A Hollingsworth
email: anthony.hollingsworth@ukaea.uk

M Yu Lavrentiev

R Watkins

A C Davies

S Davies

R Smith

D R Mason

A Baron-Wiechec

Z Kollo

J Hess

A Baron- Wiechec

I Jepu

K Heinola

J Likonen

K Mizohata

E Meslin

M.-F Barthe

A Widdowson

I S Grech

K Abraham

A Mcshee

Y Martynova

M Freisinger

A De Backer

Comparative Study of Deuterium Retention in Irradiated Eurofer and Fe-Cr from a new Ion Implantation Materials Facility

Keywords: Tritium, deuterium, Eurofer, iron-chromium, implanting, retention

come

Comparative study of deuterium retention in irradiated

Eurofer and Fe-Cr from a new ion implantation materials facility

Introduction

In the present nuclear fusion devices and in the future fusion power plants, the plasma interacts with the first wall, and affects the blanket and the divertor. In the next-step fusion device ITER, the main materials facing the plasma are beryllium and tungsten [1][2][3], whereas in the future demonstration fusion reactor DEMO the first wall material mix comprises of tungsten and reduced-activation ferriticmartensitic (RAFM) steels [4][5][6]. The structural materials of the vacuum vessel are austenitic steels but research on advanced materials like the RAFM steel Eurofer97 is ongoing. The engineering and research challenges are the control and the understanding of the evolution of the mechanical properties and the tritium retention of these materials which face the extreme conditions of the plasma and/or the neutron flux due to the fusion reactions. These harsh conditions are of major concern, as hydrogen is known to alter the properties of materials, and loss of radioactive inventory is problematic in terms of both resource scarcity and conforming to regulatory constraints [7]. High energy ions and neutrons create displacement cascades leading to defects in the microstructure which, in the low fluence limit, are clusters of both vacancy and interstitial atom types. These defects can be trapping sites for hydrogen isotopes, increasing the retention and permeation properties of tritium. Further traps arise as a consequence of complex microstructure of Eurofer with grain boundaries, interfaces and possible precipitates of steel components, such as for example C, N, and O.

In this paper, we describe the experiments performed within the TRiCEM project investigating hydrogen isotopes interaction with fusion relevant first wall materials for DEMO. The ion exposure facility has been built and commissioned with helium and deuterium plasmas. Samples of Eurofer and Fe-Cr model alloy have been exposed in the facility after several levels of damage have been created in them by self-ion implantation in the University of Helsinki's ion beam laboratory. For this project we are able to combine TDS, SIMS, Transmission Electron Microscopy (TEM), and other characterization methods to study the deuterium retention and the defect creation as a function of the level of damage and their evolution with time and temperature.

Typical sample production for the TRiCEM project involves sourcing high purity certified materials which are cut using Electrical Discharge Machining (EDM). The samples are ground using SiC paper (P250 -P4000) before being polished with a diamond and colloidal silica. The polished samples have been cleaned in an ultrasonic bath with acetone and isopropanol. No heat treatment was performed, because annealing above 600°C causes irreversible changes of the microstructure and permanent loss of the mechanical properties of steels. Prepared samples were shipped to the accelerator laboratory at the University of Helsinki where high energy ions are used to damage the microstructure. The ion species used for this work are 0.5 MeV Fe + and the fluences used were 3.2×10 16/17/18 ions/m 2 for damage levels of approximately 0.01/0.1/1 dpa respectively. The irradiation levels were calculated using SRIM software with "Detailed Calculation with full Damage Cascades" option. The samples are then exposed to deuterium, using the new facility described here, before being sent for analysis.

Hydrogen isotope exposure facility

Facility

A major component of the TRiCEM project has been the design and build of a tritium capable ion exposure materials facility. Most of the development work was completed by H3AT (Hydrogen-3 Advanced Technology) staff at the UKAEA. The exposure to ions is performed within a custom Ultra-High Vacuum (UHV) implantation system. This will include a self-contained tritium handling system.

For the initial deuterium work a scaled down gas handling system is used and the deuterium gas is recirculated through the system in the same way as the tritium gas is required to be re-circulated. This ensures the deuterium and tritium results will be consistent. During the inactive stage of the experiment it is also possible to use the deuterium in a "once through" fashion where the exhaust is vented rather than re-circulated. This once through method is more comparable to techniques that are typically employed by other existing experiments.

The primary purpose of this ion exposure facility is to expose material samples to hydrogen ions, including tritium. The level of exposure must be sufficient for the analysis techniques employed, primarily TDS and SIMS, to measure the retention levels. The fluence should be high enough to enable exposures to be completed within a single working day. The ion energy should be below the threshold required to induce significant microstructural damage.

The ion exposure facility is composed of a sample loading chamber and load lock system to allow sample handling within a vacuum and to ensure potential tritium contamination is minimized as far as is practical. The sample stage has both a cooling and heating system for accurate temperature control in the range 4°C to 450°C. The low energy ions (50 eV to 2 keV) are generated in a boron nitride plasma chamber surrounded by an 86 mT multi-polar magnetic array which provides electron cyclotron resonance to allow a higher density plasma to be created. A 2.45 GHz radially symmetric microwave field is used to produce the plasma. Ions are extracted from the plasma and focused onto the sample by two high voltage plates, each with a series of 1.95 mm diameter holes. The arrangement of holes on the inner grid provides an aperture of 13 mm diameter. The system is housed within a glovebox with an interlocking activity monitor. High quality welding and components are used throughout to ensure tritium compliance. The dry scroll pump used for this project is a special prototype being developed for tritium use with Edwards vacuum Limited.

The system used for the deuterium work to date is shown below in Figure 1. A process and instrumentation diagram is shown in Figure 2. The system includes data acquisition to record ion exposure and other conditions during exposure as well as some ancillary sections for sample storage in vacuum and inventory storage or purification. The inventory can be stored in a solid state on the SAES CapaciTorr® HV200 pump which uses a ZAO getter alloy. A zeolite chamber is filled with 1/8" zeolite pellets. The main purpose is to dry the gas inventory, but zeolite is also capable of removing other potential impurities. The gas inventory is expected to include very low traces of water vapor as it is possible to generate water in a hydrogen plasma system when oxides are present. A spectrometer is used to monitor the plasma chamber and deviations from the expected deuterium spectrum can indicate trace impurities building up in the deuterium inventory. The commissioning of the system with deuterium has been used to measure the ion flux under typical exposure conditions. The variables affecting ion flux are the exposure chamber pressure (within the range 5x10 -3 mbar to 2x10 -2 mbar, typically 9x10 -3 mbar) the current supplied to the magnetron (within the range 11 mA to 70 mA, typically 40 mA), the voltage of the anode (within the range 0 V to 2 kV, typically 400 V) and the voltage of the extractor (within the range 0 V to -1 kV, typically -200 V).

The flux is not expected to be spatially uniform and the angular distribution of the ion source was measured using two complementary methods. During sample exposures the ion current impinging on two areas is measured using Keithley model 2100-6 multimeters and a comparison is made to indicate the approximate beam divergence. Ellipsometry measurements are also used to determine the erosion of an amorphous, hydrogenated carbon (a-C:H) film placed over the sample area. This erosion technique has been demonstrated to measure the angular distribution of hydrogen beams in [8]. Figure 3 shows an ellipsometry survey from a 20-minute exposure to 100 eV deuterium ions with the sample stage held at 650 K. The central area where the beam is incident has approximately uniform erosion. The approximately uniform erosion in the central region shown by the ellipsometry survey is expected when considering the 13 mm diameter aperture used for the anode of the ion source which is centered over the sample stage, where the sample holder plate is 18 mm x 15.5 mm with a 9 mm x 11.5 mm sample seat in the center. Away from the region directly underneath the aperture the beam is less uniform. This can be observed by eye, as shown in Figure 4, and is also shown by incident current measurements on the inner and outer areas where the ions land. The area of the outer part is 17 cm 2 .

The inner area, which includes the sample, is 12 cm 2 and so the area ratio is approximately 0.7. Figure 5 shows a ratio of the average current incident on each area against the total charge incident on the inner area during the exposure of 25 samples, where the measured charge in the inner area is related the total number of ions incident on the sample. The ion beam lands as a cone and these plates are approximately square, so the ratio does not relate directly to beam divergence. Although the ratio shown in Figure 5 is calculated using much larger areas than the central area of interest (typically only the inner ~1 cm 2 ), this value is useful to confirm a consistent divergence of the beam between different exposures, since the divergence is variable depending on the ion source parameters and the chamber conditions. The measured ion current during the exposure can be used to estimate the total fluence. The estimated ion fluence can be compared to the total retention measured by TDS and cross-checked against literature values for the expected deuterium uptake in the undamaged materials used for commissioning the system. During commissioning, several undamaged tungsten samples were exposed and sent for TDS analysis with a range of time intervals between the exposure and TDS analysis, as the delay period was found to be a significant factor in the measured total retention. Tungsten samples were selected here to allow comparisons with existing literature.

Benchmarking

The undamaged sample S38 was exposed over two consecutive working days for a total of 8 hours.

Overnight operation is not currently permitted in the facility, so the exposure was halted overnight.

Standard tungsten exposure conditions were used (40 mA magnetron power, 400 V on the anode and -200 V on the extractor with a plasma chamber pressure of 1 Pa and a sample stage temperature of 50°C). A gap of 2 days was then left before the TDS analysis began. The TDS used a ramp rate of 10 K/min from ambient temperature to 1000°C, where the sample was held at the maximum temperature for 1 hour. The total deuterium retention was measured at 5.81×10 19 D/m 2 . The total charge measured on the 12 cm 2 sample stage was 2.13 C. Measurements of the ion species fractions were not made for this system, however measurements of ions produced in a similar way show approximately 0.97 D3 + , 0.02 D2 + and 0.01 D + [9] suggesting an average of 2.96 deuterium atoms per incident ion and energy per ion, determined by anode potential (400 V) and number of atoms to be about 133 eV per atom. The lower limit of the fluence can be calculated by assuming the beam profile is uniform over this central part of the sample stage which falls directly below the aperture. For this example sample, the fluence is at least 8.74×10 21 tungsten alloy samples [10,11] show that the fraction of retained deuterium is expected to be between 0.5×10 -4 and 2×10 -4 for a flux of ~10 21 D/m 2 s (see [10], Table 2). The example sample used here has a retention fraction of 0.0066, almost two orders of magnitude higher. This apparent discrepancy can be explained when considering the strong dependence of the retention on the ion fluence. With retention R proportional to F 0.5 , where F is fluence [9][10][11], retention to fluence fraction should behave as R/F~F -0.5 , thus decreasing with the fluence. With fluence in [10,11] being about 10 25 D/m 2 , nearly three orders of magnitude higher than in our experiments, retention to fluence ratio should fall by more than 10 times.

Next, the flux of 3×10 17 D/m 2 s calculated for this system is a lower bound, as the beam is likely to be more dense towards the central region where the sample is located. Finally, the ion energy used for S38 is 133 eV per deuteron, whereas 40-60 eV was used in [10,11] and our sample S38 was high purity tungsten, like in [9], rather than the W-Ta alloy used in [10,11].

During sample exposure several measurements are recorded to ensure consistency. In addition to the ion current measurements these are: optical spectroscopy of the plasma emission lines, optical power output between 400 nm and 1100 nm, the sample stage temperature and various pressure readings.

Optical spectroscopy is used to monitor the impurity build up in the deuterium inventory. The silicon diode optical power meter monitors the stability of the ion source during the exposure, as do the pressure readings, and the sample stage temperature is required for the automated temperature control system.

In future tritium experiments, the tritium inventory will be recirculated through the plasma chamber. In order to ensure current deuterium results are consistent with future tritium results the deuterium inventory is also recirculated. A spectrometer is used to measure the deuterium purity over time to ensure the results are not skewed by significant formation of hydrocarbons and water. Figure 6 shows a typical spectrum observed with a Hamamatsu C10083CAH spectrometer (spectral range from 320 nm to 1000 nm) after transmission through a Kodial viewport (transmission is above 85% for this range).

This measurement was taken during the exposure of sample S42. This deuterium had previously been used to expose several other samples, with approximately 20 hours of recirculation through the plasma chamber without any use of the Zeolite or getter bed to purify the deuterium. No significant differences are observed between Figure 6 and spectra recorded when using the system in a 'once through' mode where the deuterium is exhausted rather than re-circulated. The key lines of expected impurities (which do not overlap with deuterium emission lines) are not present. These are CH emission at 425 nm, C2 at 516 nm and O emission lines at 777 nm and 845 nm. Fig. 6. An example spectrum taken during the exposure of a sample using recirculating deuterium. The Dβ and Dα lines can be seen at 486 nm and 656 nm respectively, along with the Fulcher band between 560 nm and 640 nm. This spectrum indicates no significant buildup of impurities caused by re-circulation of the deuterium through the plasma chamber, suggesting deuterium results can be compared with those from other systems which typically have a 'once through' setup and exhaust the deuterium from the exposure chamber.

Results

Eurofer

As described above (see Introduction), Eurofer samples were irradiated up to 1 dpa by 0.5 MeV Fe + ions at room temperature in the University of Helsinki's ion beam laboratory. After exposure to deuterium plasma up to an estimated fluence of 10 23 D/m 2 , TDS analysis was performed by the UKAEA.

The samples were heated to 1000°C with a constant rate of 10 K/min, and the amount of hydrogen and deuterium was counted. Figure 7 shows deuterium spectra as a function of temperature and the total exposure charge (overall charge of D ions). SIMS analysis of the samples was performed in VTT, Finland, and TEM at CEA Saclay, France.

TDS spectra (Figure 7) demonstrate the existence of three peaks of different heights. The first peak is situated between 150°C and 200°C for samples irradiated below 1 dpa. The release of deuterium in this peak begins at temperatures just above 50°C, i.e. just above the exposure temperature. For the 1 dpa samples, the first peak is much lower and shifted to higher temperatures of about 220-300°C. The second peak at about 500-550°C is much smaller than the first. The very weak third peak at approximately 800°C might correspond to the α-γ structural phase transition in Fe. Fig. 7. TDS spectra of deuterium and exposure charge in Eurofer samples with damage levels between 0 and 1 dpa. Time period between exposure to deuterium plasma and the TDS is 1 day for all samples. The lower limit of the charge incident on the sample is indicated. It can be seen that the retention is more strongly affected by the damage level than the ion fluence.

For the purposes of analysis of SIMS results on the penetration of deuterium in the samples, the surface layer was divided into three regions: the surface (i) of 0.04 μm thickness, the damaged (ii) between 0.04 and 0.2 μm depth, and the bulk (iii) between 0.2 and 8 μm. The range of the damaged region was estimated using damage calculations performed with SRIM software [13][14][15]. Distribution of deuterium in these regions is shown in Figure 8. The deuterium concentration in the damaged region increases up to 0.1 dpa. For the damage level of 1 dpa, however, the concentration and penetration depth of deuterium decreases compared to the 0.01 and 0.1 dpa samples, thus confirming similar decrease found in TDS spectra.

Fig. 8. SIMS depth profiling of deuterium content of damaged Eurofer samples. Irradiation doses: S6 -0 dpa, S15 -0.01 dpa, S27 -0.1 dpa, and S33 -1 dpa. Time delay between exposure to deuterium plasma and the SIMS is given in days.

The in-situ TEM (Figure 9) revealed cavities which form along grain boundaries and precipitates around 625°C. It is possible that these cavities are formed by clustering of vacancies which start to diffuse after deuterium atoms have been released in the second TDS peak. Figure 9(b,c) shows dark and bright field images where cavities are revealed by the change of contrast.

Iron-chromium alloy

TDS analysis of model Fe-Cr alloys with chromium content of 8 weight % was performed in Forschungszentrum Jülich, Germany, with time delay between exposure and the TDS ranging between 3 and 20 days. This differs from the case of Eurofer, where all samples were analyzed one day after the exposure; however, several important conclusions can be made. TDS spectra (Figure 10) show a rapid rise of deuterium content in irradiated samples (S51, S57, S64) compared to an unirradiated one (S128), with the total amount of absorbed deuterium almost independent of the dose. Total deuterium inventory

Δf<0 Δf>0 c) b) a)
in unirradiated sample was found to be 1.93×10 20 D/m 2 , for irradiated samples it was between 4.6×10 20 D/m 2 and 5.6×10 20 D/m 2 . Similar to the case of Eurofer, several main peaks can be identified: at around 150°C, 450-500°C, close to 700°C, and possibly around 800°C. The first peak is much lower compared to the high temperature peaks, unlike the case of Eurofer. Also, the first peak changes very little with irradiation dose, while the second and third peaks rise sharply for irradiated samples compared to the unirradiated one. Rapid saturation of total deuterium inventory and absence of its fall at dose of 1 dpa are further differences between Fe-Cr alloy and Eurofer. Fig. 10. TDS spectra of deuterium in Fe-Cr samples with damage levels between 0 and 1 dpa. Irradiation doses: S128 -0 dpa, S51 -0.01 dpa, S57 -0.1 dpa, and S64 -1 dpa. SIMS analysis of Fe-Cr samples was performed after between 55 to 59 days after exposure. The results shown in Figure 11 show a substantial decrease in deuterium content in damaged regions for sample irradiated to 0.01 dpa compared to doses of 0.1 and 1 dpa. Again, the comparison with SIMS on Eurofer samples is difficult because of different time delays between exposure and analysis; still it is worth mentioning contrast with almost equal content of deuterium in damaged zone of Eurofer for doses of 0.01 and 0.1 dpa (Figure 9).

Discussion and conclusions

Overall deuterium retention for all samples studied is shown as a function of time between exposure and analysis in Figure 12. The straight line corresponds to the dependence of total inventory of deuterium in unirradiated samples of Eurofer. The time dependence for that line is close to inversely proportional (exactly, it behaves as t -1.15 ). This exponent is consistent with similar experiments on tungsten [16], where exponents between -0.7 and -1.1 were found for outgassing at room temperature.

Further, comparison of the decrease of inventory for different irradiation doses shows that for both Eurofer and Fe-Cr alloy, higher dose results in slower decrease. The first peak at 150-200°C corresponds to release of deuterium from the weakest traps or the interstitial positions. Comparison of TDS in Eurofer and Fe-Cr shows that this peak is considerably lower in Fe-Cr. This could be due to release of deuterium during the delay between exposure and the TDS, as well as it moving to stronger traps. In order to check this, further experiments on Fe-Cr with minimal delay are necessary. The position of the first peak (420-470 K) should be compared with recent similar experiments. Exposure to low energy 40 eV deuterium ions resulted in peak at 560 K [17], similar peak temperature was found for 20 eV ions [18,19]. Exposure to high energy 5 keV D3 + ions, on the other hand, results in a peak at about 400-440 K [20]. Our results were obtained after exposure to 400 eV ions, i.e. the energies are intermediate between those in [17][18][19][20]. They confirm the trend of decreasing temperature of the first peak with increasing energy of deuterium ions.

Two Eurofer samples irradiated to 1 dpa show similar differences from lower dose samples: substantial decrease in deuterium inventory and a shift of the first peak to higher temperatures (220°C for S28, almost 300°C for S19). The reasons for that change are not clear at this point, however, the similarity in this behavior strongly suggests this is a genuine effect. This is further confirmed by SIMS results that also demonstrate decrease of D content in 1 dpa samples. It was found in [19] that irradiation with 20 MeV W ions results in saturation of deuterium concentration at a peak damage at about 0.5 dpa, with the same concentration up to ~3 dpa. Still, the direct comparison between our results and those obtained in [19] is difficult, because (i) there is no data on overall D retention as a function of irradiation dose in [19], (ii) our SIMS profiles (Fig. 8) do not show a maximum in D concentration with depth, and (iii) energies of irradiation ions in [19] are almost two orders of magnitude higher than in the present study (20 MeV vs 0.5 MeV). To clarify possible decrease of D inventory with dose, further experiments with samples irradiated to intermediate as well as higher doses are planned.

The second peak at around 450-500°C (720-770 K) in Eurofer and Fe-Cr is most pronounced in Fe-Cr. This peak can be associated with release of deuterium from vacancies or vacancy cavities. This possibility should be checked further by modelling H/D release from traps with binding energy about 0.57-0.6 eV that is characteristic for vacancies [21,22]. It worth noting that in-situ TDS measurements performed 45 minutes after exposure did not reveal more than one peak up to 800 K [20]. Experiments performed with longer delay between exposure and TDS revealed second peak at about 790 K [18] or broad overlapping peaks at 730 and 900 K [17]. The third peak corresponding to the α-γ structural phase transition in Fe is very low in Eurofer, while in Fe-Cr a broad structure possibly consisting of more than one peak was found between 700 °C and 900 °C. This broadening may be due to the fact that because of longer time delays between exposure and analysis, deuterium penetrated deeper in Fe-Cr, as observed in the SIMS profiles. Note that it is not obvious that the mobility of deuterium in Fe-Cr and Eurofer is the same.

Summarizing, the first results obtained from the tritium capable ion implantation materials facility in UKAEA (Culham, United Kingdom), are presented in this paper. TDS, SIMS, and TEM study of Eurofer was performed and increase in deuterium retention with increased irradiation dose up to 0.1 dpa was observed with subsequent fall for 1 dpa samples. The TDS study of Fe-Cr alloy was performed for the first time, to the best of our knowledge. Here, the increase of deuterium content quickly reaches a plateau for Fe-Cr alloy, remaining at approximately the same level for all irradiation doses studied.

Peaks in the TDS spectra are associated with the release of most of the deuterium from interstitials, vacancies, cavities, and the α-γ structural phase transition in Fe. Time delays between exposure of samples to deuterium plasma and subsequent TDS/SIMS analysis evidently result in considerable loss of total deuterium retention, especially in the case of Fe-Cr alloy. Several notable differences are noticed between Eurofer and Fe-Cr. While some of them may be due to different time delays between exposure and analysis, other, such as deuterium retention as function of dose, might be genuine and require further studies. The results obtained in this study with deuterium will be checked by adding intermediate irradiation doses and will be compared to tritium behavior when full tritium operation of the facility becomes possible.

Fig. 1 .

 1 Fig. 1. Deuterium plasma exposure system after commissioning.

Fig. 2 .

 2 Fig. 2. Piping and Instrumentation Diagram (P&ID) of deuterium exposure system.

Fig. 3 .

 3 Fig. 3. An ellipsometry survey of an a-C:H foil exposed to 100 eV deuterium ions for 20 minutes. Region (i) shows approximately uniform erosion by the beam in the central area where the sample is located. Region (ii) shows where the left-hand retaining clip held the foil in place, and similarly the imprint of the right-hand clip can be seen to the right of the figure. Region (iii) shows where the top of the foil was shielded from the ion flux by a molybdenum foil shield and so the amount of erosion reduces sharply.

Fig. 4 .

 4 Fig.4. Photographs of commissioning plasmas. From left to right these are neon, helium, air and argon. The divergence of the ion beam can be observed.

Fig. 5 .

 5 Fig.5. The ratio of ions incident on the inner and outer plates, providing an indication of beam divergence. The ratio of the areas of these plates is 0.7.

  D/m 2 . Accounting for the exposure time the ion flux in this region is 3.04×10 17 D/m 2 s. For high-purity tungsten, retention of deuterium was measured for several valued of incident fluence in [9a]. The energy of D ions corresponded to 200 eV per deuteron, close to the one used in the current study. With flux being about two order of magnitude higher (2.5 -5×10 19 D/m 2 s), overall retention at fluence close to 10 22 D/m 2 was between 2×10 19 and 10 20 D/m 2 ([9a], Fig. 3), i.e. our results fall well within this range. Further measurements of the dependence of retention on the flux in undamaged

Fig. 9 .

 9 Fig. 9. TEM in-situ pictures of Eurofer sample irradiated to 1 dpa. Initial microstructure (a), microstructure at 625°C indicating cavities formed along grain boundaries and precipitates by change of contrast (b,c).

Fig. 11 .

 11 Fig. 11. SIMS depth profiling of deuterium content of damaged Fe-Cr samples. For S50, S56 and S62 the delays were 59, 55 and 57 days respectively.

Fig. 12 .

 12 Fig. 12. The total retention in Eurofer and Fe-Cr samples as a function of delay between exposure and analysis.

Acknowledgments

We thank M. Rieth for his help providing the material for the Eurofer samples and T. Schwartz-Selinger for many useful discussions and advice, and for providing a-C:H foils for beam characterization. Some of the research used equipment at the UKAEA's Materials Research Facility (MRF) which is part of the UK's Henry Royce Institute and National Nuclear User Facility initiatives. We thank the MRF staff for their support. This work was supported by EUROfusion Enabling Research project TRiCEM, Tritium Retention in Controlled and Evolving Microstructure and part-funded by the EPSRC Program [grant number: EP/P012450/1]. This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training program 2014-2018 and 2019-2020 under grant agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission.


Francesc Puig-Castellví

Laëtitia Cardona

Chrystelle Bureau

Delphine Jouan-Rimbaud

Christophe B Y Bouveresse

Laurent Cordella

Douglas N Mazéas

Olivier Rutledge

Chapleur

Delphine Jouan-Rimbaud Bouveresse

Christophe B Y Cordella

Laurent Mazéas

Douglas N Rutledge

Olivier Chapleur
email: olivier.chapleur@inrae.fr

Effect of ammonia exposure and acclimation on the performance and the microbiome of anaerobic digestion

Keywords: 16S rDNA sequencing, anaerobic digester, ammonia

In this study, the effect of ammonia (NH 3 ) as a disturbance on the microbial communities during anaerobic digestion (AD) was examined. NH 3 was progressively added into 5 stabilized semi-continuous bio-reactors containing biowaste at 5 different NH 3 loading rates until an inhibitory concentration was reached, and maintained at this concentration for 3 hydraulic retention times (75 days). The performance and the microbial community of the digesters were analysed. The digesters performances were hindered at higher NH 3 loading rates, marked by lower biogas productions and the accumulation of volatile fatty acids. At the microbial community level, changes depended on the NH 3 loading rate. For instance, the digester with the highest NH 3 loading rate showed a hydrogenotrophic methanogenic profile resulting from the growth of Methanosarcina spp. and acetate-consuming microorganisms, as Journal Pre-proof J o u r n a l P r e -p r o o f 2 well as the restricted growth of obligate acetoclastic archaea. This work can be helpful for the design of future acclimation strategies in AD.

Introduction

Anaerobic digestion (AD) is a multistep process for the treatment of organic waste that generates biogas by the action of the microorganisms. Biogas production in the anaerobic digesters strongly relies on the stability of the microbial community, which is influenced by the physicochemical state of the digester [START_REF] Calusinska | A year of monitoring 20 mesophilic full-scale bioreactors reveals the existence of stable but different core microbiomes in bio-waste and wastewater anaerobic digestion systems[END_REF]. For example, high levels of volatile fatty acids (VFA) production can inhibit methanogenesis by acidification [START_REF] Garcia-Peña | Anaerobic digestion and co-digestion processes of vegetable and fruit residues: Process and microbial ecology[END_REF]. Microorganisms can also be vulnerable to substances in the organic waste [START_REF] Chen | Inhibition of anaerobic digestion process: A review[END_REF]. In AD, the primary cause of methanogenesis inhibition is too high levels of Total Ammonia Nitrogen (TAN).

TAN is the combination of Free Ammonia Nitrogen (FAN or NH 3 ) and ammonium ions (NH 4 + ) [START_REF] Chen | Inhibition of anaerobic digestion process: A review[END_REF]. The chemical equilibrium between TAN and NH 3 is mainly dependent on pH and temperature [START_REF] Anthonisen | Inhibition of nitrification by ammonia and nitrous acid[END_REF]. NH 3 and NH 4 + species are commonly present in wastewater and organic waste as a result of the microbial decomposition of proteins, amino acids, uric acid and other N-containing compounds [START_REF] Islam | Functional relationship between ammoniaoxidizing bacteria and ammonia-oxidizing archaea populations in the secondary treatment system of a full-scale municipal wastewater treatment plant[END_REF].

TAN inhibition power is mainly caused by NH 3 . At the cellular level, NH 3 can produce an alteration of the intracellular pH, an increase in maintenance energy requirements, a depletion of intracellular potassium, and an inhibition of specific enzyme reactions [START_REF] Wittmann | Growth inhibition by ammonia and use of a pH-controlled feeding strategy for the effective cultivation of Mycobacterium chlorophenolicum[END_REF]. The inhibition of AD is reported to occur at a huge range of NH 3 concentrations, ranging from 27 to 1450 mg NH 3 /L [START_REF] Capson-Tojo | Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion[END_REF]. This can be explained by several factors, such as differences in digester operation and in the composition of the microbial communities [START_REF] Capson-Tojo | Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion[END_REF]. To mitigate TAN inhibitory effects, several approaches can be used including the dilution of the reactor content with water, air stripping, addition of absorbing material, lowering the operating temperature, co-digestion with high carbon content substrate, bioaugmentation, membrane separation, precipitate formation, addition of ion exchange media, and addition of trace elements [START_REF] Bayrakdar | Anaerobic digestion of chicken manure by a leach-bed process coupled with side-stream membrane ammonia separation[END_REF][START_REF] Borja | Effect of ionic exchanger addition on the anaerobic digestion of cow manure[END_REF][START_REF] Farrow | Ammonia removal from poultry manure leachate via struvite precipitation: A strategy for more efficient anaerobic digestion[END_REF][START_REF] Ortner | Efficient anaerobic mono-digestion of N-rich slaughterhouse waste: Influence of ammonia, temperature and trace elements[END_REF][START_REF] Tian | Acclimation to extremely high ammonia levels in continuous biomethanation process and the associated microbial community dynamics[END_REF]. However, the implementation of these methods is complex and associated with high operational costs.

Conversely, the acclimation of the microbial community to higher ammonia concentrations has been regarded as a practical and cost-effective strategy [START_REF] Tian | Acclimation to extremely high ammonia levels in continuous biomethanation process and the associated microbial community dynamics[END_REF]. Acclimation is a process that involves gradual adjustments within the microbial community modulated by gradual changes in their environment, improving their performance or survival [START_REF] Madigou | Acclimation strategy to increase phenol tolerance of an anaerobic microbiota[END_REF]. Thus, in the TAN inhibition scenario, microorganisms are fed with substrate containing slowly increasing concentrations of TAN. As a result of this acclimation, microorganisms are able to tolerate TAN levels up to 5 times higher than those unacclimated (Yenigün and Demirel, 2013).

In terms of microbial assessment, previous studies investigating the TAN effect in ADs have shown that the syntrophic degraders were activated at increased TAN concentrations, while some other species as cellulolytic bacteria were inactivated [START_REF] Kalamaras | Microbial adaptation to high ammonia levels during anaerobic digestion of manurebased feedstock; Biomethanation and 16S rRNA gene sequencing[END_REF][START_REF] Tian | Acclimation to extremely high ammonia levels in continuous biomethanation process and the associated microbial community dynamics[END_REF][START_REF] Yan | Acclimatization contributes to stable anaerobic digestion of organic fraction of municipal solid waste under extreme ammonia levels: Focusing on microbial community[END_REF]. Regarding the methanogenic community structure under the influence of TAN in ADs, discrepant results were found [START_REF] Capson-Tojo | Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion[END_REF].

The aim of this study is to elucidate how the process of microbial acclimation produces a change in the microbial community structure and, more precisely, to explore which microorganisms in the ADs can be acclimated. As well, the objective was to determine whether this change in the microbial community structure is independent of the TAN loading rate (or the time used to reach the highest TAN concentration) during acclimation. This analysis will give insight into the observed discrepancies found in the literature about microbial inhibition due to NH 3 in ADs [START_REF] Capson-Tojo | Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion[END_REF].

To do this, anaerobic reactors were supplemented with NH 4 Cl at different loading rates up to a final NH 3 concentration able to inhibit the AD process, and the microbial populations in the reactors during this acclimation process were characterized at different time-points using 16S DNA gene high-throughput sequencing. So, rather than looking at the NH 3 levels that can be reached by using the acclimation strategy as in previous studies [START_REF] Kalamaras | Microbial adaptation to high ammonia levels during anaerobic digestion of manurebased feedstock; Biomethanation and 16S rRNA gene sequencing[END_REF][START_REF] Tian | Acclimation to extremely high ammonia levels in continuous biomethanation process and the associated microbial community dynamics[END_REF][START_REF] Yan | Acclimatization contributes to stable anaerobic digestion of organic fraction of municipal solid waste under extreme ammonia levels: Focusing on microbial community[END_REF], in this work the effect of the time used for microbial acclimation was investigated.

In addition to this novel strategy, to our knowledge, this is the first time the system of ammonia acclimation is comprehensively studied over time at the microbial community structure level using different NH 3 acclimation times. Specifically, the sample set generated to study the microbial community evolution associated with the temporal dynamics under ammonia acclimation comprises 6 operational conditions and 8 screened time-points. In order to interpret this complex dataset, advanced chemometric methods [START_REF] Bouhlel | Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures[END_REF] were used to identify the microorganisms that responded similarly to the NH 3 acclimation process.

The outcome of this study will provide an in-depth understanding of the possible responses derived from the microbial acclimation to NH 3 during AD.

Material and methods

Feedstock and inoculum

During the course of the experiment, the bioreactor feed was prepared once a week as follows: 87 g of biowaste was diluted in biochemical potential buffer (International Standard ISO 11734 (1995)) to a final volume of 2 L to reach a concentration of 12.5 g of chemical oxygen demand per liter (COD/L). Biowaste was provided by an industrial food waste deconditioning unit (Valdis Energie, Issé, France) and kept at -20°C. Characteristics of the biowaste were as follows: dry matter = 21%, volatile matter = 92% of the dry matter, chemical oxygen demand (COD) = 287.0 gO 2 /L, dissolved organic carbon (DOC) = 2704 mgC/L, dissolved inorganic carbon (DIC) = 32 mgC/L, C=50.1% of the dry matter, N=3.4%

of the dry matter.

The inoculum was obtained from a mesophilic full-scale anaerobic digester treating primary sludge at the Valenton (France) wastewater treatment plant. To prepare the inoculum before its use, it was left under anaerobic conditions at 35°C for two weeks to digest the remaining residual organic matter [START_REF] Cardona | Co-digestion of wastewater sludge: Choosing the optimal blend[END_REF]. Characteristics of the inoculum were as follows: dry matter = 1%, volatile matter = 61% of the dry matter, chemical oxygen demand (COD) = 12.9 g O 2 /L, dissolved organic carbon (DOC) = 149 mgC/L, dissolved inorganic carbon (DIC) = 753 mgC/L, C=22.6% of the dry matter, N=2.2% of the dry matter.

AD experimental set-up

Six semi-continuous stirred tank reactors (Bioprocess Control AB, Sweden) with a working volume of 5 L (7 L of total reactor space) were used. Reactors were operated with a constant organic loading rate (OLR) of 0.5 g COD/L/day, a hydraulic retention time (HRT) of 25 days, an agitation of 90 rpm and at a constant temperature of 35°C. Reactor feeding was performed once a day with the previously described biowaste mixture (200 mL/day). Feeding was followed by excess liquid removal to maintain a constant volume.

The incubation consisted of 4 different periods: the initial stabilization period, the acclimation period, the plateau at the highest NH 3 concentration, and the restoration period to the initial NH 3 concentration values.

The initial period lasted for 14 weeks to stabilize the microbial communities inside the reactors. At day 98, once carbon consumption and methane production were stabilized, the process of microbial acclimation to NH 3 was started for 5 of the 6 reactors (reactors R2-R6 After reaching the desired final concentration of NH 3 , reactors R2-R6 were maintained at this concentration for 3 HRT (75 days). After that period, NH 4 Cl addition was stopped, producing a dilution effect of the NH 3 concentration due to the addition of the feed. As a consequence, NH 3 concentration was reduced down to the initial NH 3 concentrations. A summary of the NH 3 values over the course of the experiments are given in Figure 1.

Temperature and pH were monitored daily. Every week, 60 mL of liquid from the reactor were collected for the chemical and microbial community structure analyses. The samples were centrifuged at 10,000 g for 10 minutes to separate the pellets from the supernatants. Both pellets and supernatants were snapped frozen in liquid nitrogen. Pellets were kept at -80°C until the DNA extraction, and supernatants were stored at -20ºC until the chemical analysis. Every week, methane content in the gas produced was measured and gas samples were collected for isotopic composition measurements.

Gas production measurements

The biogas production flow was measured using a μFlow (Bioprocess Control). The biogas was collected in Tedlar® bags and the composition was analyzed directly from the bags using a micro gas chromatograph (CP4900, Varian) as described by [START_REF] Madigou | Acclimation strategy to increase phenol tolerance of an anaerobic microbiota[END_REF].

In addition, gas from the digesters was sampled with 7 mL vacuumed serum tubes.

The isotopic compositions of CH 4 and CO 2 (δ 13 CH 4 and δ 13 CO 2 ) in these samples were determined using a trace gas chromatograph Ultra (Thermo Scientific) attached to a Delta V Plus isotope ratio mass spectrometer via a GC combustion III (Thermo Scientific). δ 13 CH 4 and δ 13 CO 2 were used to establish whether methane was produced through an acetoclastic or a hydrogenotrophic methanogenesis process as in [START_REF] Cardona | Co-digestion of wastewater sludge: Choosing the optimal blend[END_REF]. The apparent isotopic factor (α app ) was calculated from δ 13 CH 4 and δ 13 CO 2 with the following equation: α app = (δ 13 CO 2 + 10 3 ) / (δ 13 CH 4 + 10 3 ) Eq. ( 2)

It is conventionally assumed that if α app is higher than 1.065, methane was mainly produced through the hydrogenotrophic pathway. On the other hand, if α app is lower than 1.055, methane was produced through the acetoclastic pathway [START_REF] Conrad | Quantification of methanogenic pathways using stable carbon isotopic signatures: a review and a proposal[END_REF][START_REF] Whiticar | Biogenic methane formation in marine and freshwater environments: CO2reduction vs. acetate fermentation-Isotope evidence[END_REF].

Chemical analysis

Acetic acid, butyric acid, and propionic acid were quantified in an ionic chromatograph (ICS 5000+, Thermo Fisher Scientific) equipped with an IonPAC ICE-AS1 column and using a mobile phase composed of heptafluorobutyric acid (0.4 mmol/L) and tetrabutylammonium (5 mmol/L).

Ammonium ion (NH 4 + ) concentration was determined using the Nessler"s colorimetric method following the French norm (NF T 90-105) [START_REF] Cardona | Co-digestion of wastewater sludge: Choosing the optimal blend[END_REF], and the dissolved organic and inorganic carbons were measured following the French norm NF EN 1484 using a DOC analyzer (TOC-L-Shimadzu).

Microbial structure analysis

For each reactor, the 16S DNA was sequenced for 8 samples (days 84 (before acclimation), 98 (start of acclimation), 105, 112, 133, 154, 182 and 217). This sampling aimed to determine the evolution of the microbial communities during the period of acclimation to NH 3 .

Total DNA was extracted from the pellet using Powersoil™ DNA isolation kit (Mobio Laboratories Inc. Carlsbad) according to the manufacturer"s instructions. Extracted DNA concentrations were determined using a quantifying fluorescent dye assay (Qubit dsDNA HS Assay Kit, Invitrogen, Eugene) and Qubit 2.0 Fluorometer (Invitrogen, Life Technologies, Eugene).

The DNA extracted by this method was used for the amplification of the bacterial and archaeal hypervariable region V4-V5 of the 16S rDNA genes with the primers 515F (5′-GTGYCAGCMGCCGCGGTA-3′) [START_REF] Wang | Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy[END_REF] and 928R (5′-CCCCGYCAATTCMTTTRAGT-3′) [START_REF] Wang | Conservative Fragments in Bacterial 16S rRNA Genes and Primer Design for 16S Ribosomal DNA Amplicons in Metagenomic Studies[END_REF]. More precisely, a fusion method was employed (IonAmplicon Library Preparation (FusionMethod) Protocol, Revision C). The forward primer was modified by the addition of a PGM sequencing adaptor (adaptor A: 5′-CCATCTCATCCCTGCGTGTCTCCGACTCAG-3′) and a barcode (5′-adaptor A-Barcode-515F-3′). The reverse primer was modified by the addition of a PGM sequencing adaptor (adaptor trP1: 5′-CCTCTCTATGGGCAGTCGGTGAT-3′) (5′-adaptor trP1-928R-3′).

V4-V5 region was amplified according Platinum Pfx Supermix protocol (Life Technologies) in a 50 μL reaction mixture containing 1X Pfx amplification buffer, 0.3 mM dNTP mix, 1 mM MgSO 4 , 0.3 µM of each primer, 1U of PlatinumPfx DNA polymerase, and 10-20 ng extracted DNA. The mixture was held at 94 °C for 5 min, followed by 30 cycles at 94 °C for 15 s, 50 °C for 30 s and 68 °C for 1 min, and a final extension step at 68 °C for 5 min.

PCR products were cleaned using the Agencourt AMPure XP magnetic beads purification system (Beckman Coulter) according to the manufacturer"s instructions, with a bead:amplicon ratio of 1.2, and were eluted in 45 µL TE Buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA). Quantification was done with a capillary electrophoresis bioanalyzer ( 2100Electrophoresis Bioanalyzer, Agilent Technologies, Santa Clara) using the Agilent DNA 1000 Kit (Agilent Technologies). Purified libraries were diluted (in a first step to 500 pM and then to 100 pM). Equal volumes of amplicons were then combined in equimolar concentrations Sequencing Kit according to the manufacturer"s instructions. The PGM software filtered out low quality and polyclonal sequence reads, and the quality filtered data was exported as FastQ file. Between 10,000 and 40,000 high quality reads were generated for each sample.

Bioinformatic analysis

The FROGS pipeline was used to analyze the 16S DNA tags reads. FROGS (Find Rapidly Operational Taxonomic Units (OTU) with Galaxy Solution) is a galaxy workflow designed to produce an OTU count matrix from high depth sequencing amplicon data [START_REF] Escudié | FROGS: Find, Rapidly, OTUs with Galaxy Solution[END_REF]. Briefly, the reads between 100 and 500 base pairs (bp) were merged and the resulting dataset was denoised. The reads kept were clustered with Swarm algorithm, and chimera and singleton reads were removed. Finally, the taxonomic affiliation of the remaining reads was determined using Silva132 16S as the reference database, resulting in 1287 different OTUs. The counts for every sample and OTU were arranged into a 48-by-1287 data matrix (samples in rows, OTU counts in columns).

Data analysis pipeline

OTU counts were analyzed using both traditional and advanced data analysis methods.

In the first approach, the microbial community structure in the reactors was investigated with bar plots of their relative abundances (Puig-Castellví et al., 2020) built using the phyloseq R-package [START_REF] Mcmurdie | phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data[END_REF]. The tolerance to NH 3 was investigated at the order level for the bacterial populations and at the genus level for the archaeal populations.

In the second approach, with the aim of getting a better understanding of the microbial dynamics across reactors and time, while maintaining the full affiliation of the microorganisms, the same data were examined using chemometric methods. In this approach, every sample was first normalized by the Relative Log Expression method [START_REF] Anders | Differential expression analysis for sequence count data[END_REF][START_REF] Badri | Normalization methods for microbial abundance data strongly affect correlation estimates[END_REF] using the scone R-package [START_REF] Cole | scone: Single Cell Overview of Normalized Expression data[END_REF]. Next,

OTUs not present in at least 20 % of the samples were discarded to reduce the dataset sparsity. Doing this, 703 OTUs were kept for further analysis. Before removal of the discarded OTUs, the randomness of their distribution in relation to the experimental setup was checked, and it was concluded that their presence could not be attributed to the ammonia addition.

The resulting OTU counts data matrix was investigated by Common Components Analysis (CCA) [START_REF] Bouhlel | Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures[END_REF][START_REF] Puig-Castellví | Assessment of the microbial interplay during anaerobic co-digestion of wastewater sludge using common components analysis[END_REF][START_REF] Rutledge | Comparison of Principal Components Analysis, Independent Components Analysis and Common Components Analysis[END_REF]. CCA searches for orthogonal components defined by a linear combination of the original variables, as in Principal Component Analysis (PCA). However, CCA has the advantage over PCA in that variables that have the same effect on the dispersion of the observations will be grouped together in the same Common Component (CC), and that the first CCs will group together the largest number of variables with the greatest effect on a particular dispersion of the individuals. In CCA, each component is composed of a scores vector (the coordinates of the sample on the orthogonal directions in the CC subspace), a loadings vector (the contributions of the original variables to the definition of the new subspace directions), and a salience vector (corresponding to the importance of the variables in defining each CC direction).

In this analysis, CCA was used to determine those OTUs that presented a similar response to the ammonia acclimation period across the different reactors. Data were columncentered and norm-scaled before CCA [START_REF] Bylesjö | Normalization and Closure[END_REF]. For each CC, variables (e.g., OTUs) associated with loading values beyond 2 standard deviations (± 2 × SD) were selected [START_REF] Bouhlel | Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures[END_REF] and graphically represented in a topological tree based on the phylogenetic data of these OTUs using the GraPhlAn online tool from the Galaxy website (http://huttenhower.sph.harvard.edu/galaxy/).

Results and discussion

1) Bioreactor performance

Figure 1 shows the chemical performance data (biogas production, methane concentration, α app , pH, volatile fatty acids acetate and propionate concentrations, DOC, and DIC), as well as the NH 3 concentration, for the different reactors over the course of the experiment.

Results from Figure1 show that the stabilization phase (which lasted until the 98 th day) had a similar behaviour in all reactors. In general, the biogas production was around 400 mL/day and contained 85% of methane. Moreover, the methanogenic profile observed during the stabilization phase was acetoclastic (α app < 1.055). The value of the NH 3 concentration stabilized at approximately 20 mg/L, which is insufficient to cause inhibition [START_REF] Capson-Tojo | Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion[END_REF]. The lack of inhibition was confirmed by the absence of VFAs accumulation and the pH constant at around 7.8. A deviation from the general performance was detected for the biogas production in R4, which was at 350 mL/day. This lower gas production was attributed to a gas leakage during stabilization. This hypothesis is supported by the fact that the rest of the parameters for R4 were comparable to those of the other reactors.

During the acclimation period, the relative CH 4 content remained stable although the biogas production dropped at a rate proportional to the NH 3 addition rate. This response suggests that the methanogenic community was strongly affected by the NH 3 addition. This is in agreement with the fact that acetoclastic methanogens are considered to be the microorganisms most sensitive to NH 3 excess [START_REF] Rajagopal | A critical review on inhibition of anaerobic digestion process by excess ammonia[END_REF].The DOC and the acetate levels increased, while the DIC decreased. This response suggests a reduced microbial activity from the species involved in the last steps of the degradation. Propionate levels also increased in the digesters with the shortest NH 3 acclimation period. The rest of the parameters followed the same profile observed during the stabilization phase.

During the plateau at the highest NH 3 concentration (represented in Fig1 by the two lines of the same color as the reactor label), some parameters varied more significantly.

At the beginning of the plateau, when ammonia level was maximum in the reactors, the lowest biogas production was observed for every reactor. This time-point also presented the maxima of DOC and the minima of DIC. In addition, for reactors R5 and R6, and to a lesser extent in reactor R2, it coincides with the minimal relative content of CH 4 in the biogas.

For R3 and R4, the relative content of CH 4 remained unaffected. After this low biogas production, the values were partially restored later. The time needed for the recovery of the gas production was longer for those digesters with the faster NH 3 addition (R5 and R6).

The methanogenic activities during the early part of the plateau period shifted towards the hydrogenotrophic profile due to the NH 3 addition, and were shifted back to acetoclastic after the biogas production was restored. The observed minima value of DIC could be a consequence of the assimilation of the dissolved CO 2 by hydrogenotrophic archaea. However, the only digester that was effectively hydrogenotrophic (α app higher than 1.065) at some point during the plateau period was R6. For R2-R5 reactors, the calculated α app values indicated mixed contributions of both acetoclastic and hydrogenotrophic methanogenesis.

In all the altered reactors (R2-R6), the increase of the NH 3 levels caused an accumulation of VFA (acetate and propionate) that reached their maxima at the plateau period (Fig. 1) revealing some degree of inhibition caused by the NH 3 addition Hence, the high values of DOC may be representative of this VFA accumulation. However, after that maxima, the VFA decreased in all digesters except for the one with the immediate NH 3 addition. This result indicates that despite all digesters being altered due to the NH 3 addition, the acclimation strategy in R2-R5 reactors allowed for a faster recovery than in R6. Derived from the accumulation of VFA, the pH during the plateau in R6 was more acid than in the other reactors (Fig. 1). Similarly, for R5, the pH was also slightly more acidic, although it returned to normal values by the end of the plateau. In reactors R2-R4, pHs were close to those in R1, indicating that the reactor conditions were more stable in those reactors in which NH 3 was added more slowly.

Finally, the decrease in the NH 3 concentration after the plateau did not modify the biogas production (except for R3, where it decreased), nor the relative content of methane, VFAs, DOCs and DICs compared to the end of the plateau. On the other hand, the decrease in NH 3 caused a basification of the pH (the change is most apparent in R2), and digesters R3 and R6 showed a methanogenic hydrogenotrophic activity. The higher variability in terms of pH and methanogenic activity across digesters in this last period can be argued as the recovery of the original NH 3 levels resulted in a less constrained environment in ecological terms. Then, the observed differences across digesters are the consequence of the stochastic readjustment of the microbial community to the new NH 3 concentration levels.

2) Relative abundance in the reactors

Overall, the microbial diversity consisted of 1287 OTUs (34 archaeal OTUs and 1253 bacterial OTUs). Of these, 91 OTUs (5 archaeal OTUs and 86 bacterial OTUs) had a relative abundance greater than 1% in at least one of the samples.

The archaeal diversity (Fig. 2A) is mainly dominated by the methanogenic archaea

Methanobacterium (1 OTU) and Methanosarcina (2 OTUs).

At the 84 th day, the sample point descriptive of the stabilization period, the relative abundance of the total archaea in R1-R6 reactors was 2.3-3.9%. Similarly, in the reactor with no NH 3 addition (R1), the archaeal diversity remained steady during all the experiment and the relative abundance of the total archaea was <3%. In reactors with slow NH 3 addition (R2-R5), the archaeal structure was similar to that of R1, but less stable over time. However,for the reactor with the fastest NH 3 addition (R6), the archaeal population total relative abundance decreased continuously during the plateau until the 133 th day, implying that the NH 3 exposure was too intense to allow the survival of the community.

In R6 and to a lesser extent in R5, coinciding with the lowered NH 3 levels at the latest time-points, the archaea levels rose to >8% of the relative abundance. The substantial increase of the archaea population was mainly associated with one Methanosarcina spp. (OTU_11).

Thus, the increase of Methanosarcina relative abundance after lowering the NH 3 levels must be regarded as an adaptation response to the acclimation period since these relative abundance values are much higher than those found in the control reactor (R1), despite the NH 3 values in R5 and R6 reactors being higher (~150 mg/L) at the latest dates. Methanosarcina is known to be more tolerant to ammonia inhibition than other archaea [START_REF] Bonk | Ammonia Inhibition of Anaerobic Volatile Fatty Acid Degrading Microbial Communities[END_REF]. It must be noted, however, that the relative abundance of Methanosarcina dropped in R6 reactor at day 217 (at the restoration period). This decrease was interpreted to be the result of the removal of the environmental pressure to the inhibited microorganisms, which can now recover their initial niche, and to the consumption of an important quantity of accumulated VFA facilitating archaea growth (Figure1).

The bacterial structure of the reactors was composed of more than 24 orders, Bacteroidales (31 OTUs), Cloacimonadales (4 OTUs), Clostridiales (23 OTUs) and Synergistales (4 OTUs) being the predominant ones (Fig. 2B).

Analogously to the archaeal structure, the bacterial structure at the 84 th day was very similar across reactors, denoting their successful stabilization.

The bacterial profile of R1 remained very stable over time, although some changes in diversity were detected. For instance, one Sphingobacteriales species (OTU_22) reached observable abundances at day 105 (Fig. 2B), and persisted during the rest of the experiment.

Two distinct bacterial dynamics depending on the NH 3 addition rate were observed.

The first was observed for R2-R5 reactors. In these reactors, Cloacimonadales were more prominent than in R1, although their presence was severely hindered in R5 at 182 nd and 217 th days (end of plateau and restoration periods, respectively) (Fig2B). This decrease seems to be connected to the recovery of Methanosarcina population for the same samples (Fig2A).

Cardiobacteriales (1 OTU), DTU014 (1 OTU), Izimaplasmatales (1 OTU), and

Spirochaetales (3 OTUs) also presented significant abundances in reactors R2-R5 compared to R1. These microorganisms, together with the archaeon Methanosarcina, should be regarded as the ones most acclimatable to NH 3 .

The second microbial dynamic was observed in reactor R6. Firstly, by day 112 th (at the start of the plateau period), Cloacimonadales relative abundance became negligible. In line with the response observed for reactors R2-R5, it can be interpreted that Cloacimonadia spp.

does not tolerate a fast increase in the NH 3 levels. Secondly, at later time-points in R6, Spirochaetales (3 OTUs) and Acholeplasmatales (1 OTU) had a substantial increase, and to a lesser extent, also DTU014 (1 OTU), Enterobacteriales (4 OTUs), and MSBL9 (1 OTU), among others. This fact indicates that these microorganisms are highly tolerant and can grow despite the high ammonia concentration. The low relative abundances of Cardiobacteriales and Izimaplasmatales in R6 suggests that these two microorganisms can only be acclimated if NH 3 is added slowly.

The different temporal fluctuations observed in the reactors revealed that the microbial susceptibility to NH 3 is very complex and varies among microorganisms.

3) Microbial Response to NH 3

In order to get a general view of the dynamics of the microbial communities across reactors and time, and untangle the main growing responses to NH 3 , the microbial data were analyzed with CCA (Figure 3A-C). In this analysis only those OTUs that were detected in at least 20% of the samples (n=703 OTUs, see Methods) were considered. With CCA, the components obtained are a linear combination of the OTUs that give the same dispersion for the set of samples. Thus, CCA detects those OTUs that have a similar susceptibility to NH 3 , even if these OTUs are found at subdominant population levels. Moreover, the most significant OTUs for each component can be regarded as representative of the main microbial community dynamics (see Methods) and are discussed more in detail below.

CCA only revealed three interpretable components, and the CCA scores are given in

Fig3A-C.
The temporal evolution of the scores in Common Component 1 (CC1, Fig3A) show that the most important microbial community alteration is the inhibition that appeared after the start of NH 3 addition at day 98. In this component, score values slowly declined over time for reactor R1 samples. For reactor R2-R6 samples, the same trend was observed during the first half of the experiment, although the scores declined more steeply and reaching negative values after day 112. CC1 is therefore descriptive of a microbial community prevalent in R1

and inhibited in reactors R2-R6 at 183 mg/L of NH 3 . It is worth noting that, in reactors R2-R5, the microbial community represented by this component shows a partial tolerance to NH 3 , since it was not strongly inhibited until it was exposed to the highest NH 3 concentrations.

On the other hand, both Common Component 2 (CC2, Fig3B) and 3 (CC3 (Fig3C, respectively) were mainly representative of the microbial dynamics within just one of the reactors. Specifically, these reactors correspond to those with the two fastest NH 3 addition rates (CC2 for R5, and CC3 for R6). For these two reactors, the temporal evolution of CC2

and CC3 peaked at the 154 th and 105 th days, respectively, both coinciding with two samples from the stabilization plateau. Thus, the exposure to short acclimation periods caused two different changes in the microbial community composition (one observed in reactor R5 and the other in reactor R6).

However, while the whole acclimation period in R5 was mainly defined by CC2, CC3

was only relevant during the first half of the corresponding acclimation period in R6. This result reveals that the microbial community represented by CC3 was not stable over time and died after circa 1.5 HRT, and led to a switch of the methanogenic profile towards hydrogenotrophic methanogenesis. This disturbance could be due to the abrupt acidification (Fig1 and Fig3E). Hence, NH 3 additions similar to those used in R6 must be avoided so as to not produce microbiota instabilities.

Furthermore, CC2 also showed a mild contribution in reactor R3 during the acclimation period, although this contribution disappeared when the highest NH 3 concentration was reached. This result suggests that the microbial community defined by CC2 can only exist while the non-acclimatable microorganisms are inhibited. This was also observed in reactor R5, since CC2 contribution decreased significantly during the NH 3 restoration period.

Finally, the fact that none of the components showed positive scores during the plateau period in R2-R4 reactors points out that the NH 3 acclimation in those reactors did not require a strong readjustment of the microbial community, but it was mediated instead by physiological changes in the microorganisms.

To summarize, we can conclude than CC1 is representative of the microbial community that is inhibited by NH 3 addition, while CC2 and CC3 correspond to those that can survive the acclimation period. At the same time, microorganisms represented by CC3 can tolerate higher levels of NH 3 than those represented by CC2 (Figure 4).

4) Key microorganisms of the NH 3 acclimation

In order to focus on the most characteristic OTUs from each CC, only the OTUs with high loadings (greater than ± 2 SD) were selected and used for microbial interpretation.

Hence, 13 OTUs were selected for CC1, 45 OTUs for CC2, and 47 for CC3. In total, 103 OTUs (4 archaeal and 99 bacterial) were selected in at least one CC.

All 4 selected archaea belong to different families (Methanobacteriaceae, Methanosarcinaceae, candidatus Methanomethylophilaceae, and to an unknown family from the phylum Crenarchaeota), whereas the bacteria are from 27 different orders (see Supplementary Table S1).

OTUs selected in CC1 are from diverse orders, indicating that the inhibitory action of NH 3 is prevalent across all microbial realms. These OTUs, from Aminicenantia, Anaerolineae, Coprothermonbacteriales, and Cloacimonadales among others, are typical from sewage sludge [START_REF] Rivière | Towards the definition of a core of microorganisms involved in anaerobic digestion of sludge[END_REF]. The inhibition (and lack of adaptation) of these OTUs due to NH 3 may result from the absence of mechanisms for surviving at high NH 3 levels, which would be unnecessary for these OTUs since NH 3 concentration in sludge is typically not as elevated. Similarly, Crenarchaeota, a chemolitoautotroph archeon that grows by oxidizing NH 3 [START_REF] Könneke | Isolation of an autotrophic ammonia-oxidizing marine archaeon[END_REF], was also selected in CC1. It can be argued that the inhibition of this microorganism results from the unsuitable environmental conditions for carrying out the NH 3 oxidation, as ammonia-oxidizing archaea prefer soils with low NH 3 levels [START_REF] Di | Ammonia-oxidizing bacteria and archaea grow under contrasting soil nitrogen conditions[END_REF].

Conversely, the presence of OTUs from polyphyletic classes, such as Clostridia or Bacteroidales, is reduced in this component pointing out the preference of these microorganisms for N-enriched environments as reported elsewhere [START_REF] Rui | The core populations and cooccurrence patterns of prokaryotic communities in household biogas digesters[END_REF].

Finally, methanogenic archaea were not selected in CC1 despite it being known that they are inhibited in NH 3 rich environments (Yenigün and Demirel, 2013), suggesting that these microorganisms successfully adapted to NH 3 inhibition. This can be observed in Fig2

for Methanosarcina (with an increased abundance at the latest time-points in reactors R5 and R6) and Methanobacterium (since similar abundance levels were maintained throughout the experiment). Regarding CC2, a wide range of microorganisms was selected. Most of the selected OTUs (except for OTU_59) are associated with a better growth during the stabilization plateau in reactor R5. On the other hand, the response was severely inhibited for OTU_59 (genus Acetobacteroides). The only species reported from this genus is an acetateand hydrogen-producer [START_REF] Su | Acetobacteroides hydrogenigenes gen. nov., sp. nov., an anaerobic hydrogen-producing bacterium in the family Rikenellaceae isolated from a reed swamp[END_REF]. In this experiment, the highest acetate concentration was found in reactor R5 shortly after the start of the plateau (day 133). Thus, it is possible that inhibition of OTU_59 growth is due to acetate accumulation.

In CC2, 2 archaea were selected. One is a hydrogenotrophic Methanobacteriaceae (OTU_38), while the other is a Methanomethylophylaceae (OTU_210) capable of using methyl-amine as substrate for methane formation [START_REF] Borrel | Genomics and metagenomics of trimethylamine-utilizing Archaea in the human gut microbiome[END_REF]. It has been reported

that Methanobacteriaceae are hardly affected by NH 3 inhibition [START_REF] Bonk | Ammonia Inhibition of Anaerobic Volatile Fatty Acid Degrading Microbial Communities[END_REF]. The existence of hydrogenotrophic archaea in this component would also explain the peak in the apparent isotopic factor observed in reactors R3 and R5 after entering into the acclimatisation plateau. On the other hand, methyl-amine formation may be favoured in ammonia-rich environments (such as the in these reactors), thus promoting the growth of Methanomethylophylaceae species.

As for the bacterial OTUs selected in CC2, the most numerous phylogenetic orders are the Clostridiales (19 OTUs), Bacteroidales (8 OTUs) and Synergistales (5 OTUs).

Clostridales, together with Bacteroidales, showed an increased relative abundance due to NH 3 concentration [START_REF] De Vrieze | Ammonia and temperature determine potential clustering in the anaerobic digestion microbiome[END_REF], while Synergistales can grow in environments rich in NH 3 [START_REF] Godon | Rarity associated with specific ecological niches in the bacterial world: the "Synergistes" example[END_REF].

Within the Clostridiales, the most important families were Family XI (5 OTUs),

Family XIII (3 OTUs), Ruminococcaceae (3 OTUs) and Syntrophomonadaceae (5 OTUs).

Syntrophomonas have been described as NH 3 -tolerant [START_REF] Bonk | Ammonia Inhibition of Anaerobic Volatile Fatty Acid Degrading Microbial Communities[END_REF]. In addition, Tissierella (from Family XI) presence is known to be enhanced by the thermal hydrolysis of amino acids in sewage sludge, which is a NH 4 + -releasing chemical process [START_REF] Chen | Effects of thermal hydrolysis on the metabolism of amino acids in sewage sludge in anaerobic digestion[END_REF].

Finally, in this component, a Spirochete OTU was also selected. Nevertheless, in this case, its favorable growth in R5 could be attributed to its ability to consume acetate [START_REF] Lee | Evidence of syntrophic acetate oxidation by Spirochaetes during anaerobic methane production[END_REF], such as Syntrophomonas.

CC3 is descriptive of the microbial community resistant to a fast NH 3 addition (Fig3C). The highest level of this component is found in reactor R6, coinciding with the start of the NH 3 addition, indicating a marked preference for N-enriched media.

Only a Methanosarcina mazei archaea species was selected in CC3 while for bacteria, the major groups are the Clostridiales (26 OTUs) and the Bacteroidiales (8 OTUs). In addition, single OTUs from the bacterial orders Alphaproteobacteria, Bacilli, Desulfovibrionales, Erysipelotrichia, and Phycisphareae, among others, were also selected in CC3 (Fig. 3).

Most of the OTUs from Clostridiales and Bacteroidales were selected either in CC2 or CC3 component, showing that OTUs from these two groups have a preference for the presence of NH 3 [START_REF] De Vrieze | Ammonia and temperature determine potential clustering in the anaerobic digestion microbiome[END_REF].

Within the Bacteroidales, the most common genus was Proteiniphilum (5 OTUs).

Interestingly, in a recent publication, Proteiniphilum growth was found to be promoted by the thermal hydrolysis of proteins, which could be a source of NH 3 [START_REF] Chen | Effects of thermal hydrolysis on the metabolism of amino acids in sewage sludge in anaerobic digestion[END_REF].

Within the Clostridiales, the most common families were Clostridiaceae 1 (5 OTUs),

Christensenellaceae (4 OTUs), Ruminococcaceae (4 OTUs), Lachnospiraceae (3 OTUs) and Peptostreptococcaeae (3 OTUs).

On the other hand, two OTUs (OTU_17 and OTU_65, a Synergistales and a Betaproteobacteriales) were selected for both CC2 and CC3, revealing the capability of some microorganisms to adapt differently in presence of high NH 3 levels depending on the addition rate.

Interestingly, some of the OTUs selected for CC3 are known to play a role in the microbial community rearrangement derived from the TAN addition with no acclimation in batch AD reactors [START_REF] Madigou | Acclimation strategy to increase phenol tolerance of an anaerobic microbiota[END_REF]. For instance, the archaeon Methanosarcina mazei was the predominant archaeon when TAN levels were increased to 7.5g/L in Poirier"s study [START_REF] Madigou | Acclimation strategy to increase phenol tolerance of an anaerobic microbiota[END_REF]. In addition, in that study, Ruminococcaceae and Lachnospiraceae (among other Clostridia) were found to be predominant in reactors with low initial TAN levels (up to 10g/L), while Peptostreptococcaeae was associated with 25g/L TAN.

Furthermore, OTU_17 and OTU_65 were found to respond positively when extreme concentrations of TAN (up to 50g/L) were used.

The fact that no obligate acetoclastic methanogen was selected in CC3 can be explained by acetoclastic archaea being more sensitive to NH 3 than the hydrogenotrophic archaea [START_REF] Borja | Influence of ammonia concentration on thermophilic anaerobic digestion of cattle manure in upflow anaerobic sludge blanket (UASB) reactors[END_REF]. It has also been stated that Methanosarcina species are more resistant to high NH 3 levels than other methanogenic archaea because of their high volume to surface ratio and to their capability to form big clusters [START_REF] Calli | Community changes during start-up in methanogenic bioreactors exposed to increasing levels of ammonia[END_REF]. Moreover, the switch from acetoclastic methanogenesis to hydrogenotrophic methanogenesis (Fig3F) may have also been strengthened by the growth of bacteria that perform symbiosis or syntrophic relationship with hydrogenotrophic bacteria, such as the sulfate-reducing Desulfovibrio [START_REF] Bryant | Growth of desulfovibrio in lactate or ethanol media low in sulfate in association with H2-utilizing methanogenic bacteria[END_REF], the H 2 -producing Acetivibrio [START_REF] Patel | Metabolism of Acetivibrio cellulolyticus during optimized growth on glucose, cellobiose and cellulose[END_REF], and the acetate-oxidizing Synergistaceae [START_REF] Ito | Identification of a novel acetateutilizing bacterium belonging to Synergistes group 4 in anaerobic digester sludge[END_REF], all of which are selected in CC3. In all, this explains the accumulation of acetate in reactor R6 (Fig. 1).

The marked hydrogenotrophic profile of the microbial community described by CC3

was also observed experimentally (Fig. 3F). While reactors R1-R5 presented an acetoclastic profile over the whole course of the experiment, R6 followed a different trend, switching to a hydrogenotrophic profile after the addition of NH 3 (day 98) and peaking at day 133 (Fig. 3F).

After the acclimation period was finished, the methanogenic profile transitorily switched back to acetoclastic and then returned again to hydrogenotrophic at the last sampled day, indicating that the acclimated microbial community was in overall hydrogenotrophic.

This observed instability of the methanogenesis profile agrees with the fact that the microbial defined by CC3 did not last for all the stabilization plateau in R6 (Fig3C).

Conclusions

The strategy of NH 3 acclimation caused perturbations in the performance of all digesters, the one from the digester with the fastest NH 3 addition being the most extreme.

CCA revealed 3 main changes in the community structure derived from the NH 3 addition, associated with the inhibition of non-acclimated microorganisms and the growth of the acclimated ones. Most of these microorganisms belonged to the orders Clostridiales and Bacteroidales.

Hence, we have shown that the AD process can be acclimated to NH 3 , and that the resulting changes in the microbial community structure will be a function of the NH 3 concentration and addition rate. In F), Samples with a hydrogenotrophic methanogenic profile (α app > 1.065) were labelled with "h", while those with a marked acetoclastic methanogenic profile (α app < 1.055) were labelled with "a". Red dashed lines represent the limits of the plateau period at the highest NH 3 concentration, while the black dashed lines represent the acclimation and restoration periods. outer dots in the tree, were colored differently according to the component they were selected in: red for OTUs selected in CC1, blue for OTUs selected in CC2, and green for OTUs selected in CC3. To improve tree readability, the background of groups of OTUs at different phylogenetic levels were colored according to their average importance of the components (i.e. redder if CC1 is more important, and so on). Full phylogenetic affiliation associated with each cluster is given in Table S1. a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a a h h a a h

Figures:

(

  100 pM) for sequencing. Emulsion PCR was carried out to prepare template-positive ISPs containing clonally amplified DNA, using the Ion PGM™ Hi-Q View OT2 Kit with the Ion OneTouch™ 2 Instrument. The template-positive ISPs were enriched with the Ion OneTouch™ ES according to the manufacturer"s instructions. Sequencing was performed on Journal Pre-proof J o u r n a l P r e -p r o o f 10 an Ion Torrent Personal Genome Machine using Ion 316 chip and the Ion PGM Hi-Q View

Figure 2 .

 2 Figure 2. Microbial structure of the reactors. A) Relative abundance of archaea. B) Relative

Figure 3 .

 3 Figure 3. Heatmap representation of the reactors" evolution over time. A-C) Common Components

Figure 4 .

 4 Figure 4. Interpretation of CCA results.

Figure 5 .

 5 Figure 5. Phylogenetic tree of the OTUs selected from the CCA analysis. OTUs, represented by the

  Figure 2

  Figure 3

  Figure 5

  dynamics.Bioresour. Technol. 286, 121376. https://doi.org/10.1016/j.biortech.2019.121376 Yenigün, O., Demirel, B., 2013. Ammonia inhibition in anaerobic digestion: A review. Summary of the performance data. Vertical blue lines correspond to the start of the NH 3 addition. The two parallel lines of the same color as the reactor labels denote the limits of the plateau period at the highest NH 3 concentration. Horizontal black lines in the apparent isotopic factor (α app ) indicate the thresholds limits for the methanogenic acetoclastic (α app <1.055) or hydrogenotrophic (α app >1.065) activities in the digesters.

	Process Biochem. 48, 901-911. https://doi.org/10.1016/J.PROCBIO.2013.04.012
	Figure 1.

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Acknowledgements

This work is supported by the French ANR project DIGESTOMIC (ANR-16-CE05-0014).

Declaration of interests

☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Graphical abstract

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Highlights:

 The influence of different NH 3 loading rates in AD acclimation was tested.

 All tested acclimation strategies altered the digesters states.

 The most affected parameters were the VFA and the biogas production.

 The microbial communities were modulated by the NH 3 loading rate.

 Most of the acclimated OTUs are from the Clostridiales and bacteroidales orders.