an expression to predict the redox potential of the Fe 3+ /Fe 2+ couple up to 150 °C,Hydrometallurgy,[147][148][196][197][198][199][200][201][202][203][204][205][206][207][208][209] Zhu, N., Xiang, Y., Zhang, T., Wu, P., Dang, Z., Li, P., Wu, J., 2011. Bioleaching of metal concentrates of waste printed circuit boards by mixed culture of acidophilic bacteria. Journal of Hazardous Materials,192,2,


Benjamin Flamme

Mansour Haddad

Phannarath Phansavath

Virginie Ratovelomanana-Vidal

Alexandre Chagnes

Virginie Ratovelomanana- Vidal

Anodic Stability of New Sulfone-Based Electrolytes for Lithium-Ion Batteries

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Introduction

For more than two decades, lithium-ion batteries (LiBs) have outclassed other electrochemical energy-storage systems in day life applications such as cell phones or laptops in which classical 4V batteries are commonly used. [1][2][3] However, the need for highenergy density for other applications such as electric vehicles has recently stimulated the search for high energy density batteries, and therefore, the development of high-voltage cathode materials such as LiCoPO4, LiNiPO4, LiMn2O4 or LiNi0.5Mn1.5O4. [4][5][6][7][8][9][10] Nevertheless, the success of these materials suffers from the lack of compatible electrolytes, i.e. electrolytes that exhibit an anodic stability sufficiently high to achieve a good cycling ability with 5V cathode materials. Liquid and solid electrolytes can be advantageously used in LiBs depending on the targeted applications. Regarding solid electrolyte, the paper published by Varzi et al. [11] draws up a recent and complete panorama of challenges and prospects of the role of solid electrolytes for lithium metal batteries, which could be a very competitive technology provided that the safety issues of lithium metal batteries would be fixed. Solid electrolytes including polymeric and inorganic materials may be able to reply to this challenge but a great effort has to be done to increase ionic conductivity and improve the lithium-solid electrolyte interface, especially at low temperature. In the meantime, many efforts are focused to design new liquid electrolytes. However, these electrolytes cannot be used in lithium metal batteries because of the high reactivity of liquid electrolytes towards lithium metal and dendrites formation. They are presently used in lithium-ion batteries but many improvements must be achieved, especially regarding safety issues and lack of stability at high voltage. The most used liquid electrolytes for LiBs are composed of binary or ternary mixtures of linear and cyclic carbonates in the presence of 1 M LiPF6 (lithium hexafluorophosphate) such as ethylene carbonatedimethyl carbonate (EC-DMC), ethylene carbonate-diethyl carbonate (EC-DEC) or propylene carbonate-ethylene carbonate-dimethyl carbonate (PC-EC-DMC). [START_REF] Chagnes | Lithium Process Chemistry: Resources, Extractions, Batteries and Recycling[END_REF][START_REF] Chagnes | Lithium Ion Batteries -New Developments[END_REF] These electrolytes exhibit very good cycling ability at a graphite electrode but also at positive electrodes such as LiCoO2, LiMn2O4 or NMC (LiNi1/3Mn1/3Co1/3) around 4 V vs. Li/Li + . Other electrolytes were formulated to achieve particular specifications by using other families of organic dipolar aprotic solvents such as asymmetric alkylcarbonates, [START_REF] Geoffroy | [END_REF]15] g-butyrolactone in mixture with alkylcarbonates for low-temperature applications [16][17][18] or ionic liquid-based electrolytes for low and high temperature applications [16][17][18][19][20][21][22][23][24] , sulfone [25] , dioxalane 26 as well as less common solvents such as 3-methyl-2-oxazolidinone [27] and nitriles. [28][29][30] However, most of the studies reported in the literature are focused on the formulation of new electrolytes for LiBs containing mixtures of commercial solvents, whereas more studies should be dedicated to the synthesis of new solvents and the investigation of their properties. Flamme et al. [31] have recently published a review on the physicochemical and electrochemical properties of alkylcarbonates, ethers, esters, nitriles, and sulfones. This work showed interesting trends between the chemical structures of these molecules and their physicochemical and electrochemical properties. In particular, the authors emphasize sulfones could be good candidates as solvents for 5V electrolytes thanks to their high anodic stability. However, the main drawback for their use in LiBs is their high viscosity and their low ionic conductivity in the presence of lithium salts including LiPF6. Commercial sulfones such as dimethyl sulfone (DMS), ethyl methyl sulfone (EMS) and tetramethylene sulfone (TMS) were studied for LiBs applications. Nevertheless, their low wettability for Celgard separators and their poor compatibility towards graphite electrodes preclude their use in 4V and 5V LiBs. In 2002, Xu et al. [32] synthesized 3,3,3-trifluoromethylpropyl sulfone (FMPS, Table 1), but the electrochemical properties of this sulfone were not thoroughly investigated.

[a] Prof. A. Prof. Alexandre Chagnes (alexandre.chagnes@univ-lorraine.fr) for the investigation of the physicochemical and electrochemical properties of the electrolytes, Dr. Phannarath Phansavath and Dr. Virginie Ratovelomanana-Vidal for the synthesis of sulfones phannarath.phansavath@chimieparistech.fr (, virginie.vidal@chimie-paristech.fr).

Supporting information for this article is given via a link at the end of the document.

Accepted Manuscript

ARTICLE

Table 1. Recent sulfones at the laboratory scale for their use in LiBs. [33][34][35] Name Structure

MiPS

McPS

FMES

FMPS

FMIS

Only the five sulfones reported in Table 1 were synthesized between 2002 and 2017, [33][34][35] including three sulfones synthesized in 2017 by Su et al. [35] (trifluoromethyl ethyl sulfone (FMES), trifluoromethyl propyl sulfone (FMPS) and trifluoromethyl isopropyl sulfone (FMIS), see Table 1). Their anodic stability at a platinum electrode and the cycle ability in a full-cell composed of LiNi0.5Mn0.3Co0.2O2 (NMC532) and graphite were studied without co-solvent and in mixture with difluoroethylene carbonate (DFEC) or ethyl methyl carbonate (EMC) in the presence of LiPF6. It was shown that the addition of fluorine atoms in the structure of sulfones reduces the viscosity and improves the wettability towards Celgard separator. The authors claimed these sulfone-based electrolytes were promising for high-voltage and high-energy lithium-ion batteries. Because only a few papers relate to the synthesis of new sulfones for LiBs application, it is of great interest to synthesize new sulfones to investigate the potential of the sulfone family further. In particular, no sulfone containing ester or ether groups were reported in the literature for their use in LiBs. It seems interesting to study the effect of the addition of such chemical functions in the sulfone structure since esters and ethers are commonly known for their high anodic stability. [31] In the present work, 22 new linear and cyclic sulfones have been synthesized to investigate the effect of fluorine atoms, ethoxy, ester and nitrile moieties on viscosity, thermal stability, ionic conductivity and oxidation potentials of sulfone-based electrolytes containing lithium bis-trifluoromethanesulfonimidate (LiTFSI).

Experimental Section

Synthesis methods and electrolyte preparations

The sulfones syntheses were performed according to methods reported in the literature (Scheme 1). [36][37][38] More informations about the synthesis procedures and sulfone characterizations by NMR and GC-MS are available in the ESI. Appropriate amounts of lithium bis-trifluoromethanesulfonimidate (LiTFSI, Sigma Aldrich, Battery Grade) previously vacuum dried at 120°C overnight were mixed with the synthesized sulfones to prepare sulfone-based electrolytes at 1 mol.L -1 LiTFSI. Water contents in the electrolytes were measured by the coulometric Karl Fisher method by means of the Metrohm KF Titrando titrator. Water content was estimated at 20-30 ppm in the investigated sulfone-based electrolytes. In the case of sulfones exhibiting melting points higher than room temperature, it was possible to determine their ionic conductivities and anodic stabilities in the presence of LiTFSI by heating the electrolyte at 60 °C followed by slow cooling in order to keep the electrolyte in its liquid state (electrolytes remained liquid at room temperature because of supersaturation phenomena and metastability after LiTFSI solubilisation at high temperature).

Physicochemical characterization

Melting and boiling points of sulfones were determined by differential scanning calorimetry (DSC). DSC experiments were performed using 40 μL aluminum crucibles which were pierced prior to thermal analyses. DSC crucibles were prepared in an argon-filled glovebox containing less than 2 ppm H2O and O2. The reference cell was filled with silica. Thermograms were recorded using a Mettler Toledo DSC822e apparatus equipped with a nitrogen gas flow system cooled by liquid nitrogen. To prevent water condensation, a stream of nitrogen was continuously passed around the sample holder. The heating and cooling rates were fixed at 10 °C min -1 . Density (r) and kinematic viscosities (u) of the synthesized sulfones were determined at 25 °C by using an Anton Paar DMA 4500M and an Anton Paar Lovis 2000 ME, respectively. The dynamic viscosity (h) was deduced from the kinematic viscosity by using the following relationship: h= u/r. Ionic conductivities were measured at room temperature (23 °C) in an argon-filled glovebox containing less than 2 ppm H2O and O2 by using a Mettler Toledo FE30 equipped with an Inlab 741-4 mm probe (Mettler Toledo).

Electrochemical characterization

Oxidation potentials were studied by linear and cyclic voltammetry in classical three-electrodes cells using a platinum rotating electrode as working electrode (1000 rpm) and lithium wires as counter and reference electrodes. The same experiments were conducted using only two electrodes in a stainless steel Swagelock system using two glass fibre separators (glass microfiber filter, 691, VWR, 11 mm diameter), a working electrode of platinum (Goodfellow), glassy carbon or NMC (LiNi1/3Mn1/3Co1/3O2, Aldrich), and a counter/reference electrode of lithium. No major difference was detected on oxidation potential values using either setup. Therefore, the Swagelock system was preferred to determine oxidation potentials in the present work since only small amounts of electrolyte were available (1-2 grams of each sulfone were synthesized). Voltammetry studies were conducted at 5 mV.s -1 and recorded on an Origaflex 500 potentiostat from Origalys Electrochem. Electrochemical measurements and Swagelock assembly were carried out in an argon-filled glovebox containing less than 2 ppm H2O and O2.

Anodic stability is one of the most important criteria, especially for high voltage lithium-ion batteries. However, it is difficult to compare rigorously oxidation potentials from the literature because of the lack of uniform evaluation methods and experimental conditions. Oxidation potentials were assayed in the literature by three different methods: (i) determination of oxidation potentials under a constant density current (j), which is arbitrarily chosen, (ii) determination of oxidation potentials by plotting the slope of j=f(E) curves before and after the oxidation, and (iii) determination of the oxidation potential by measuring the leakage current over time of an electrolyte under a constantpotential electrolysis process. In this case, the current intensity reflects the electrochemical instability due to decomposition at a given potential and the anodic potential limit of the electrolyte, as indicated by a sudden jump of the leakage current. [START_REF] Chagnes | Lithium Process Chemistry: Resources, Extractions, Batteries and Recycling[END_REF]39 In the present paper, another method for determining anodic stability of electrolytes without bias was developed based on the analysis of voltammograms. In this method, the oxidation potential corresponds to the potential for which the slope of the curve j=f(E) takes over a threshold value of 1000. This slope was determined after reducing the noise of the voltammograms by means of a home-made program developed under Scilab.

Results and Discussion

Physicochemical properties of new sulfones

Electrolytes for lithium-ion batteries must exhibit a large thermal stability (low melting point and high boiling point) so that batteries could be used in a large range of temperatures. Furthermore, they must have a low viscosity to ensure high ionic conductivity and to get easier electrolyte penetration into separator and electrode porosity. Last but not least, solvent has to solubilize lithium salt at high concentration, i.e. usually around 1 mol L -1 because ionic conductivity is generally at its maximum value at this concentration. 40,41 Many studies use sulfone-based electrolytes with LiPF6 concentration of about 0.5 mol L -1 because LiPF6 cannot be dissolved at 1 mol L -1 . Conversely, LiTFSI can be more easily solubilized at 1 mol L -1 because the charge density borne by TFSI -anion is more delocalized. Therefore, LiTFSI will be used as salt in the present work. Table 2 gathers boiling point, melting point, density and dynamic viscosity of the 22 sulfones synthesized in the present work. Van der Waals interactions, hydrogen bonding, and molecular shape influence more or less the melting and boiling points. Tm: melting point; Tb: boiling point (at atmospheric pressure except when pressure is given in parentheses); r: density at 25 °C except for values with star (*) for which the temperature is equal to 60 °C; h: dynamic viscosity at 25 °C except for values with star (*) for which the temperature is equal to 60 °C. (a) no crystallization and melting peaks observed by DSC even until -70 C°.

Accepted Manuscript

If the molecules contributing to the lattice are rigid, compact and symmetrical, they tend to "fit" the best and tend to maximize interactions, which results in higher melting points as it takes more energy to separate the molecules. Examination of Table 2 seems to demonstrate that the presence of ester or carbonate groups results in an increase of the melting point probably because the presence of these chemical functions increases the molecular interactions. [31] Table 2 shows that the high melting point of sulfones is a drawback for their use in electrolyte for LiBs, especially for low temperature applications. Most of the synthesized sulfones exhibit melting points much greater than 0 °C except for MSTFA, which has a melting point very close to 0 °C and EMEES, MSPA, MSPEC, EMSA, MESL, IESL and GSL, for which no crystallization and no melting peak were observed by DSC, even at a temperature as low as -70 °C. 2). From a practical point of view, these molecules must be mixed with another solvent, which remains liquid withina large range of temperature. However, it is worth pointing out that the addition of a lithium salt into the solvent usually leads to an important decrease of the melting point of the latter (the decrease of the melting point is usually around 10-20 °C depending on the solvant and the salt concentration). In spite of the decrease of the melting point in the presence of lithium salt, it would be prefered to add a cosolvent for a use as electrolyte in LiBs.

Boiling points of the synthesized sulfones are very high (more than 200 °C except for EMEES (Table 2)). Their stability in the liquid state, even at very high temperature, is an advantage for their use in LiBs from a safety point of view. Such high boiling points can be explained by their high molecular weights because the bigger the molecule, the higher the Van der Waals interactions and the higher the boiling point. Sulfones are known to be viscous compared to other sulfurcontaining compounds such as sulfites, but their anodic stability is usually higher. [331] Cyclic sulfones are generally more viscous than linear sulfones. Table 2 shows that the addition of other groups such as ethers, esters or carbonates is responsible for a sharp increase of the dynamic viscosity because more intermolecular interactions occur. Sulfones containing carbonate groups are generally more viscous than those containing ester groups, which are themselves more viscous than sulfones containing ethers groups (Table 2). The lowest viscosity is obtained for sulfones containing ether functions. The dynamic viscosity is around 12 cP for linear sulfones and 16-19 cP for cyclic sulfones containing an ether function while the dynamic viscosity is usually greater than 30 cP for sulfones containing carbonate or ester groups. Therefore, carbonate and ester functions introduced in the structure of sulfones increase intermolecular interactions and disfavor molecular arrangements. Ionic conductivities of LiTFSI in the synthesized sulfones are gathered in Figure 1. Examination of this Figure shows that ionic conductivities of LiTFSI in the synthesized sulfones are very low (ionic conductivities reported in Figure 1 do not exceed 1 mS cm - 1 ). in order to reduce the ohmic drop in LiBs, electrolytes must exhibit high ionic conductivities. High ionic conductivity can be achieved when the lithium salt is highly dissociated in the solvent and ions can move easily in the solvent. Therefore, solvents must have a high dielectric constant and a low viscosity. Sulfones are generally characterized by high values of dielectric constants. For instance, ethyl isopropyl sulfone (EIPS) or sulfolane (SL) have a dielectric constant of 55 and 43.3 at 25 °C, respectively. [42,43] Thereby, the poor ionic conductivity of the sulfone-based electrolytes displayed in Figure 1 may be mainly due to the high values of sulfones viscosity. Electrolytes composed of LiTFSI and sulfones containing ether moiety (MEMS, EMEES MESL, EESL, IESL and GLSL in Figure 1) exhibit higher ionic conductivities than sulfones containing esters or carbonates. Ionic conductivities reach 1.5 mS.cm -1 for acyclic sulfones and 1.0 mS.cm -1 for cyclic sulfones. Sulfones with ester functions (MSEA, MSTFA, MSPA, MSPTFA, MMSA, EMSA, and ACSL) exhibit the lowest ionic conductivities, i.e. 0.2-0.3 mS.cm -1 , except EMSA which has an ionic conductivity of 0.5 mS.cm -1 likely because this solvent exhibits a slightly lower dynamic viscosity (Table 2). Electrolytes composed of LiTFSI and sulfones containing carbonate moieties (MSEMC, MSDEC, MSEiPC, MSPMC, MSPEC, MSPiPC, MCSL and ECSL) exhibit very low ionic conductivities, i.e. 0.1-0.2 mS.cm -1 at 25°C. It is clear that such low ionic conductivities represent a drawback for their use in LiBs in the absence of co-solvent. However, good electrochemical properties including formation of a stable passivation layer onto a graphite electrode and high oxidation potential could justify the use of these sulfones in electrolytes for LiBs. More investigations about their electrochemical properties are therefore required.

Anodic stability of new sulfones

Oxidation potentials of electrolytes can strongly vary depending on the nature of the solvent used in the electrolytes, the salt and the electrode. Our group reported important changes in oxidation potentials of sulfur-based electrolytes from 2.9 V to 5.8 V vs. Li/Li + depending on the chemical structure of the solvent. 24 In particular, electrocatalytic reactions can be responsible for an important drop of the oxidation potential. Such electrocatalytic reactions must be taken into account to evaluate any potential applications of electrolytes for high-density energy LiBs as these reactions diminish considerably the anodic stability of electrolytes. For instance, the oxidation potential of diethylsulfite (DES) in the presence of LiPF6 is dramatically reduced from 4.5 V to 2.9 V when oxidation tests are performed at a LiCoO2 electrode usually used in LiBs instead of a platinum electrode. However, other sulfur compounds have been reported that have interesting anodic stability. For instance, 2-(ethylsulfonyl)butane (EsBS) exhibits high oxidation potential, i.e. 5.8 V vs. Li + /Li at a LiMn2O4 electrode because no electrocatalytic reactions occur 31 . Likewise, fluoro-2-(methylsulfonyl)benzene (FS), 2-(ethylsulfonyl)propane (EiPS), 1-(ethylsulfonyl)-2-methylpropane (EiBS), 2-(ethylsulfonyl)butane (EsBS), (ethylsulfonyl)ethene (EVS), (ethylsulfonyl)cyclopentane (ESCP), 1-(propylsulfonyl)propane (DPS), 2-methylthietane 1,1-dioxide (MTS), 3-methyltetrahydrothiophene 1,1-dioxide (3Me-SL) can be considered as relevant solvents for high voltage applications. 31 For instance, 1-fluoro-2-(methylsulfonyl)benzene (FS), 2-(ethylsulfonyl)propane (EiPS) and 1-

Accepted Manuscript

ARTICLE

(propylsulfonyl)propane (DPS) exhibit oxidation potentials of 5.1 V, 5.6 V and 5.7 V vs. Li/Li + in the presence of 1 mol L -1 LiTFSI at a platinum electrode, respectively. Figures 2 and3 show voltamperograms of the synthesized sulfones reported in Table 2 in the presence of 1 mol L -1 LiTFSI at platinum and glassy carbon electrodes. It is interesting to highlight the presence of an anodic wave before the oxidation wall when platinum is used as a working electrode instead of a glassy carbon electrode. 2). Scan rate is equal to 5 mV s -1 .

A two-step mechanism may explain the presence of this anodic wave before the oxidation wall. Such a two-step mechanism is not surprising as the chemical structure of the sulfones contains two functions. Therefore, the anodic wave may be attributed to electrocatalytic oxidation of the solvent.Electrocatalytic reactions onto platinum and glassy carbon electrodes are responsible for a decrease of about 0.8 V and 0.6 V vs. Li/Li + of the anodic stability of the electrolytes, respectively (Table 3). All sulfones undergo electrocatalytic reaction onto platinum and glassy carbon electrodes but they are more sensitive to electrocatalytic reactions onto platinum electrode.

Sulfones containing ether functions, i.e. MEMS and EMEES, exhibit lower anodic stability at a glassy carbon electrode than sulfones containing ester or nitrile groups (5.0 V and 4.9 V vs. Li/Li + against 5.6 V, 5.5 V, 5.6 V vs. Li/Li + for MSEA, MMSA,

Accepted Manuscript

MCPS, respectively). There is no significant change in the anodic stability when cyclic sulfones are replaced by linear sulfones and no correlation can be deduced between the chemical structure of sulfones and their anodic stabilities. The anodic stability at a glassy carbon electrode and a platinum electrode follows the same trend but it is higher at a glassy carbon electrode. EMEES is the less stable electrolyte and the best anodic stability is achieved with MSEA.Examination of Table 3 shows that the anodic stability of sulfones containing carbonate and ester moieties is of the same order and greater than the anodic stability of ether groups. Furthermore, no significant change in the anodic stability of the sulfones is achieved when an electronegative group such as nitrile or fluorine is added in the chemical structure of the sulfones. Figure 4 shows the linear sweep voltamperograms of MESL, IESL, MCPS and MSEA at a NMC electrode as well as the corresponding oxidation potentials. The anodic wave located at about 4 V vs. Li/Li + corresponds to lithium deinsertion from NMC as previously reported: [44] LiNi1/3Mn1/3Co1/3O2 → Li1-xNi1/3Mn1/3Co1/3O2 + xLi + + xe - After this wave, the anodic wall attributed to the electrolyte oxidation is observed. The noisy signal observed for MSEA and MCPS when the anodic current suddenly increases is typical of gas formation due the electrolyte oxidation. The oxidation potential of MESL, IESL, MCPS and MSEA in the presence of 1 mol L -1 LiTFSI deduced

Conclusions

For the first time, bifunctional sulfones containing ether, ester and carbonate moieties have been synthesized to investigate their physicochemical and electrochemical properties for lithiumion batteries. The main objective of this work was focused on the search for alternative electrolytes for 5V batteries, i.e. electrolytes exhibiting high anodic stability. Bifunctional sulfones are generally more viscous than classical sulfones reported in the literature for LiBs applications, they have higher melting points and their ionic conductivities in the presence of LiTFSI do not exceed 1.2 mS cm -1 at 25 °C because of their high viscosity.

Nevertheless, ionic conductivity is high enough to envisage their use as electrolyte in LiBs alone or in the presence of a cosolvent if their high melting point is too high to be liquid near Accepted Manuscript ARTICLE room temperature. All of the synthesized sulfones have high boiling points, which brings interesting safety properties to bifunctional sulfones. Last but not least, bifunctional sulfones exhibit high anodic stability despite electrocatalytic reactions onto platinum and glassy electrodes as well as NMC cathode materials. The anodic stabilities of sulfones containing carbonate and ester moieties are of the same order and greater than the anodic stabilities of sulfones containing ether groups. It is difficult to give a general trend to find sulfone exhibiting high anodic stability because the oxidation degradation of electrolytes depends on the nature of the solvent, the salt and the electrode material caused by electrocatalytic reactions. However, it is also possible to play on salt:solvent molar ratio to improve the electrolyte stability beside the chemical structure of the molecules.

Among the different bifunctional sulfones synthesized in the present work, MESL seems to be the most interesting one for high energy density LiBs because the oxidation potential of this sulfone in the presence of LiTFSI onto NMC cathode material reaches 4.9 V vs. Li/Li + . The cyclability of MESL onto NMC and graphite electrode will be further investigated.

Introduction Experimental Section

Synthesis methods and electrolyte preparations

Physicochemical characterization

Electrochemical characterization

Results and Discussion

1 -Scheme 1 .

 11 Scheme 1. Synthetic pathways used for bifunctional sulfones synthesis.

  1,1-dioxide (GLSL), were synthesized by treating sulfolene with different alcohols in the presence of 10 mol % potassium hydroxide (Scheme 1, Reaction 6). 1,1-Dioxidotetrahydrothiophen-3-yl acetate (ACSL) yl methyl carbonate (MCSL) and 1,1-dioxidotetrahydrothiophen-3-yl ethyl carbonate (ECSL) were obtained by reacting 3-hydroxysulfolane resulting from reduction and oxidation of dihydrothiophen-3(2H)-one with chloroformates (Scheme 1, Reaction 7).

Figure 1 .

 1 Figure 1. Ionic conductivities at 25 °C of the synthesized sulfones in the presence of 1 mol.L -1 LiTFSI.

Figure 2 .

 2 Figure 2. Linear sweep voltamperograms of LiTFSI-based electrolytes containing (a) acyclic sulfones at a platinum electrode (ref. 1, 2, 13-15 in Table 2); (b) acyclic sulfones at a glassy carbon electrode (ref. 1,2,13-15 in Table 2); (c) acyclic sulfones at a platinum electrode (ref. 3-7 from Table 2); (d) acyclic sulfones at a glassy carbon electrode (ref. 3-7 in Table 2); (e) acyclic sulfones at a platinum electrode (Ref. 8-12 in Table2) and (f) acyclic sulfones at a glassy carbon electrode (8-12 from Table2). Scan rate is equal to 5 mV s -1 .

Figure 3

 3 Figure 3 Linear sweep voltamperograms of LiTFSI-based electrolytes containing the cyclic sulfones reported in Table 2 at (a) a platinum electrode and (b) a glassy carbon electrode (scan rate=5 mV.s -1 ).

Figure 4

 4 Figure 4 Linear sweep voltamperograms at a NMC electrode for LiTFSI-based electrolytes containing the sulfones #3, 13, 16 and 18 in Table 2 (scan rate= 0.05 mV s -1 ).from Figure4are 4.9 V, 4.7 V, 4.4 V and 4.5 V vs. Li/Li + , respectively. A slight decrease of the anodic stability is observed when the glassy carbon electrode or the platinum electrode is replaced by NMC because of electrocatalytic reactions. The electrocatalytic reactivity of sulfones onto NMC electrode is therefore slightly more important than onto platinum or glassy carbon electrodes. It is interesting to highlight that MESL exhibits the best anodic stability at a NMC cathode in the presence of LiTFSI among the investigated sulfones. Such a high anodic stability allows to envisage its use in electrolyte for high-voltage LiBs. In addition to the electrochemical properties of MESL, its physicochemical properties are compatible with a use in LiBs, especially because the ionic conductivity of this solvent in the presence of 1 mol.L -1 LiTFSI is high enough (1 mS.cm -1 at 25 °C) and this solvent remains liquid within a large range of temperatures (no freezing peak was observed by DSC down to -70 °C).

Table 2 .

 2 Physical properties of the synthesized sulfones.

  The other sulfones, i.e. MEMS, MSDEC, MSPTFA, EESL, are liquid at room

	Entry	Name	Structure	Tm (°C)	Tb (°C)	ρ (g.cm -3 )	η (cP)
	1	EMEES		<0 a	170	1.15	12.0
	2	MEMS		15	97 (2.0 Torr) 261	1.21	11.5
	3	MSEA		48	102-104 (2.0 Torr) 268-270	1.24 b	10.9 *
	4	MSTFA		-1	98-100 (2.0 Torr) 260-263	1.94	41.9
	5	MSEMC		42	292	1.30 *	15.5 *
	6	MSDEC		21	282	1.24 *	7.4 *
	7	MSEiPC		57	244
	8	MSPA		<0 a	250	1.23	49.2
	9	MSPTFA		5	261	1.42	>50
	10 11 12 13 14 15 16 17 18 19 20 21 22	MSPMC MSPEC MSPiPC MCPS MMSA EMSA MESL EESL IESL GLSL ACSL MCSL ECSL		42 <0 a 21 45 65 <0 a <0 a 24 <0 a <0 a 65 92 56	282 262 281 138-142 (0.6 Torr) 343-347 286 260 94-96 (0.7 Torr) 280-282 308 105-107 (0.6 Torr) 298-301 310 248 232 272	1.26 * 1.24 1.19 1.25 1.21 1.16 1.29	15.9 * >50 >50 27.5 19.1 15.8	Accepted Manuscript

ARTICLE

temperature but their use is limited to temperatures close to 20 °C. However, they could be used in LiBs of electric vehicle since the temperature into such LiBs reaches 40 °C. MSEA, MSEMC, MSDEC, MSEiPC, MSPMC, MCPS, MMSA, EESL, ACSL, MCSL, ECSL cannot be used alone as electrolytes for LiBs as they are solid at room temperature, and the melting point is greater than the temperature into LiBs of electric vehicle (Table

Table 3 .

 3 Oxidation potentials of the synthesized sulfones in the presence of 1 mol L -1 LiTFSI at glassy carbon (GC) and platinum electrodes (Eox vs. Li/Li + ).

	Molecules	Structures	Eox a Pt (V)	Eox b Pt (V)	Eox a GC (V)	Eox b GC (V)
	EMEES		4.0	4.9	/	4.7
	MEMS		4.3	5.0	/	4.9
	MSEA		4.7	5.6	5.0	5.7
	MSTFA		4.5	5.2	4.7	5.1
	MSEMC		4.7	5.6	/	5.5
			4.7	5.4	/	5.3
	MSPA		4.4	4.9	/	4.9
	MSPTFA		4.2	5.2	4.5	5.1
	MSPMC		4.4	5.3	/	/
	MSPEC		4.5	5.2	/	5.0
	MSPiPC		4.4	4.9	4.5	4.9
	MCPS		4.5	5.6	4.7	5.5
	MMSA		4.5	5.5	4.8	5.3
	EMSA		4.0	5.0	/	5.0
	MESL		4.2	5.1	4.5	5.1
	EESL		4.2	5.1	4.5	5.0
	IESL		4.0	5.3	4.4	5.1

Table 2 )

 2 ; (b) acyclic sulfones at a glassy carbon electrode (ref. 1,2,13-15 in Table 2); (c) acyclic sulfones at a platinum electrode (ref. 3-7 from Table 2); (d) acyclic sulfones at a glassy carbon electrode (ref. 3-7 in Table 2); (e) acyclic sulfones at a platinum electrode (Ref. 8-12 in Table2) and (f) acyclic sulfones at a glassy carbon electrode (8-12 from Table

Acknowledgements

We thank the Agence Nationale de la Recherche (ANR DEVEGA, 2014-2019 for a financial support, B. F.). We also thank Dr Céline Fosse for performing GC-MS analyses.

Keywords: Anodic stability; Electrolyte; Lithium ion batteries;

Oxidation; Solvent; Sulfone.


Weijie Wei

Zhi Liu

Lijin Huang

Alexis Nebout
email: alexis.nebout@irisa.fr

Olivier Le Meur
email: olemeur@irisa.fr

Saliency prediction via multi-level features and deep supervision for children with autism spectrum disorder

Keywords: Saliency prediction, visual attention, saliency model, autism spectrum disorder

come

INTRODUCTION

People with ASD perform atypically with respect to the controls while they are viewing the world. People with ASD will pay more attention to idiosyncratic objects and less focus on social objects (e.g. face) than normal humans do [START_REF] Dawson | Understanding the nature of face processing impairment in autism: insights from behavioral and electrophysiological studies[END_REF]. In [START_REF] Wang | Atypical visual saliency in autism spectrum disorder quantified through model-based eye tracking[END_REF], a three-layered saliency model is proposed to quantitatively measure the difference between ASD group and controls, and the results show that people with ASD have a stronger center-bias and less attention on faces and socially gazed regions. The study in [START_REF] Sasson | Brief report: Circumscribed attention in young children with autism[END_REF][START_REF] Sasson | Children with autism demonstrate circumscribed attention during passive viewing of complex social and nonsocial picture arrays[END_REF] show that such abnormal visual attention can be found even in children and adolescents. By collecting eye-tracking data from children with ASD while they are watching videos delivering actual courses, it is found that the unwillingness to gaze at teachers and the persistence in other areas lead to their maladaptation to school [START_REF] Higuchi | Spatiotemporal characteristics of gaze of children with autism spectrum disorders while looking at classroom scenes[END_REF]. Studying this kind of atypical visual attention would help design textbooks or CHIs (Computer Human Interfaces) for people with ASD.

The distinctive characteristic of visual attention has been regarded as a valid biomarker to assist clinicians for better ASD diagnosis [START_REF] Wadhera | Eye Tracker: An Assistive Tool in Diagnosis of Autism Spectrum Disorder[END_REF]. In [START_REF] Wan | Applying Eye Tracking to Identify Autism Spectrum Disorder in Children[END_REF], children's eye-tracking data while gazing at several short videos were exploited to discriminate ASD from TD (typical development). In [START_REF] Jiang | Learning visual attention to identify people with autism spectrum disorder[END_REF], the difference of fixation density maps, which were generated by eyetracking data, between ASD group and TD group, was exploited to drive the model generating the most discriminative features for an effective classification.

The performance of saliency prediction makes a huge progress due to the breakthrough of deep learning technique and ever-growing datasets. SALICON [START_REF] Huang | Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks[END_REF] and ML-Net [START_REF] Cornia | A deep multi-level network for saliency prediction[END_REF] re-purpose the existing deep architectures by the convolutional neural network (CNN) with two-path shared weights and multi-level features, respectively. A skip-layer network, which use hierarchical saliency information to refine coarse and local saliency response, is proposed to predict pixel saliency [START_REF] Wang | Deep visual attention prediction[END_REF]. In [START_REF] Cornia | Predicting human eye fixations via an lstm-based saliency attentive model[END_REF], the attentive convolutional long short-term memory (ConvLSTM) is integrated into a saliency attentive model for fixation prediction. The state-of-the-art saliency prediction models mentioned above can generate predictions close to human fixation maps [START_REF] Borji | Saliency prediction in the deep learning era: An empirical investigation[END_REF].

In this paper, we focus on predicting visual attention of children with ASD. Specifically, our contributions can be summarized in twofold: [START_REF] Dawson | Understanding the nature of face processing impairment in autism: insights from behavioral and electrophysiological studies[END_REF] We propose a novel saliency prediction model that exploits multi-level features and deep supervision to effectively predict the fixations of children with ASD. [START_REF] Wang | Atypical visual saliency in autism spectrum disorder quantified through model-based eye tracking[END_REF] To facilitate the proposed model to focus on learning the features of salient regions, the fixation density maps as the ground truths are processed via single-side clipping, which further boosts the saliency prediction performance. The rest of this paper is organized as follows. The proposed saliency prediction model is detailed in Section 2. Experimental results and analysis are presented in Section 3, and conclusions are drawn in Section 4.

SALIENCY PREDICTION MODEL

The CNN is proved to be an effective architecture to predict human fixations. CNN is capable of capturing both lowlevel contrast features and high-level semantic features, which describe the characteristics of the original image and help generate the predicted saliency map.

As shown in Fig. 1, we fully adopt the multi-level features derived from the dilated convolutional network (DCN) and utilize deconvolutional operations to upsample feature maps through multiple paths. The prior maps learned from ground truths are combined with the upsampled maps by using convolutional operations. The outputs of this operation are three attention maps, which are concatenated and convolved to generate the saliency map, as the output of our model. In the training phase, both attention maps and saliency map are used to calculate the loss, which is exploited to optimize our model with deep supervision manner.

Dilated Convolutional Network

VGG-16, which contains 13 convolutional layers and 3 fully connected layers, is an outstanding architecture for image classification [START_REF] Simonyan | Very deep convolutional networks for large-scale image recognition[END_REF]. Since the saliency prediction is an image-to-image task, the last three fully connected layers of VGG-16 are removed to avoid the condensation of spatial information. Besides, the pooling layers that downsample image will worsen the performance. To mitigate the influence of reduced resolution, the last max pooling layer is removed and the stride of the penultimate max pooling layer is set to 1. Besides, the kernels of three convolutional layers in the 5 th block are replaced by the dilated kernels [START_REF] Yu | Multi-scale context aggregation by dilated convolutions[END_REF] whose holes are set to 1, as shown in the red dashed boxes of Fig. 1. The outputs of the last convolutional layers in the 3 rd , 4 th and 5 th block are denoted as conv3_3, conv4_4 and conv5_3, respectively. These feature maps are fed into the deconvolution layers in multiple paths as shown by the dotted lines in Fig. 1.

Deep Supervision

We exploit the deconvolution layers to upsample feature maps, in order to supervise not only the output of the last convolutional layer but also the deep convolutional layers in the network. The deconvolution operation on feature maps, which reduces the number of channels by a factor of two while increases the spatial resolution by a factor of two, can be regarded as the reverse operation of convolution. The outputs of the three deconvolution layers are denoted as deconv3_3, deconv4_3 and deconv5_3, respectively. All the three deconvolved feature maps share the same dimension as shown in Fig. 1.

The learned prior maps come from the self-learning block in [START_REF] Cornia | Predicting human eye fixations via an lstm-based saliency attentive model[END_REF], which learns the parameters of 2D Gaussian distribution to fit the location-bias of the dataset. Deconv3_3, deconv4_3 and deconv5_3 are concatenated with the learned prior maps. The resulting three tensors pass through the convolutional layers with 64 filters and 1 filter in succession to generate the three attention maps, i.e. AM1, AM2 and AM3, respectively. Finally, the predicted saliency map SM is generated by convolving the concatenated attention maps. The loss function is defined as follows:

𝐿(𝑃, 𝐺 , 𝐹𝑃) = ∑ [𝐹 (𝑃 , 𝐺 ) + 𝐹 (𝑃 , 𝐺 ) + 𝐹 (𝑃 , 𝐹𝑃)] (1)

where 𝑃 indexes four predictions, namely SM, AM1, AM2 and AM3, G' and FP are the clipped ground truth and fixation points map. 𝐹 , 𝐹 and 𝐹 are respectively the Pearson correlation coefficient (CC), the Kullback-Leibler divergence (KL) and the normalized scanpath saliency (NSS). Specifically, they are calculated as follows:

𝐹 𝑃 , 𝐺′ = -2 × ( , ′) ( )• ( ′) (2)
where 𝜎(•) and 𝜎(•,•) represent standard deviation and covariance, respectively. Since CC has a higher value when two variables are more similar, it should multiple a negative coefficient while being added to the total loss.

𝐹 (𝑃 , 𝐺′

) = -∑ 𝐺 log ( , ) (3)
where j indicates 𝑗 pixel and N is the total number of pixels. For the same reason, 𝐹 should multiple a negative coefficient.

𝐹 (𝑃 , 𝐹𝑃) = 10 × ∑ , ( )
( ) 𝐹𝑃 ( 4
)
where M is the total number of fixations. The map 𝑃 is normalized to zero means and unit standard deviation. The above defined loss function encourages the ground truth to supervise deeper features in the network and to train a highperforming saliency prediction model.

Single-Side Clipping

Generally, the human fixation map is a binary map of fixation location. The fixation density map (FDM), as the ground truth to train the saliency prediction model, is generated by smoothing the fixation map with a Gaussian filter and performing a min-max normalization. Thus, the most salient region, which is gazed by most observers, has dense fixations. For the task of saliency prediction for children with ASD, what we concern is the attractive regions for observers with ASD. There are two sets of such attractive regions. The first set includes regions that attract attention from both ASD and TD. The features of this kind of regions can be learned through the training on large-scale eye-tracking datasets. The second set includes regions that are gazed by ASD instead of TD. The features of the second set will be learned by exploiting the ASD eye-tracking dataset to finetune the model. To encourage the model to precisely predict the regions gazed by most observers with ASD, we process the FDM by single-side clipping (SSC) as follows:

𝐺 (𝑖) = 0 , 𝐺(𝑖) ≤ 𝑇 𝐺(𝑖) , 𝐺(𝑖) > 𝑇 (5)
where 𝑖 indexes the 𝑖 pixel, 𝐺 is the original FDM that is generated from fixation map, and 𝐺′ is the processed ground truth. The threshold 𝑇 is set to 0.05 empirically. By using SSC, the salience of the regions where most ASD observers pay attention on are reserved, while the salience of other regions where few ASD observers gaze are depressed.

EXPERIMENTAL RESULTS

Experimental setup

For saliency prediction model, the backbone (i.e., VGG-16) is initialized by the pre-trained parameters on ImageNet [START_REF] Russakovsky | Imagenet large scale visual recognition challenge[END_REF]. The other parameters are initialized according to Xavier normalization [START_REF] Glorot | Understanding the difficulty of training deep feedforward neural networks[END_REF]. First, our model was trained on the MIT1003 dataset [START_REF] Judd | Learning to predict where humans look[END_REF] with an initial learning rate of 1e-4.

The training set of ASD eye-tracking dataset [START_REF] Duan | A dataset of eye movements for the children with autism spectrum disorder[END_REF] contains 300 images, which are split to 240, 30 and 30 for training, validation and testing, respectively. Then we finetuned the model on the first 240 images with a learning rate of 1e-6 and evaluated its performance on the validation set. Finally, the performance of our model is tested on the last 30 images. The same operations are performed for the two compared models, i.e. SalGAN [START_REF] Pan | Salgan: Visual saliency prediction with adversarial networks[END_REF] and SAM-VGG [START_REF] Cornia | Predicting human eye fixations via an lstm-based saliency attentive model[END_REF]. The saliency prediction maps are evaluated with five well-known metrics, i.e. similarity (SIM), CC, AUC Judd (AUC-J), NSS, and KL.

Comparison with state-of-the-art models

As shown in [START_REF] Duan | Learning to Predict where the Children with Asd Look[END_REF], by finetuning five state-of-the-art saliency prediction models on the ASD eye-tracking dataset, it was found that SalGAN [START_REF] Pan | Salgan: Visual saliency prediction with adversarial networks[END_REF] and SAM-VGG [START_REF] Cornia | Predicting human eye fixations via an lstm-based saliency attentive model[END_REF] outperform the other three models including SALICON [START_REF] Huang | Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks[END_REF], ML-Net [START_REF] Cornia | A deep multi-level network for saliency prediction[END_REF] and SAM-ResNet [START_REF] Cornia | Predicting human eye fixations via an lstm-based saliency attentive model[END_REF]. Therefore, SalGAN and SAM-VGG are selected for comparison in this paper. Besides, the classical model GBVS [START_REF] Harel | Graph-Based Visual Saliency[END_REF] is also compared. As shown in Table 1, our model with SSC (the bottom line in Table 1) outperforms all the other models. Our model without SSC still performs better than the other three models.

As shown in Table 2, the performance of our model on the evaluation set is not as good as the performance on the test set. This is explainable considering that the images in the test set are more similar to the images in the validation set than those in the evaluation set. Some examples of saliency maps generated by all the five models are shown in Fig. 2. It can be seen that our model is capable of better capturing salient regions at different locations. Besides, our model performs better in predicting low-saliency region, and better suppresses irrelevant regions than other models.

CONCLUSION

In this paper, we have presented a novel saliency prediction model suitable to children with ASD. The fusion of multilevel features, deep supervision on attention maps, and the single-side clipping operation on ground truths contribute the higher prediction performance of our model Moreover, we demonstrate that it is necessary to first train the model on eye-tracking dataset of normal humans to learn salience of most attractive regions, and then finetune the model on the ASD eye-tracking dataset for more effective saliency prediction.

Fig. 1 .

 1 Fig. 1. Overview of the proposed network architecture. The left part is the dilated convolutional network (DCN) where the layers are expressed in terms of channels_kernel_stride<holes>. The red dashed boxes indicate the modified layers.

Fig. 2 .

 2 Fig. 2. Qualitative comparison with other state-of-the-art models.

Table 1 .

 1 Comparison with state-of-the-art models on the test set with 30 images in the dataset[START_REF] Duan | A dataset of eye movements for the children with autism spectrum disorder[END_REF]. The best two scores are marked in bold and underlined.

	Model	SIM	CC	KL	NSS	AUC-J
	GBVS	0.599 0.554 0.543 0.992	0.764
	SalGAN	0.635 0.687 1.565 1.307	0.783
	SAM-VGG	0.643 0.705 0.586 1.377	0.797
	Our(w/o SSC)	0.671 0.734 0.465 1.459	0.808
	Our	0.678 0.769 0.421 1.738	0.834

Table 2 .

 2 Performance of our model on the evaluation set with 200 images in the dataset[START_REF] Duan | A dataset of eye movements for the children with autism spectrum disorder[END_REF].

	Model	SIM	CC	KLD	NSS	AUC-J
	Our	0.623 0.681 0.590 1.510	0.818

This work was supported by the National Natural Science Foundation of China under Grant No. 61771301.