Kheireddine Sellami
email: kheireddine.sellami.usthb@gmail.com

Annabelle Couvert

Noureddine Nasrallah

Rachida Maachi

Nassima Tandjaoui

Mahmoud Abouseoud

Abdeltif Amrane

Usthb

Bio-based and cost

Keywords: Peroxidase Immobilization, Phenols, CLEAs, Enzymatic transformation, green process

teaching and research institutions in France or abroad, or from public or private research centers.

Introduction:

Modernization and economic development have led to changes in the various industrial sectors to ensure the comfort and well-being of humans. On the other hand, they participated negatively and irreversibly to the deterioration of our environment [START_REF] Bhandari | Effect of Industrialization on Environment ( Indian Scenario ) Commerce Medical Science Effect of Industrialization on Environment ( Indian Scenario ) Ms . Deepika Bhandari Dr[END_REF]. Intensive industrialization also have a direct effect on ecosystems and severe climate changes [START_REF] Chopra | Environmental Degradation in India: Causes and Consequences[END_REF][START_REF] Jhariya | Role of Microbial Enzymes in the Bioremediation of Pollutants: A Review[END_REF]. Industrial activity releases numerous toxic chemicals compounds into water, air and soil (Mielke and McLachlan, 2020). This hazardous waste represents a significant risk to human health and can be in some cases an additional source of cancer development (Jagai present in sewage treatment plants discharged by petroleum refineries. Indeed, the concentration of phenolic compounds varies from 40 mg.L -1 to 185 mg.L -1 in the wastewater of oil refinery (Naguib DM 2019). For example, they can reach a concentration of 185 mg.L -1 for raw outlets sour water, 50 mg.L -1 for catalytic cracker and 80 mg.L -1 for post-stripping [START_REF] Hashemi | Characterization and Removal of Phenolic Compounds from Condensate-Oil Refinery Wastewater[END_REF]. Moreover, several authors have revealed the undesirable effects of phenols and their derivatives on aquatic organisms. It has been reported that exposure of algae and fish to phenol concentrations of 72.29 mg.L -1 and 14 mg.L -1 respectively, lead to their death [START_REF] Duan | Toxicological Effects of Phenol on Four Marine Microalgae[END_REF][START_REF] Patra | The Effects of Three Organic Chemicals on the Upper Thermal Tolerances of Four Freshwater Fishes[END_REF]. The same observations have been reported for exposure to p-cresol at concentrations of 45.8 mg.L 1 for algae and 28.6 mg.L 1 for fish [START_REF] Aruoja | Toxicity of 58 Substituted Anilines and Phenols to Algae Pseudokirchneriella Subcapitata and Bacteria Vibrio Fischeri: Comparison with Published Data and QSARs[END_REF][START_REF] Degraeve | Acute and Embryo-Larval Toxicity of Phenolic Compounds to Aquatic Biota[END_REF]. This is why, in order to protect the J o u r n a l P r e -p r o o f receiving environment, many wastewater treatment processes are implemented to reduce their impact on the environment [START_REF] Villegas | A Short Review of Techniques for Phenol Removal from Wastewater[END_REF].

The use of microorganisms, enzymes and immobilized cells of organisms for the degradation of phenol and p-cresol have been the subject of several studies [START_REF] Bayramoǧlu | Enzymatic Removal of Phenol and P-Chlorophenol in Enzyme Reactor: Horseradish Peroxidase Immobilized on Magnetic Beads[END_REF][START_REF] Edalli | Evaluation of P-Cresol Degradation with Polyphenol Oxidase (PPO) Immobilized in Various Matrices[END_REF][START_REF] Günther | Phenol and Cresol Metabolism in Bacillus Pumilus Isolated from Contaminated Groundwater[END_REF][START_REF] Tallur | Biodegradation of P-Cresol by Immobilized Cells of Bacillus Sp. Strain PHN 1[END_REF].However, the treatment of pollutants with microorganisms may show certain limits due to the drastic conditions in which bacterial growth must be ensured (Karigar and Rao, 2011). Therefore, the use of enzymes may be a more attractive approach to overcome these problems. Several studies have demonstrated the potential of peroxidases for wastewater bioremediation by involving free radicals, thus generating polymerized or oxidized products (Bansal and Kanwar, 2013). In addition, through work carried out by researchers on horseradish peroxidase (HRP) and soybean peroxidase (SBP), it turns out that peroxidases are an effective tool in the degradation of phenolic compounds [START_REF] Bayramoǧlu | Enzymatic Removal of Phenol and P-Chlorophenol in Enzyme Reactor: Horseradish Peroxidase Immobilized on Magnetic Beads[END_REF][START_REF] Steevensz | Crude Soybean Hull Peroxidase Treatment of Phenol in Synthetic and Real Wastewater: Enzyme Economy Enhanced by Triton X-100[END_REF]. Despite their certain efficacy in the treatment of these compounds, free enzymes also encounter problems which can lead to their denaturation and a loss of catalytic activity (Brady and Jordaan, 2009). Immobilization or insolubilization of enzymes, can give rise to a more stable biocatalyst, resistant to extreme conditions, recyclable and having the capacity to operate continuously [START_REF] Brady | Advances in Enzyme Immobilisation[END_REF]. Four traditional methods of enzymes immobilization can be distinguished mainly, including entrapment, encapsulation, fixation on support and cross-linking (Sheldon and van Pelt, 2013). Among them, cross-linking is a promising technique since the immobilization of the enzyme is possible by using bifunctional cross-linking J o u r n a l P r e -p r o o f agent to bind the enzyme molecules without using a support (Brady and Jordaan, 2009). In addition, the other techniques show some drawbacks. In the case of entrapment, the molecules of the enzymes are free but the gel which surrounds them limits their movement and act as a barrier to mass transfer, which impact reaction kinetics (Brady and Jordaan, 2009). For encapsulation, its use is limited to enzymes with substrates of small molecular size due to the diffusion limits [START_REF] Hanefeld | Understanding Enzyme Immobilisation[END_REF]. As for attachment to support by adsorption, the enzyme seems to retain certain mobility; which allows it to retain its catalytic properties. However, it has a major drawback because the interactions between the enzyme and the support are weak. The enzyme can thus be released over time, especially under industrial conditions (strong agitation). On the other hand, the ionic and covalent bindings are generally stronger but the fact remains that this technique is more expensive due to the use of the support (Sheldon and van Pelt, 2013). Therefore, the synthesis of cross-linked enzyme aggregates (CLEAs) is a simple alternative technique in its implementation; it allows the reduction of the immobilization cost compared to immobilization on support while retaining a considerable rate of initial enzyme activity. Many advantages are associated to CLEAs technology in comparison with soluble enzyme, including stability to denaturation caused by high temperature, organic solvents and proteolysis [START_REF] Sheldon | Cross-Linked Enzyme Aggregates (CLEA®s): Stable and Recyclable Biocatalysts[END_REF]. It also offers many benefits, such as volumetric productivities and recoverability, superior operational stability following the formation of a rigid structure which prevents the breakdown of the aggregated enzyme by the multipoint attachment of enzyme molecules [START_REF] Park | Substances Using Carbonic Anhydrase-Immobilized Electrospun Nanofibers Enhancing the Production of R . Sphaeroides -Derived Physiologically Active Substances Using Carbonic Anhydrase-Immobilized Electrospun Nanofibers Running Title : The Effect of CA-CLEA[END_REF][START_REF] Sheldon | Characteristic Features and Biotechnological Applications of Cross-Linked Enzyme Aggregates (CLEAs)[END_REF]. Despite several advantages, carrier-free immobilized enzymes have some drawbacks which can make its application at industrial scale complicated. The J o u r n a l P r e -p r o o f lack of control on their particle size, mass-transfer issues related to recovery operations such as filtration and centrifugation, make the CLEAs particles only partially recycled [START_REF] Cui | Optimization Protocols and Improved Strategies of Cross-Linked Enzyme Aggregates Technology: Current Development and Future Challenges[END_REF]. To overcome these constraints, several researchers have developed techniques to improve the mechanical stability of CLEAs and facilitate their recovery, by encapsulating, coating and trapping them in polymers and matrices. Penicillin G acylase have been successfully co-aggregated with aminofunctionalized superparamagnetic iron oxide nanoparticles and then cross-linked, thus allowing its efficient and rapid magnetic decantation [START_REF] Kopp | Easily Handling Penicillin G Acylase Magnetic Cross-Linked Enzymes Aggregates: Catalytic and Morphological Studies[END_REF].

Similarly, by adopting an innovative approach [START_REF] Cui | Hybrid Cross-Linked Lipase Aggregates with Magnetic Nanoparticles: A Robust and Recyclable Biocatalysis for the Epoxidation of Oleic Acid[END_REF] developed a hybrid magnetic CLEAs (HM-CSL-CLEAs) using lipase and unfunctionalized magnetite nanoparticles. The resulting CLEAs enhanced the enzyme stability to elevated temperature, increased storage stability while allowing their separation in a simple and easy manner. The same observations were concluded in the synthesis of spherical CLEAs with biosilica shell which turned out stable against denaturants, while maintaining 70% of its activity after 13 cycles [START_REF] Cui | Encapsulation of Spherical Cross-Linked Phenylalanine Ammonia Lyase Aggregates in Mesoporous Biosilica[END_REF]. In addition, the combination of traditional techniques with CLEAs technology may prove useful, as in the case of the adsorbed cross-linked phenylalanine ammonia lyase aggregate on the crude-pored microspherical silica core. The immobilized CLEAs can be precipitated naturally without filtration or centrifugation, thus reducing mass-transfer limitations [START_REF] Cui | Simple Technique for Preparing Stable and Recyclable Cross-Linked Enzyme Aggregates with Crude-Pored Microspherical Silica Core[END_REF]. However, it is important to take into consideration the biochemical properties and protein structure of each enzyme before proceeding to any immobilization [START_REF] Yamaguchi | Techniques for Preparation of Cross-Linked Enzyme Aggregates and Their Applications in Bioconversions[END_REF].

J o u r n a l P r e -p r o o f

In a circular economy objective, the present study relates to the use of a green method for the degradation of phenolic compounds, whose component is a new source of peroxidase which could succeed to SBP and HRP. In this context, Raphanussativus var. niger peroxidase was extracted and immobilized in the form of cross-linked enzyme aggregates (RSVNP-CLEAs). After preparation, optimization and characterization of RSVNP-CLEAs, the latter were evaluated for their potential in the degradation of phenol and p-cresol while investigating the parameters that can influence their elimination. This approach could provide an ecological and costeffective alternative for a large-scale enzyme treatment.

Materials and methods

Chemical reagents

Phenol (purity 99%), p-cresol (purity 99%), 4-aminoantipyrine, hydrogen peroxide solution (30% w/w) and glutaraldehyde (GA) were supplied by Sigma-Aldrich (Saint Quentin Fallavier, France). Sulfuric acid (purity ≥ 95) was purchased from AcrosOrganics (Thermo Fisher Scientific, Geel, Belgium). All solutions were prepared with ultrapure water and all reagents used for experiments were obtained from Acros and Sigma.

Protocol for RSVNP-CLEAs preparation

The enzyme was isolated from a fresh black radish using a juice extractor. The solution of crude peroxidase was filtered by four layers cheesecloth after what the solution was used to develop cross-linked aggregates of Raphanussativus var. niger peroxidase without any purification beforehand. The RSVNP-CLEAs were J o u r n a l P r e -p r o o f synthesized using a standard preparation method described by (Sheldon 2011).

Briefly, the preparation is carried out in two steps (i) the precipitation which consists in the addition of a solvent (acetone, methanol, 2-propanol, acetonitrile, and ethanol); then, three times volume of pre-cooled solvent are added dropwise to the enzyme solution. After a continuous stirring (250 rpm) for 1 hour at 4 °C, (ii) the cross-linking step occurs, glutaraldehyde (GA) using different volume concentrations, 1%, 1.5%, 2%, 2.5%, 3%, are added to the total volume solution and then allowed to react for 3 hours. The CLEAs were recovered by centrifugation at 4000g for 10 min. After each preparation, the CLEAs were washed and stored in a phosphate buffer solution (pH 7±0.2, 50 mM) at 4 °C.

For an optimal preparation of immobilized enzyme, several parameters were studied, such as the optimal precipitating agent, the enzyme and the cross-linking agent, taking into account activity recovery (Eq. ( 1)) and the aggregation yield (Eq. ( 2)) defined as reported by (Bilal et al., 2017a).

Activity recovery (%) = 100 (1) Aggregation yield (%) = 1 100 (2)
J o u r n a l P r e -p r o o f

Peroxidase activity assay

Free and immobilized enzyme activity was assayed using hydrogen peroxide and phenol as substrates; the reaction with 4-aminoantipyrene (4-AAP) forms a colored product which absorbs at (A 510 nm ) (Nicell and Wright, 1997). The mixture assay contained 1.4 mL of 4-AAP/phenol solution at a concentration of 0.0025 M and 0.17

M respectively; 0.1 mL of free enzyme or 2 mg of CLEAs and 1.5 mL of 0.0017 M hydrogen peroxide. One unit (U) of peroxidase activity corresponds to the amount of enzyme that oxidizes 1 µmol of hydrogen peroxide per min at room temperature and pH 7±0.2 (molar extinction coefficient, 7100 M -1 cm -1 ).

Protein quantification

The determination of the protein amount was made by the Bradford method (Bradford, 1976) using bovine serum albumin as a standard for the calibration curve.

Characterization of RSVNP-CLEAs

Effect of pH and temperature

Different values of pH and temperature ranging from 3 to 9 and 25 °C to 60 °C respectively were assayed to evaluate the tolerance of CLEAs compared to the free enzyme under extreme conditions. Samples were incubated without the presence of any substrate for 15 min in the previously mentioned different cases. Then, the residual activity of the samples was analyzed.

J o u r n a l P r e -p r o o f

Effect of organic solvents

Given the interest of using enzymes in organic media, RSVNP-CLEAs were evaluated by incubating a quantity of 10 mg in 10 mL of the different selected solvents with different polarities (table 1): methanol, chloroform, acetone, dimethyl sulfoxide (DMSO), hexadecane and silicone oil or polydimethylsiloxane (PDMS) V20.

Tests were conducted at room temperature for 72 h. After their recovery, the CLEAs were washed and dried then the residual activity was determined at pH 7±0.2 and 25 °C.

Storage stability

Incubation of free and immobilized enzyme for 60 days in a phosphate buffer solution (pH 7±0.2) at 4 °C was carried out to evaluate their stability over time. The percentage of initial activity (100%) of the two enzymes was considered as control.

Phenolic compounds degradation by RSVNP-CLEAs

The RSVNP-CLEAs potential to degrade selected phenolic compounds was studied in 22 mL sealed glass sacrificed vials for a given time in order to establish the degradation kinetics. The medium consisted of phosphate buffer solution (50 mM, pH 7±0.2) containing phenol or p-cresol at a given concentration, in which was added the required amount of RSVNP-CLEAs to achieve the desired activity. The reaction was started by adding gradually hydrogen peroxide (5 µL) four times every 10 min through the rubber septa. Vials were kept under permanent magnetic agitation (300 J o u r n a l P r e -p r o o f rpm) and constant temperature at 25 °C. At the end of the reaction, solutions were centrifuged at 4000 rpm for 5 min and the supernatant was acidified by a few drops of 6 M H 2 SO 4 solution to stop the reaction. After filtration, samples were taken for the determination of the residual phenol using HPLC and TOC analysis.

Biodegradation kinetics was studied by varying several parameters such as: initial pcresol and phenol concentrations in the range of 20 to 160 mg.L -1 , hydrogen peroxide dose from 0.25 to 20 mM and initial enzyme activity varied from 0.1 to 1.8 U.L -1 . The objective was to determine optimal conditions under which maximum efficiency for phenol and p-cresol degradation was realized.

Experiments were conducted in duplicate.

In order to quantify abiotic degradation, control tests were performed under the same conditions without enzyme or without hydrogen peroxide. An insignificant degradation yield of 3±1% was observed in both cases.

Degradation yield (DY) and initial degradation rate (IDR) were calculated using the (Eq. ( 3)) and (Eq. ( 4)) respectively.

DY (%) = ( 100 (3) IDR (mg.L -1 min -1 ) = (4)
Where, C 0 = Initial concentration before enzymatic treatment (mg.L -1 )

J o u r n a l P r e -p r o o f 13 C t = Final concentration after enzymatic treatment (mg.L -1 ) t 0 = Initial time of reaction (min) t f = Final time of reaction (min)

Reusability tests

Four consecutive cycles were performed to evaluate the reusability of RSVNP-CLEAs under fixed optimal conditions. Each batch was carried at room temperature 25 °C for a given time of phenol and p-cresol degradation followed by centrifugation (4000 rpm for 5 min) of the reaction media to separate the immobilized enzyme from the solution. The recovered enzyme was reused directly without any treatment or washing in the next cycle. The efficiency of RSVNP-CLEAs in each batch was calculated by means of the degradation percentage according to (Eq. ( 3)).

High performance liquid chromatography (HPLC) and Total organic carbon (TOC) analysis

The residual concentration of phenol and p-cresol was measured using an Alliance UV controller HPLC system equipped with waters 717 plus autosampler. The column was a Waters C-18 (4.6 mm × 250 mm × 5 µm). The mobile phase for phenol concentration determination was a mixture of ultrapure water/acetonitrile (30/70 v/v) with 0.1% of formic acid and the flow rate was kept at 1 mL min -1 . A ratio of (20/80 v/v) ultrapure water/acetonitrile containing 0.1% formic acid was used as the mobile phase for the p-cresol amount and set at a flow rate of 0.5 mL min -1 . The phenolic compounds were detected at 275 nm.

J o u r n a l P r e -p r o o f 14 TOC concentration was determined using a TOC-meter (Shimadzu TOC-VCSH).

Assessment of Michaelis-Menten reaction kinetics

Immobilized peroxidase was used to determine the initial reaction rates of phenol and p-cresol at various initial concentrations in the range from 20 to 160 mg.L -1 . From the data of established kinetics, Michaelis-Menten and Lineweaver-Burk curves were constructed to obtain Mechaelis-Menten kinetics constant (K m ) and the maximal velocity (V max ).

Scanning electron microscopy of RSVNP-CLEAs

The surface morphologies of the enzyme before and after degradation essays were envisaged using a JSM IT 300 apparatus from JEOL. Samples were prepared by drying and coating with gold/palladium mixture. The SEM images were obtained with 2000 × magnification.

Results and discussion

Preparation of RSVNP-CLEAs

Results from this study represent two novelties. Beyond this value (2%), the recovered activity decreased owing to the loss of enzyme flexibility, which is necessary for the catalytic activity of CLEAs (Sheldon,

J o u r n a l P r e -p r o o f 2011). It was also observed that there was no significant change in the aggregation yield above 2% (v/v) of GA; its value remained around 85%.

Characterization of RSVNP-CLEAs

Effect of pH and temperature on free and immobilized enzyme

Activity test can be carried out under different pH conditions in order to study the chemical stability of cross-linked enzyme. Results, are shown in Fig. 2a. RSVNP-CLEAs showed better stability against variations in pH compared to the free enzyme.

The relative activity of RSVNP-CLEAs was about 60% at pH 3 while it did not exceed 10% for the free enzyme. The optimum pH range was between 6 and 7 for both Temperature can have two contradictory effects in enzyme catalysis. On the one hand, it can increase the speed of the reactions by increasing the number of collisions between the substrate and the enzyme and on the other hand it can cause enzyme deactivation. The influence of the temperature variation is presented in Fig. 2b; it was found that the RSVNP-CLEAs retained more than 88% of their initial activity in an interval of 25 °C to 50 °C compared to the free enzyme which posted a significant drop at a temperature of 50 °C by preserving only 45% of its initial activity.

These results were confirmed by several authors who explained that this decrease in

Effect of organic solvents on RSVNP-CLEAs

The nature of the solvent, the size, the morphology and the microenvironment of the

Storage stability

The activity of the two forms of enzyme was monitored regularly for 60 days at 4 °C and results are presented in Fig. 2d, considering an initial activity at 100%. Free J o u r n a l P r e -p r o o f peroxidase activity was almost totally lost after 30 days of storage. A biological degradation phenomenon may be involved. In contrast, a stable activity was observed with RSVNP-CLEAs, maintaining 100% of their activity over 60 days of storage, and even an increase of 10% after 30 days of follow-up. This stability can be explained by the rigidity of CLEAs which limits enzyme structural changes (Verma et al., 2019).

Biodegradation of p-cresol and phenol

Influence of the initial concentration

The degradation capacity of RSVNP-CLEAs was evaluated for different initial concentrations of p-cresol and phenol under constant temperature of 25 °C.and pH 7±0.2. At fixed enzyme activity (0.9 U.mL -1 ), the hydrogen peroxide was added at t=0 min to initiate the enzymatic reaction so as to obtain a final concentration of 0. where the degradation of phenol is less significant than for p-cresol.

Effect of co-substrate (H 2 O 2 )

The oxidation of phenolic compounds requires the use of a co-substrate which is for phenol and 20 min for p-cresol in order to examine the influence of gradual addition mode. It was observed in both cases that degradation rate and conversion yield increased with increasing concentration of hydrogen peroxide. An optimal concentration between 2 and 3 mM of H 2 O 2 led to a maximum dephenolization and an increase in the rate of degradation by achieving at least a yield of more than 78 and 96 ± 2% with an initial rate of 3.04 ± 0.078 mg.L -1 .min -1 for phenol and 7.43 ± 0.15 mg.L -1 .min -1 for p-cresol respectively. This is valid for each concentration of phenol and p-cresol investigated. Moreover, a decrease in phenol conversion was noted at co-substrate amounts greater than 3 mM. This decline was due to the inhibitory effect It can also be noticed that RSVNP-CLEAs showed good stability at large doses of oxidant, due to its protection against denaturing agents.

Effect of RSVNP-CLEAs activity on phenols removal

A study was also carried out on the activity of RSNVP-CLEAs by varying it from 0.1 to 1.8 U.mL -1 , at initial concentrations of H 2 O 2 (2mM), phenol (100 mg.L -1 ) and pcresol (160 mg.L -1 ). From Fig 5a, it was noticed that the degradation of phenol increased with enzyme dose until it reached 92 % of phenol removal with an initial rate of 2.28 mg.L -1 .min -1 at 0.9 U.mL -1 . No further improvement was observed by increasing the amount of CLEAs introduced into the reaction medium. A dramatic decrease in phenol degradation (65% of conversion yield with a degradation rate of 1.6 mg.L -1 .min -1 ) occurred when enzyme dose decreased to 0.45 U.mL -1 . This might be justified by a decrease in the availability of active sites ready to with the target compound [START_REF] Tandjaoui | A Combination of Absorption and Enzymatic Biodegradation: Phenol Elimination from Aqueous and Organic Phase[END_REF]. The experiments also revealed that a lower amount of CLEAs was sufficient to achieve more than 98% of p-cresol degradation J o u r n a l P r e -p r o o f (Fig. 5b). Indeed, it was found that equilibrium was reached for an initial activity of 0.2U.mL -1 , namely 4 times lower than that used for phenol degradation, by achieving more than 98% conversion yield of p-cresol with an initial degradation rate of 7.43 mg.L -1 .min -1 .

Kinetics and reusability of RSVNP-CLEAs under optimal conditions

After examining the effects of the concentration of phenol and p-cresol, hydrogen peroxide and enzyme activity on the degradation process, a kinetic study was conducted under optimal conditions. RSVNP-CLEAs showed their effectiveness in the biodegradation of phenolic compounds, as illustrated in Fig. 6a and6b Evenly, researchers described the removal of phenol by immobilized HRP in porous calcium alginate where the maximum conversion yield was 50% with an activity of 7.5 U.mL -1 . after 100 min of treatment (Alemzadeh and Nejati, 2009).

The ease of recovery and recycling of the biocatalyst is one of the advantages of enzyme immobilization for efficient use. This property was verified in the case of RSVNP-CLEAs during the biodegradation process of the two phenolic compounds over 4 successive cycles. As it appears from Fig. 7a and 7b, the performance stability

Kinetics parameters of RSVNP-CLEAs

The kinetic parameters of phenol and p-cresol degradation by RSVNP-CLEAs were determined after obtaining profiles of the initial rate evolution as a function of substrate concentration. It has been shown that in both cases, the kinetic typically follows the Michaelis-Menten model. The Mechaelis-Menten kinetics constant (K m )

and the maximal velocity (V max ) were determined using a Lineweaver-Burk double reciprocal plot. It was found that the K m values for phenol 125.99 mg.L -1 and p-cresol 115.60 mg.L -1 were almost at the same order of magnitude. As for V max , a value of 2.30 mg.L -1 .min -1 was found for phenol and 13.70 mg.L -1 .min -1 for p-cresol, respectively (table 2).

J o u r n a l P r e -p r o o f

Morphology of RSVNP-CLEAs

The analysis of shape, size and morphology of CLEAs could be an interesting way to explore the factors influencing the formation of enzyme molecules aggregates, therefore, it allows in some way to predict their impact on the catalytic activity.

Controlling these parameters would pave the way for the transformation of CLEAs from a laboratory phenomenon into a mature catalytic process [START_REF] Schoevaart | Preparation, Optimization, and Structures, of Cross-Linked Enzyme Aggregates (CLEAs)[END_REF].

Images of RSVNP-CLEAs before and after using in successive batch treatment of the target compound are portrayed in Fig. 8. Before use, the cross-linked peroxidase shows an amorphous structure with a clean surface and many cavities. At the end of the fourth batch, a decrease in phenol conversion rate by RSVNP-CLEAs was observed; this could be explained by the partial inhibition of CLEAs caused by products deposition of the catalytic transformation on their surface. The picture after use confirmed this suggestion by revealing the presence of small particles on the surface of CLEAs; their morphology also differed to that of RSVNP-CLEAs.

Conclusion

The efficacy of immobilized RSVNP-CLEAs in the form of cross-linked enzyme aggregates was investigated for the biodegradation of phenolic compounds. The immobilization step consisted in the preparation and optimization of a robust biocatalyst with efficient catalytic performances, as well as great chemical and thermal stability compared to the free enzyme. The cross-linked enzyme showed J o u r n a l P r e -p r o o f interesting characteristics, retaining 100% of its activity after 60 days of storage and significant operational stability in hydrophobic solvents. RSNVP-CLEAs showed promising capacity for dephenolization under mild conditions. According to the results, a total conversion of p-cresol was obtained after 40 min of treatment in the presence of hydrogen peroxide as co-substrate. Phenol was also eliminated by more than 71% after 3 consecutive batches. Given the ability of RSNVP-CLEAs to transform more than one phenolic compound, it might be a possible alternative to conventional biological treatment methods. To confirm these results, a large-scale study on similar compounds and then on industrial effluents would be useful.

  J o u r n a l P r e -p r o o f et al. 2017). The effluents generated by the petrochemical industry are characterized by a strong concentration of toxic organic products, as well as oil and grease (Abd El-Gawad 2014; Bahri et al. 2018). Indeed, this industry uses a large volume of water for cooling systems and refining of crude oil; thus causing, a continuous discharge of pollutant-laden wastewater (Bustillo-Lecompte et al., 2018; Tian et al., 2019). Generally, wastewater from petrochemical refineries contains sulfides, hydrocarbons, phenols, oils and greases (Abdelwahab et al., 2009; Altaş and Büyükgüngör, 2008; Dat and Chang, 2017). The US Environmental Protection Agency (EPA), Agency for toxic Substances and Disease Registry (ATSDR) and the National Institute for Occupational Safety and Health (NIOSH) consider phenols as priority pollutants and dangerous for health or life at a concentration of 250 mg.L - 1 (Tandjaoui et al. 2019). Due to their solubility, phenolic compounds are widely

  First, cross-linking and the characterization of the resulting CLEAs of RSVNP, as a new source of plant peroxidase. On the other hand, the capacity of RSVNP-CLEAs to degrade phenols under specified conditions. First step was to implement an aggregation protocol by testing different precipitant agents. Previous studies have shown the importance in the choice of the precipitation solvent which plays an important role in the preservation of enzyme activity (Šekuljica et al., 2016; Sheldon, 2011). For this J o u r n a l P r e -p r o o fpurpose, five organic solvents (acetone, acetonitrile, methanol, ethanol and 2propanol) were tested as precipitant using 1:3 (v/v) ratio of enzyme solution/precipitant. After proteins precipitation, the formed aggregates were crosslinked with glutaraldehyde and the results are shown in Fig.1a.The low recovered activity of RSVNP-CLEAs was observed in the case of different solvents (acetonitrile, ethanol, methanol and 2-propanol) used as precipitants, displaying a value not exceeding 10%. However, acetone showed better results yielding 20% of the initial activity recovery and 83% of aggregation yield. Loss of activity is probably due to highly denaturating effect of solvents. Hence, considering the retention of the initial activity, which was two times higher compared to the solvents selected for enzyme precipitation, acetone was adopted for further experiments. Similar results were found (Bilal et al., 2017b; Šekuljica et al., 2016) in the synthesis of HRP-CLEAs by opting for acetone as a precipitant of choice. The impact of the precipitation solvent varies from one enzyme to another and can affect the catalytic activity of the biocatalyst by denaturing the protein(Schoevaart et al., 2004). Therefore, the choice of a precipitating agent strongly depends on the tertiary structure and the properties of the protein and this is also valid for the same type of enzyme extracted from different sources (Talekar et al., 2013), which explains the different ways to prepare cross-linked enzymes.Another parameter that can influence the preparation of CLEAs is the initial enzyme concentration. Thus, different dilutions of RSVNP mother solution were introduced and mixed with the cross-linking agent (GA:E, v/v) (1:3, 1:6, 1:9 and 1:12) using acetone for physical aggregation of proteins,which were subsequently cross-linked by J o u r n a l P r e -p r o o f glutaraldehyde at 2% concentration. Recovered activity and aggregation yield of the resulting CLEAs are illustrated in Fig.1b. The results revealed that the activity recovery increases up to 29 % for 1:9 (GA:E, v/v) ratio, while it was decreasing for higher values. This concentration was therefore chosen for the rest of the experiments.The second step in the preparation of RSVNP-CLEAs is the cross-linking of the precipitated proteins with GA. The concentration of GA can be defined by the number of aldehyde groups present in the solution. Increasing the concentration leads to a large number of free aldehyde groups that react with the amine groups of the enzyme. Accordingly, it is important to quantify the amount of cross-linker required to successfully form CLEAs with tunable catalytic performance. In addition, an excess or a deficit in glutaraldehyde can influence the enzyme activity, stability, and particle size of the resulting CLEAs (Sheldon, 2011). Low cost, commercial availability, gentle toxicity and ease of manipulation made glutaraldehyde the ultimate choice for CLEAs preparation[START_REF] Talekar | Parameters in Preparation and Characterization of Cross Linked Enzyme Aggregates[END_REF]. The influence of GA concentration on the activity recovery and aggregation yield of RSVNP-CLEAs is depicted in Fig.1c. At less than 2% glutaraldehyde concentrations, a considerable amount of the enzyme was not cross-linked and lost in the supernatant or during the washing operation. The increase in the cross-linker quantity, at a rate of 0.5%, resulted in the formation of a noticeable load of CLEAs. At an optimal level of 2% GA, 29% of peroxidase activity was retained due to the presence of a large number of cross-linking agent molecules.

  forms of the enzyme. Previously, (Bashir et al., 2018) reported similar findings with crosslinked alkaline protease from Bacillus licheniformis compared to the free enzyme. Loss of activity under extreme pH values could be explained by a change in the charges of the active site as well as the entire surface of the enzyme and leads to an alteration in the stereochemistry of the enzyme (Verma et al., 2019). Enzyme aggregation plays a protective role against such phenomenon.

J

  o u r n a l P r e -p r o o f catalytic activity is attributed to a progressive denaturation of the protein, while the cross-linked enzyme would be protected by the presence of the strong covalent bonds (Bilal et al., 2016; Verma et al., 2019).

  biocatalyst can affect the enzymatic activity in organic solvents[START_REF] Sangeetha | Preparation and Characterization of Cross-Linked Enzyme Aggregates (CLEA) of Subtilisin for Controlled Release Applications[END_REF][START_REF] Xia | Immobilization of Horseradish Peroxidase Enzymes on Hydrous-Titanium and Its Application for Phenol Removal[END_REF]. The effect of organic solvents on immobilized enzyme is illustrated in Fig.2c. Considering the activity of CLEAs in the buffer solution pH 7±0.2 as a maximum value (100%), it was found that the RSVNP-CLEAs retained 68 and 63% of their initial activity after 72 hours of incubation in hexadecane and silicone oil, respectively; while RSVNP-CLEAs retained only 38, 33, 29 and 19% of their catalytic activity in methanol, acetone, chloroform and DMSO.The drop in activity is due to the competition between the enzyme and the solvent to react with the essential water layer which is on the surface of the enzyme because polar solvents tend to peel off the water layer surrounding the enzyme by establishing bonds with the water molecules[START_REF] Dordick | Enzymatic Catalysis in Monophasic Organic Solvents[END_REF][START_REF] Fathali | Catalytic Phenol Removal Using Entrapped Cross-Linked Laccase Aggregates[END_REF]. These data indicate that cross-linking reduces the deformation of the protein structure by strengthening the rigidity of the enzyme molecules. The same conclusions were reported by[START_REF] Sangeetha | Preparation and Characterization of Cross-Linked Enzyme Aggregates (CLEA) of Subtilisin for Controlled Release Applications[END_REF].

  5 mM in the reaction medium. The residual concentration of phenol and p-cresol over time is shown in Fig. 3a and Fig. 3b respectively. It is obvious that an increase in compound concentration led to a decrease degradation capacity due to saturation of active sites of CLEAs. Consequently the reaction kinetic became zero order for high concentrations (Tandjaoui et al., 2019). Another observation, which can be drawn from this experiences that RSVNP-CLEAs show probably more affinity for p-cresol than for phenol. For example, for an initial concentration of 100 mg.L -1 only 18% of phenol was removed within 20 min. In contrary, 63% of p-cresol degradation was obtained in 10 min of reaction time. The same deduction were made in another study, which investigate the oxidation of various phenolic compounds by Luffa aegyptiaca J o u r n a l P r e -p r o o f peroxidase (Yadav et al., 2017). A distinction can be made from Fig. 3a and Fig. 3b

  hydrogen peroxide. A change in the oxidative state of the enzyme occurs and leads to a generation of intermediate radicals after reaction with the aromatic compound to form insoluble polymers and consequently a reduction of medium toxicity[START_REF] Veitch | Horseradish Peroxidase: A Modern View of a Classic Enzyme[END_REF]. The effect of hydrogen peroxide dose variation (0.1-20 mM) on initial degradation rate and biodegradation efficiency of phenolic compounds by RSVNP-CLEAs was explored and responses are shown in Fig.4a 4b, 4c and 4d. For this study, the H 2 O 2 concentration was varied for each initial concentration of phenol and p-cresol (only data for 100 mg.L -1 , 120 mg.L -1 , 140mg.L -1 and 160 mg.L -1 are shown) by introducing the co-substrate discontinuously in four aliquots at 10 min intervals to reach the desired amount. The reaction time was extended by two times i.e., 40 min

J

  o u r n a l P r e -p r o o f exerted by H 2 O 2 on the active site of peroxidase (Bilal et al., 2016). The same phenomenon was described in researches focusing on phenol biodegradation by horseradish peroxidase (Alemzadeh and Nejati, 2009; Xia et al., 2016). It was also found that the crescent addition of the oxidant improved the catalytic performances by increasing the degradation yield to 25% for phenol and 70% for p-cresol (100 mg.L -1 ) with 0.5 mM of H 2 O 2 . It seems that hydrogen peroxide was an impacting parameter for biodegradation process. Effectively, a control in co-substrate delivery while adjusting it according to the reaction rate plays an important role in oxidation procedure (Velde et al., 2001).

  . After 1 hour of reaction time; the enzymatic transformation of phenol was recorded showing a value of 92% and a yield of 78% of TOC eliminated. Additionally, 98% of the pcresol was treated after 40 min with elimination of more than 76% of TOC. In an earlier study, immobilized polyphenol oxidase was evaluated for the degradation of pcresol and almost complete degradation was achieved after 30 hours of transformation with the enzyme entrapped in sodium alginate-polyvinyl alcohol-silver nanoparticles matrix showing an activity of 208 Units/2g beads (Edalli et al., 2016).

J

  o u r n a l P r e -p r o o f of RSNVP-CLEAs was revealed and this without any washing operation before their reuse, achieving more than 71% degradation of phenol after 3 successive batches against more than 54% elimination of p-cresol operating on 4 repeated uses. Beyond the third cycle, the decline in phenol conversion was presumably due to the polymer generated from enzymatic transformation on the CLEAs surface leading to lower activity. The use of CLEAs in stirred batch systems presents some drawbacks. In particular, a risk of damage to the cross-linked structure due to agitation and consequently a loss of enzyme (Šekuljica et al., 2016). In addition, a break in the prepared form causes exposure of the enzyme to the substrate and it has been reported that this phenomenon leads to an inhibition of enzyme activity(Bilal et al., 2017b). Finally, to overcome these disadvantages, a use of CLEAs in packed-bed reactor is strongly recommended to avoid CLEAs destructuring by passing the solution to be treated through the layer of the fixed bed.

FigFig 3 .Fig 4 .Fig 5 .Fig 6 .Fig 8 .

 34568 Fig 1.E glutara

Table 1 .

 1 Characteristics of the solvents used for CLEAs stability test (

	Tables

Darracq et al., 2010; Fathali et al., 2019; Hahn et al., 1993; Sangeetha and Emilia Abraham, 2008; Tandjaoui et al., 2019).

	Solvent Water Hexadecane Silicone oil (V20) Methanol Acetone Chloroform J o u r n a l P r e -p r o o f Dielectric constant ε Log P 80.2 1 2.01 8.5 2.6 4.25 32.7 -0.74 21 -0.1 4.8 2.3
	DMSO	47	-1.3

Table 2 .

 2 Kinetic constants of Mechaelis-Menten model for phenol and p-cresol degradation.

	Substrate	K m (mg.L -1 )	V max (mg.L -1 .min -1 )	R 2
	Phenol	125.99	2.30	0.97
	p-cresol	115.60	13.70	0.97

Acknowledgements:

The authors are grateful to the Algerian-French program PROFAS B+ for its financial support in this collaborative project.

Conflict of interest:

We declare that we have no conflict of interest.

Ethical statement:

We declare that there are no ethical issues form human or animal rights in the work presented here.


domain: phys sdu

text:
M G Rachid

S Pilling

W R M Rocha

A Agnihotri

H Rothard

P Boduch

Processing of 72 K water-rich ices by keV and MeV oxygen ions: Implications for the Saturnian moon Enceladus

Keywords: astrochemistry, methods:laboratory:molecular, methods:laboratory:solid state, techniques: spectroscopic

The processing of H 2 O:CO 2 :CH 4 (10:1:1) and H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) ices at 72 K by oxygen ions was studied in attempt to simulate the physicochemical effects induced by energetic ions on Enceladus surface (or similar cold surfaces in the outer Solar System). The experiments were carried out at GANIL ( Grand Accélérateur National d'ions Lourds ) in Caen/France. The samples were irradiated with 15.7 MeV O 5+ at the IRRSUD beamline and with 108 keV O 6+ at the ARIBE beamline. The frozen samples were monitored by FTIR Spectroscopy (4000 -650 cm -1 , 2.5 -15.4 μm, at 1 cm -1 resolution). The identified molecular species formed during irradiation were: CO, OCN -, CH 3 OH, HCN, CN -,H 2 CO 3 , HNCO, HCO and CO 3 . The effective formation cross sections for the synthesis of new species and the effective molecular destruction cross sections of the parent species in the experiments with MeV ions were found to be of the order of 10 -14 -10 -13 cm 2 . For the keV ions experiments these values were of the order of 10 -16 -10 -15 cm 2 . The fluence at which the sample reaches chemical equilibrium and the molecular abundances in this region (Equilibrium branching ratios) were estimated. These experiments suggest that the chemical inventory on Enceladus surface can be influenced by the incidence of charged particles onto the moon's surface.

Introduction

The Saturnian moons have been pointed out as potential places to support extra-terrestrial life and to host prebiotic molecules [START_REF] Kazeminejad | The Cassini/Huygens mission to Saturn and Titan and its relevance to exo/astrobiology[END_REF], Parkinson et al. 2008[START_REF] Raulin | Astrobiology and Habitability of Titan[END_REF], McKay et al. 2014). Among these moons, Enceladus is one of the most promising targets because it harbors a salty and warm subsurface ocean (Postberg et al. 2009, Thomas et al. 2016). Material from this ocean vents through four fissures, known as tiger stripes, in the south pole of Enceladus from approximately 100 geysers spreading volatiles, organic molecules, salts, and ice grains into space (Postberg et al. 2009, Teolis et al. 2010, Porco et al. 2014). The material erupting from the tiger stripes are the Enceladus plumes, and data from the Cassini mission have revealed that they contain a rich molecular inventory (Brown et al. 2006, Matson et al. 2007[START_REF] Waite | [END_REF], that includes macromolecular organics with molecular masses above 200 u (Postberg et al. 2018a).

The Enceladus surface and plumes were extensively investigated during flybys of the Cassini spacecraft using a variety of instruments onboard it. The Cassini's Near Infrared Mass Spectrometer (NIMS) revealed that Enceladus surface is mainly composed of water ice with smaller quantities of volatile species, such as CO 2 , NH 3 , and tholins (Brown et al. 2006, Hendrix et al. 2010, Combe et al.2019). The moon's surface temperature was mapped using the CIRS instrument (Composite Infrared Spectrometer) and showed a temperature gradient varying from 35 K in the north pole up to 72 K in the equatorial region. Temperatures as high as 170 K were also measured close to the tiger stripes (Spencer et al. 2006).

The surface of Enceladus is recovered by infalling material from the plumes (Southworth et al. 2019) and it is constantly bombarded with ions and electrons from the magnetosphere of Saturn as well as X-rays and UV photons from the Sun. This bombardment can lead to ejection of molecules from the icy surface and the grains floating around Enceladus (sputtering and photo-desorption). Also, this bombardment can trigger the formation of new chemical species on the Enceladus surface and on the icy grains expelled from the plumes.

In this work, we analyzed the effects of medium-mass (e.g. oxygen) ion bombardment in H 2 O :CO 2 :CH 4 (10:1:1) and H 2 O :CO 2 :CH 4 :NH 3 (10:1:1:1) ices at 72 K, conditions similar to that Enceladus' surface (Spencer et al. 2006). The choice of medium mass ions relies on the fact that the saturnian inner magnetosphere is mainly populated by water-derived atoms and molecular ions, the so-called water group ions, as O + , OH + , H 2 O + , H 3 O + (Sittler et al. 2005, Young et al. 2005), with kinetic energies peaking at hundreds of keV. The ion irradiation employed oxygen ions of different energies: 108 keV O 6+ and 15.7 MeV O 5+ . A work involving the processing of similar ice samples by keV electrons was performed by Bergantini et al. (2014a). Interestingly, the authors reported that some species not yet detected on Enceladus, for example OCN -and HCONH 2 , can be formed in conditions similar to those found at the moons' north pole. Since charged particles are also important ionizing agents impinging on Enceladus (and other icy moons), radiolysis experiments can be used along with data from the Cassini spacecraft for a better understanding the chemical complexity of Enceladus and other icy-moons of the outer Solar System.

Experimental Methodology

The experiments were performed at the " Grand Accélérateur National d'Ions Lourds " (GANIL) in Caen-France. The irradiation with 108 keV O 6+ ions were performed at the low energy facility ARIBE ( A ccélérateurs pour les Recherches avec les Ions de Basses Energies ), and the experiments with the 15.7 MeV O 5+ ions at the IRRSUD ( IRRadiation SUD ) beamline. The CASIMIR chamber ( Chambre d'Analyse par Spectroscopie Infrarouge des Molécules IRradiées ) was coupled to the different beamlines. The set-up, shown in Fig. 1, consists of a stainless steel chamber at high vacuum (base pressure ~2 × 10 -7 mbar); a cryostat system that is thermally connected to the sample holder; a CsI substrate where the ices are grown; a pre-chamber for mixing the gases and vapor molecules; and an inlet where the gas mixtures are admitted into the chamber.

The sample-cryostat system can be rotated up to 180°and fixed at three different positions that allow i) the front deposition of gas mixtures onto the substrate; ii) the FTIR measurements in the transmission mode; and iii) the sample irradiation. The gas mixtures were prepared by mixing volumes of gases (or vapors) in the desired ratio. The mixtures were admitted into the chamber through a needle valve and deposited onto the CsI substrate at 12 K. The samples were then heated up to 72 K at a rate of 3 K min -1 and kept at this temperature during the irradiation. In-situ Fourier-transformed infrared spectra were taken before irradiation and at different fluences with a Nicolet FTIR spectrometer (Magna 550) from 4000 cm -1 to 650 cm -1 with 1 cm -1 resolution. More details of the experimental setup can be found elsewhere (Duarte et al. 2009, Pilling et al. 2010a, 2010b, Lv et al. 2012). The samples were irradiated up to a maximum fluence of about 10 14 ions cm -2 , for the experiments with MeV ions, and 10 16 ions cm -2 for the experiments with keV ions. Table 1 shows the maximum projectile fluences that the ices were exposed during the irradiations.

The molecular column density of the species in the ice is related to the optical depth (τ ν ) and the vibrational mode band strength (A) by (d'Hendecourt and Allamandola 1986):

[molecules cm -2 ] dν dν N = 1 A ∫ τ ν = A 2,3 ∫ Abs ν (1)
where τ ν = ln(I 0 /I) , where I 0 and I are the intensity of light at a given frequency before and after passing through a sample, respectively, A is the vibrational mode band strength (in cm molecule -1 ) and Abs ν is the absorbance measured by the FTIR at a wavenumber ( Abs ν = ln (I 0 /I) / ln(10) = τ ν ν /2.3 ). The initial and final column density of all parent molecules were calculated using Equation 1. In these calculations, we estimated the initial column density as the sum of the initial column density of the parent species (H 2 O, CO 2 , CH 4 and NH 3 ). The total column density of the samples are shown in Table 1.

Knowing the molecular column density of all the species in the samples before and after irradiation, it is possible to estimate the ice thickness using the following equation, from Pilling et al. (2011):

× 10 d = N 6.02 × 10 23 ρ M 4 [ μ m] ( 2
)
where N is the column density, in units of molecules cm -2 , M is the molar mass in units of g mol -1 , and ρ is the density in units of g cm -3 for the considered species. In Table 1 the thickness of the ice samples is estimated as the sum of the individual components of the sample. The density of each component was assumed to be the same as for pure ices (Brunetto et al. 2008, Satorre et al. 2008): ~1.0 g cm -3 for H 2 O, 1.8 g cm -3 for CO 2 , 0.44 g cm -3 for CH 4 and 0.8 g cm -3 for NH 3 . The stopping power and the penetration depth of the incoming ions in samples with compositions similar to the ones studied here were calculated using the software SRIM [START_REF] Ziegler | Srim-the stopping and range of ions in matter[END_REF]. The stopping power (deposited energy) plotted as a function of the penetration depth of the projectiles is shown in Figure 2. From panel a (Figure 2) it is possible to see that the energy loss of the MeV ions inside the sample happens mainly by electronic interactions (inelastic interactions) with the atoms of the target material. For the keV ions, the energy loss is both by interaction with electrons and nucleus (elastic interactions) of the target material. These two ways of energy transfer can result in different induced chemistry within the ice samples. Using the stopping power calculated by SRIM it is possible to calculate the way in which energy was transferred to the target material.

The maximum penetration depth of the oxygen ions is around 25 µm for the 15.7 MeV oxygen ions and around 0.7 µm for the 108 keV oxygen ions. Considering the initial sample thickness (listed in Table 1), the MeV ions cross the entire length of the sample, processing the surface as well as the ice bulk. In contrast, the 100 keV ions are implanted in the sample, processing just a portion of the ices. This also implies a relatively smaller yield of molecular fragments from radiolysis by the latter when compared to MeV projectiles. The effects of the implantation of oxygen projectiles in the ices (i.e. the contribution of this atom in the chemical synthesis of new species) were not analyzed in this work since we cannot distinguish between implanted oxygen projectiles and the oxygen atoms from the H 2 O and CO 2 molecules originally in the sample.

Results

The IR spectra of the non-irradiated and irradiated samples (at maximum fluence) for all the experiments are shown in Figures 3,4, 5 and 6. In the irradiated spectra (black full lines in the figures), new infrared features, associated with new molecular species, are presented. Some bands from parent and daughter species are indicated in the figures. All the spectra were baseline corrected using a spline fit tool available in the software, Origin, and offset for better visualization. The infrared bands used to quantify the column density of the parent species (using Equation ( 1)) as well as the corresponding A-values are listed in Table 2. The bands used to identify and quantify the daughter species, as well as their assignment, are summarized in Table 3. From Table 3, it is possible to note that MeV ions induce the synthesis of more species than the keV ions. The daughter species HCN, CN -HCO, HNCO, and CO 3 are produced only in the samples irradiated by MeV ions. This may be related to the fact that these ions ionize even the inner shells of light target atoms, such as C,N, and O, which completely destroys the molecules and thus produces free radicals. This opens reaction pathways that do not appear for the lower energy projectiles.

Molecular cross-section

From the evolution of column density as a function of fluence, it is possible to calculate the effective dissociation and formation cross-sections of the parent and daughter species, respectively, following the equation (adapted from Pilling et al. 2010aPilling et al. , 2010b)):

[molecules cm -2 ] N F N (F ) -N 0 = inf 1 ( -exp -F ( σ d,f ) ) -Y (3)
where F is the ion fluence, in units of cm -2 ; N(F) is the column density of the molecular species at fluence F; N 0 i s the column density of such species in the non-irradiated sample; σ is the effective destruction cross section ( σ d ) or the effective formation cross section ( σ f ), all in cm 2 ; Y is the sputtering yield, in molecules per ion (see also Vasconcelos et al. 2017aVasconcelos et al. , 2017b)); and N inf is a constant, in units of cm -2 . Most of the parent species were modeled considering Y = 0. This approach was preferred because some species are formed in the bulk of the ice, being less affected by a surface process like sputtering. The species for which Equation 3 was better adjusted by including the sputtering term are indicated in Table 4. For a more formal and detailed discussion about the variation of sputtering with the ice thickness, we refer the reader to Dartois et al. 2018.

The values for effective destruction and formation cross-sections for parent and daughter species, respectively, are shown in Table 4. Figure 7 shows the measured column density of the parent and daughter species as a function of the ion fluence along with the fit of Equation 3. The cross-sections obtained for the MeV ions experiments are in the range 10 -13 -10 -14 cm 2 , the same order of magnitude as those reported for previous experiments on ion irradiation of pure or mixed ices performed by our group with similar instrumentation (e.g. Vasconcelos et al. 2017a;2017b;2017c;Pilling et al. 2010a;2010b). The cross-sections for the experiments with keV ions are of the order of 10 -15 cm 2 and 10 -16 cm 2 . These values are about two orders of magnitude smaller than the effective cross-sections obtained for MeV ions, also in agreement with values from irradiation experiments with ions of similar energy ( Gomis et al. 2005). A point worth stressing is that the term "effective" means that these values depend on the chemical environment of the icy samples. *Since the band assigned to v3 mode of CO 2 could be saturated, the band chosen to monitor the column density of CO 2 in the experiment with ammonia irradiated with 108 keV ions was the combination mode v1 + v3, around 3700 cm -1 . **Daughter species adjusted with the sputtering term (Equation 3)

Destruction of the parent species

The percentage of each parent species destroyed after irradiation (D%) can be quantified by the equation: [%] (4)

D% 00 = 1 * N o N o-N f
where No and Nf indicate the column density of a given parent species before irradiation and after irradiation (at maximum fluence), respectively. The calculated values are listed in Table 5. As can be seen from Table 5, the MeV projectiles destroy more parent molecules than 108 keV projectiles, being methane and ammonia the more depleted species. Moreover, it seems that in the presence of NH 3 , the depletion of CH 4 is higher. This could be due to the reaction of species produced from methane radiolysis with NH 3 (or also with species produced from ammonia radiolysis), but further investigation would be necessary to reach any conclusion.

Chemical Equilibrium and Equilibrium Branching Ratio (EBR%)

At low irradiation fluences we observe that the molecular column densities decrease for parent species and increase for daughter species. At high fluences, the molecular column density reaches a plateau (and at even higher fluences, the sputtering becomes predominant and N(F) decays linearly in time). For irradiation experiments with ions, when the regime at which the column densities decrease linearly with fluence is reached, the net formation or destruction of molecular species no longer occurs, but only the depletion due to sputtering. So, we refer here to "chemical equilibrium" as the regime where the variation in column density of a species is only due to the sputtering process (see also Bonfim et al. 2017, Vasconcelos et al. 2017b, 2017c). At the fluence at which the sample reaches the chemical equilibrium, the "final" composition of a sample under irradiation can be determined. The criteria and procedure for determining the point at which the sample is in equilibrium is described in the Appendix B.

Table 7 shows the equilibrium fluence F E , calculated using the methods described in Appendix B, the energy fluence at this point (E E ) and electronic local dose ,D e (i.e. the energy projectile energy that is transferred to the electrons of the target material). The electronic local dose D e , in units of eV molecule -1 is calculated with the equation:

(

) 5
where φ is the ion flux, in units of ions cm -2 s -1 ; t is the irradiation time (or exposure time) in seconds; S e is the integrated electronic stopping power considering penetration up to a depth where the projectile ion has stopped completely (see Figure 2), in units of keV; M is the initial average molecular mass of the sample in g per mol: ρ is the average sample density in g cm -3 ; N A is Avogadro's Number; and S e is the energy transferred to the sample during electronic interaction between the projectile and the atomic targets. The average density of the samples was estimated by considering the weighted average of each parent species, assuming their densities for pure ice.

The values of energy deposited per molecule, or electronic local dose, to reach the chemical equilibrium (D e ) are higher for the experiments with 108 keV ions (144 and 63 eV molecule -1 ) than the values for the experiments with swift ions (170 and 144 eV molecule -1 ). This result shows that, for samples irradiated with MeV ions, less energy is needed to reach the equilibrium when compared to 108 keV ion bombardment. To explain this difference, one must consider the way in which each projectile loses energy when interacting with target atoms. The slower 108 keV oxygen ions lose more than half of their energy in nuclear interactions with the atoms of the bombarded material (see Figure 2 panel b), while 15.7 MeV oxygen ions interact almost mainly electronically with the target atoms (Figure 2 panel a). The nuclear interaction of the ions with target nuclei can result in collisions that displace atoms of the target molecules within the sample, resulting in the dissociation of the formed molecules. However, the reason why the samples irradiated with MeV ions require a smaller input of energy is still not understood.

From the values in Table 6, it is possible to notice that samples containing NH 3 show lower values of equilibrium fluence than the experiments without NH 3 . This could indicate that the daughter species that originate from ammonia may be more stable. Knowing the equilibrium fluence, the percentage abundances of the molecular species in equilibrium, the "Equilibrium Branching Ratio" (EBR%), can be calculated by: (6) where N i indicates the column density of a species at the equilibrium fluence. In this equation, the sum takes into account all parent and daughter species at this fluence, including species present in the ice that can not be detected using the IR spectroscopy (called here "unknown species"). Such unknown species include molecules with abundances below the detection limit of the spectrometer, molecules with IR bands being highly convoluted with other bands and molecules that are not detectable in the infrared but may be present in the ice. The procedure for estimating the column density of these species is described in Appendix A. The EBR for the produced species are Table 7: Equilibrium Branching Ratio (EBR%), in percentage, for the parent species and identified new produced species in all the experiments. The values were calculated using Equation ( 6). Estimated values for unidentified species were also given (see details in the text).

Molecule

Experiment with MeV ions

Experiments with 108 keV ions The EBR% of daughter species are larger in samples bombarded with MeV ions when compared with the same species in the samples bombarded with keV ions. In the case of CO, the EBR % are 1.0% and 1.6%, in experiments #SI-1 and #SI-2, respectively, in contrast with 0.5% and 0.2% in experiments #LI-1 and #LI-2, respectively. For the OCN -, the EBR% value is roughly 10 times higher for MeV ion irradiation when compared to the keV irradiated ices, being the values 0.4% and 0.03% for the #SI-2 and #LI-2, respectively.

#SI-1 #SI-2 a #LI-1 #LI-
In the case of Methanol (CH 3 OH), as can be seen in table 7, the presence of NH 3 in the ice can influence the reaction pathways for this species during radiolysis. Indeed, the corresponding EBR% value is only half of that observed without the presence of NH 3 for MeV ion irradiation. The effect is even more pronounced in the case of 108 keV ions: in this case, EBR%=0. Interestingly, however, the presence of ammonia seems to enhance the production of unknown species during ion bombardment. This might suggest that a large fraction of the unknown species may contain nitrogen atoms. A future investigation will help to clarify this issue.

The EBR% of CO 3 are virtually the same in the two projectile energy regimes. This indicates that ammonia does not play a significant role in the reaction pathways for this species, although it seems to have some influence in the production of CO and CH 3 OH, and HCO.

Implications on Enceladus chemistry scenario

The analyzed samples are case studies and could represent aspects of physicochemical processes induced by the bombardment of icy surfaces in space with energetic ions (cosmic rays, magnetospheric particles, solar wind or solar energetic particles). Examples are frozen moons around giant planets, KBOs (Kuiper Belt Objects) and TNOs (Transneptunian Objects), comets, protoplanetary ices and other frozen surfaces in evolved planetary systems, as well as dust grains in molecular clouds. In this section, we focus on the astrophysical implications of this work for one particular example, the Saturnian moon Enceladus.

The ice particles and gas in Enceladus plumes were already proven to contain many organic species (see Postberg et al. 2018b for a review about the Enceladus plume and surface composition). These particles, arising from Enceladus interior, are constantly falling onto the moon's surface and feeding the Saturnian E-ring, making the composition of the frozen material more complex. In addition, the solid material is continuously affected by ionizing radiation that forms and destroys species and changes the physical properties of the frozen material. It follows that the species produced by the charged particles analyzed here are just a fraction of the chemical processes that take place on the solid bodies in Enceladus. Most of the species can be sequentially destroyed by other types of radiation (e.g. incoming UV and X-rays photons, electrons and other charged particles in Saturn's magnetosphere), so the abundances obtained by this work can just be linked to the Enceladus environment in combination with other laboratory experiments and the data taken in the different Cassini's flybys.

In all the irradiated ices, CO is amongst the most produced species (not considering species that are included in the "unknown species"). The CO abundance (EBR(%)) is between 1.0 -1.6 % in all the irradiated ices (see Table 7). These values are higher than the upper limit of 0.2% estimated for CO in the Enceladus plumes (Postberg et al. 2018b). The higher abundances of CO in the irradiated ices when compared with Cassini data can be due to the fact that CO 2 , the parent species of CO, present in a final abundance of 4.8 -6.5 % in our experiments, is present in the Enceladus plumes in smaller ratios, between 0.3 -0.8% (Postberg et al. 2018b) . The subsequent photoprocessing and radiolysis of CO, induced by other energetic agents, may also be responsible for the lower abundances of this species in Enceladus plumes.

The planetesimals that formed Enceladus may have brought some species detected in plumes during the CASSINI flybys. This may be the case for HCN, that is present in Enceladus plume at maximum abundance of 0.2%. In the presence of warm water, HCN is quickly hydrolyzed to HCOOH and NH 3 (Miyakawa et al. 2002), indicating that this species does not arise from Enceladus' interior. This molecule may have been brought to Enceladus within primordial material [START_REF] Waite | [END_REF] or it may have formed in-situ at Enceladus' surface. In the NH3 containing samples irradiated with MeV ions, HCN is formed, and it is present in a quantity of 1% in the chemical equilibrium. Curiously, the irradiation of water-rich ices of similar composition by 1 keV electrons (Bergantini et al. 2014a), 5 keV electrons and VUV/soft X-rays photons (Pilling et al. 2019), this species was not detected. This indicates that, if HCN is formed in-situ in Enceladus, charged particles may play a crucial role in the synthesis of this species.

In the same way as HCN, HCNO was also produced in the NH 3 -containing ice irradiated by MeV ions but not in similar experiments involving the irradiation by electrons and VUV and X-rays photons. This species has mass 43 a.u., but it has not been assigned in the mass spectra taken by INMS. However, the assignment of carbon-bearing species in this region presents some ambiguities, and better assignments would require higher-resolution mass spectra (P ostberg et al. 2018b).

In all irradiations of NH 3 containing samples discussed here, the cyanate ions (OCN -) were detected after radiolysis. This species was also detected in the irradiation of ices with similar composition and temperature by 1 keV electrons (Bergantini et al. 2014a), VUV and X-rays photons (Pilling et al. 2019). The OCN-is a common species present in the energetic processing of ammonia-containing samples in the presence of molecules such as CO 2 , CH 4 and H 2 O (Broekhuizen et al. 2004) We note that the efficiency of OCN -production by 1 keV electrons (roughly estimated by N OCN-/(N H2O + N CO 2 + N NH3 ) taken from Bergantini et al. 2014a), seems to be less than the observed in the ion irradiation experiments. The EBR of OCN-for the MeV ion experiments is however comparable to the EBR of the same species in VUV-soft X-rays irradiation of ices : 0.4 % for the MeV ion irradiation and 0.5% for the VUV-soft X-rays irradiation (Pilling et al., 2019). Besides being easily formed by the energetic processing of ices with composition similar to Enceladus moon, the cyanate ions were not detected by the Cassini measurements. Negatively charged molecules can be detected by the Cassini's Electron Spectrometer (ELS), part of the CAPS instrument. The species detected in the mass spectra taken in the Enceladus plumes are mainly associated with negatively charged water clusters (Coates et al. 2010) and high mass species, with no conclusive assignment so far. Coates cited that these negatively charged clusters have a short lifetime in the enceladus plume environments where collisions with neutrals, positive charged particles, and grains, are frequent. This can also be the case for other anionic species, so the presence of these negatively charged species in the plume environment is not expected. In-situ investigations of the Enceladus icy surface would reveal the presence of anionic species (such as OCN-) in regions where the ice is processed by energetic particles and photons, since negatively charged particles could have a longer life-time when embedded in the ice.

Another anionic species identified in our experiments, the CN-, was synthetized in detectable quantities only in the MeV irradiation experiment, what is expected, since the formation route of this molecule is probably linked to the formation of HCN (also detected only in the MeV ion experiment). However, this species was not detected in Enceladus. The reasons may involve difficulties in the detection of anionic species in the Enceladus environment, as cited before.

With the knowledge of the ion flux in a given cold space environment and with the determined EBR% and the sputtering yield Y, we can estimate the individual flux of molecular desorption from the surface ( , in units of molecules cm -2 s -1 from:

) ψ Ei,space [molecules cm -2 s -1 ] (8) ψ Ei,space = 100 EBR% i × Y × ϕ space
where the ion flux in space environment ( is in units of ions cm -2 s -1 . The sub-index E at ) ϕ space is to remind us that this quantity was determined under the scenario of chemical ψ Ei,space equilibrium in the sample. By summing the contribution of all desorbed species (including estimated unknown ones) after reaching chemical equilibrium we obtain the total desorption flux in space environment as ψ ( Ei,space)

[molecules cm -2 s -1 ] .

(

) Y ψ E,space = ∑ i=all ψ Ei,space = 100 EBR% i × × ϕ space 9
Especially for Enceladus, the effects of incident O-containing ions are of great importance since these species are the main component of Saturn's magnetosphere plasma at its orbit (Sittler et al. 2005, Young et al. 2005) . However, such a procedure might be applied to other cold Solar System surfaces in an attempt to elucidate the mechanisms that influence the formation of tiny atmospheres around these frozen surfaces. A future publication will handle this issue mode deeply, but a glimpse of preliminary calculations is given below.

Considering the sputtering yield of Y = 10 3 molecules ion -1 (for MeV ions ), the flux of oxygen ions (with energy ~10 MeV) of the order of 10 4 ions cm -2 s -1 (roughly estimated from Jurac (2001)) and the EBR% of water (~70%), we have estimated that the rate at which H 2 O molecules are sputtered from the icy surface is approximately 7 x 10 6 molecules cm -2 s -1 . This value is smaller than the rate of H 2 O in Enceladus, estimated by Johnson et al. (2008) as nearly 10 8 -10 9 molecules cm -2 s -1 . The value estimated by Johnson et al. takes into account the sputtering of water due to the magnetospheric ions of the water group (i.e. the sputtering due to the incidence of protons and other magnetospheric ions are not accounted for). Additionally, if we consider an icy body with the dimension of Enceladus (surface area ~8 x 10 15 cm 2 ), the average rate of H 2 O ejection by oxygen would be roughly 6 x 10 22 H 2 O s -1 . For a matter of comparison, this value is orders of magnitude lower than the amount of H 2 O ejected by the plumes at the south pole of Enceladus (~10 28 H 2 O s -1 ), and it is also lower than a secondary global contribution of H 2 O molecules ejected by Enceladus (~10 25 H 2 O s -1 ) detected by Cassini CIMS observations (Burger et al. 2007).

These comparisons would suggest that the water desorption induced processes at Enceladus' surface by the incoming MeV oxygen ions play a minor role in the production of gaseous species in the vicinity of this moon. Although the calculated desorption flux is smaller than observed, it is necessary to keep in mind that this estimative just takes into account the sputtering by oxygen ions with a specific energy. A more realistic comparison should be made considering a broader range of energies. Additionally, Enceladus' surface is constantly being refreshed by fluffy deposits from its plumes, which complicates even more the parameterization of gas-phase delivery induced by ion bombardment of the surface.

Conclusions

This work presents experimental results of the irradiation of H 2 O:CO 2 :CH 4 (10:1:1) and H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) ices at 72 K by 108 keV 16 O +5 ions and 15.7 MeV 16 O +6 ions. These experiments help to understand the chemical composition and chemical processes of ice surfaces of the outer Solar System (with focus on Enceladus) when exposed to bombardment by energetic particles. The physicochemical changes in the ices were monitored during the irradiation by infrared spectroscopy. The conclusions of the work are summarized below:

-The samples irradiated with MeV ions produced a more (detectable) diversity of daughter species, some of them not observed in the experiments using 108 keV ions. The species identified in the experiments with MeV ions are: CO, OCN, CO 3 , HCO, H 2 CO, H 2 CO 3 , CH 3 OH, HNCO, CN -, HCN and CN -; and the ones identified in the experiment with keV ions are: CO, OCN and CH 3 OH. In all the experiments, the CO is amongst the most abundant produced species (considering just the ones identified and quantified by IR spectroscopy). -The effective destruction cross-sections of the parent species and the effective formation cross-sections of the daughter species were calculated. The effective formation cross-section for the new species is within the 10 -15 -10 -16 cm 2 range for the experiments using 108 keV ions as projectiles and 10 -13 -10 -14 cm 2 for the experiments using 15.7 MeV ions.

-The ices irradiated with MeV ions presented higher depletions of NH 3 and CH 4 (destruction larger than 95%) when compared to the ice bombarded with keV ions. -The molecular abundances at chemical equilibrium (quantified by equilibrium branching ratios -EBR%) were quantified. These quantities are important because they give the abundances of the molecules present in the ice samples after long irradiation times (please, see details in the text). -An estimative of the abundance of the species that are not quantified by the infrared spectroscopy is presented (these species are referred to in this work as "unknown species"). The abundance of the unknown species (estimated in solid samples after the bombardment) was larger in the samples irradiated by MeV ions experiments, suggesting that these samples may be even more chemically complex. -The desorption of water molecules induced by the ion sputtering process was estimated and extrapolated to the Enceladus environment. The experimental data suggest that the ion desorption of water molecules by 15.7 MeV oxygen ions from the entire surface area of Enceladus would be around 7 x 10 22 H 2 O s -1 for MeV ions, a value that is order of magnitude smaller than the water ejected by Enceladus plumes.

The results found in this work help us to understand the effect of charged particles in cold astrophysical environments. The discussion about chemical equilibrium in solid phase in the presence of ionizing radiation after large fluences suggests that charged particles may largely modulate the chemistry in astrophysical environments, inducing similar composition in different lines of sights and locations in the galaxy, as well as in other cold space environments.

Figure 1 :

 1 Figure 1: Schematic picture of the experimental apparatus (CASIMIR chamber). The sample holder rotates to three different positions to permit the sample deposition, irradiation, and spectra acquisition (from Pilling et al. 2010a)

Figure 2 :

 2 Figure 2: Evolution of the stopping power (deposited energy) as a function of penetration depth of the incoming projectile ions in the samples. a) For experiments #SI-1 and #SI-2 with 16 O 5+ 15.7 MeV ions at the IRRSUD beamline. The inset shows the region close to the complete stopping (implantation) of 15.7 MeV ions in the sample. b) For experiments #LI-1 and #LI-2 with 108 keV ions at ARIBE beamline. The calculations were performed with the SRIM code (Ziegler et al. 2010).

Figure 3 :

 3 Figure 3: #SI-1 experiment. a) Infrared spectra of H 2 O:CO 2 :CH 4 (10:1:1) ice before irradiation (dashed line) and after irradiation with 16 O +5 15.7 MeV at a fluence of 3.0 × 10 14 ions cm -2 (full line); b) zoomed -in region around 2400 -1200 cm -1 .

Figure 4 :

 4 Figure 4: #SI-2 experiment. Infrared spectra of H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) ice before irradiation (dashed line) and after irradiation with 16 O +5 15.7 MeV at a fluence of 1.0 × 10 14 ions cm -2 (full line); b) zoomed -in region around 2400 -1200 cm -1 .

Figure 5 :

 5 Figure 5: #LI-1 experiment. a) Infrared spectra of H 2 O:CO 2 :CH 4 (10:1:1) ice before irradiation (dashed line) and after irradiation with 16 O +6 108 keV at a fluence of 1.3 × 10 16 ions cm -2 (full line); b) zoomed -in region around 2400 -1200 cm -1 .

Figure 6 :

 6 Figure 6: #LI-2 experiment. a) Infrared spectra of H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) ice before irradiation (dashed line) and after irradiation with 16 O +6 108 keV at a fluence of 1.2 ×10 16 ions cm -2 (full line); b) zoomed -in region around 2400 -1200 cm -1 .

Figure 7 -

 7 Figure 7 -Column density of selected species as a function of fluence for experiments a) #SI-1; b) #LI-1; c) #SI-2, d)#li-2. Lines are the best fits obtained with equation 3. As discussed in Appendices A and B, "Unk" indicates the column density of the species that are not identified by IR spectroscopy. See details in the text.

Table 1 :

 1 Summary of the experiments -Experiment label, sample composition, projectile employed in the irradiation, maximum fluence (F max ), sum of the column density of the molecules in the non-irradiated ice (N 0 ) and after maximum fluence (N f ), initial thickness (d 0 ), and final thickness (d f ). All the ice samples were irradiated at 72 K.

Sample parameters Exp. Label Sample Projectile F max (ions cm -2 ) N 0 (molec cm -2 ) d 0 (µm) N f (molec cm -2 ) d f (µm) #SI-1 #SI-2 a

		H 2 O:CO 2 :CH 4	15.7 MeV 16 O 5+	3.0 × 10 14	7.5 × 10 18	2.25	6.3 × 10 18	1.96
		(10:1:1)	(IRRSUD BEAMLINE)
		H 2 O:CO 2 :CH 4 :NH 3	15.7 MeV 16 O 5+	1.0 × 10 14	4.5 × 10 18	1.53	3.0 × 10 18	0.94
		(10:1:1:1)	(IRRSUD BEAMLINE)
	#LI-1	H 2 O:CO 2 :CH 4	108 keV 16 O 6+	1.3 × 10 16	7.8 × 10 18	3.02	7.2 × 10 18	2.25
		(10:1:1)	(ARIBE BEAMLINE)
		H 2 O:CO 2 :CH 4 :NH 3	108 keV 16 O 6+	1.2 × 10 16	9.3 × 10 18	3.34	7.9 × 10 18	2.72
	#LI-2 a	(10:1:1:1)	(ARIBE BEAMLINE)

a Samples with ammonia.

Table 2 :

 2 Bands in the IR spectra used to quantify the parent species in the icy samples.

H 2 O:CO 2 :CH 4 (10:1:1) ices Band position in exp. #SI-1 Band position in exp. #LI-1 Assignment (vib. Mode) A-value (cm molecule -1 ) Ref.

	794	784	H 2 O (libration) 2.6×10 -17	d'Hendecourt & Allamandola 1986
	2340	2341	CO 2 (v3)	7.3×10 -17	Gerakines et al. 1995
	1302	1301	CH 4 (v4)	6.1×10 -18	d'Hendecourt & Allamandola 1986
			H 2 O

:CO 2 :CH 4 :NH 3 (10:1:1:1) ices Band position in exp . #SI-2 Band position in exp. #LI-2 Assignment (vib. Mode) A-value (cm molecule -1 ) Ref.

  The v3 mode of CO 2 was saturated. The v3 mode of 13 CO 2 was used to quantify CO 2 in the sample

	795	781	H 2 O (libration) 2.6×10 -17	d'Hendecourt & Allamandola 1986
	2341	2280*	CO 2 (v3)	7.3×10 -17	Gerakines et al. 1995
	1302	1302	CH 4 (v4)	6.1×10 -18	d'Hendecourt & Allamandola 1986
	1119	1116	NH 3 (v3)	1.4×10 -17	Zanchet et al. 2013

*

Table 3 :

 3 Bands of daughter species in the IR spectra of H 2 O:CO 2 :CH 4 (10:1:1) and H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) ices irradiated with 16 O +6 108 keV and 16 O +5 15.7 MeV ions.

H 2 O:CO 2 :CH 4 (10:1:1)

ices Band position in exp. #SI-1 Band position in exp. #LI-1

	1488**	-	H 2 CO	-	Pilling et al. 2010b
	1855	-	HCO	2.1×10 -17	d'Hendecourt & Allamandola (1986)
	2045	-	CO 3	8.9×10 -18	Bennett et al. (2004)
	2137	2138	CO	1.1×10 -17	d'Hendecourt & Allamandola (1986)
	2154*	-	-	-	-
	2176*	-	-	-	-
	2265*	-	-	-	-
			H 2 O
			Assignment A-value	Ref.
				(cm
				molecule -1 )
	1017	1015	CH 3 OH	1.4×10 -17	d'Hendecourt & Allamandola (1986)
	1388*	-	-	-	-

:CO 2 :CH 4 :NH 3 (10:1:1:1) ices Band position in exp. #SI-2

		Band position	Assignment A-value	Ref.
		in exp. #LI-2
	1015	-	CH 3 OH	1.4×10 -17	d'Hendecourt & Allamandola (1986)
	1357*	-	-	-	-
	-	1374*	-	-	-
	1385*	-	-	-	-
	1484**	-	H 2 CO	-	Pilling et al. 2010b
	1855	-	HCO	2.1×10 -17	d'Hendecourt & Allamandola (1986)
	2045	-	CO 3	8.9×10 -18	Bennett et al. (2004)
	2089	-	CN -	1.8×10 -17	Moore et al. (1983), Augé (2016)
	2097	-	HCN	5.1×10 -18	Burgdorf et al. (2010), Augé (2016)
	2137	2137	CO	1.1×10 -18	d'Hendecourt & Allamandola (1986)
	2171	2171	OCN -	1.3×10 -16	Moore et al. (1983)
					van Broekhuizen et al. (2004)
	2263**	-	HNCO	-	Lowenthal et al. (2002)

*Features that were not assigned; **Tentative assignments

Table 4 :

 4 Effective destruction cross section (σ d ) of parent species and effective formation cross section (σ f ) of daughter species in the studied ices. The bands used to monitor the column density of each species are also shown. Estimated errors are around 20%.

	Parent species			σ d (10 -13 cm 2 )	σ d (10 -15 cm 2 )
	Molecule	ν (cm -1 )	#SI-1	#SI-2	#LI-1	# LI-2
	H 2 O	800	0.7 ± 0.6	1.9 ± 0.4	0.7 ± 0.1	1.0 ± 0.4
	CO 2	2342 a	1.0 ± 0.1	0.50 ± 0.03	2.5 ± 0.3	*
	CH 4	1301	0.9 ± 0.1	0.8 ± 0.1	1.6 ± 0.1	3.0 ± 0.2
	NH 3	1117	-	1.1 ± 0.1	-	1.6 ± 0.1
	Daughter species		σ f (10 -13 cm 2 )	σ f (10 -15 cm 2 )

Table 5 :

 5 Percentage of the destroyed parent species molecules (D%) in the four experiments, with and without ammonia during radiolysis up to the final projectile fluence. Projectile energy and maximum fluence are also indicated. , respectively. The projectile range is larger than the sample thicknesses so that the incoming ions pass through the sample, depositing only a fraction of their kinetic energy.

	Molecules	H 2 O:CO #LI-1	#SI-1	#LI-2	#SI-2
	H 2 O	9.3 %	9.5 %	7.4 %	12.5 %
	CO 2	5.5 %	20.1 %	20.9 %	53.9 %
	CH 4	24.5 %	77.0%	37.1 %	95.4 %
	NH 3	-	-	21.2 %	97.1 %
	Maximum ion Fluence	1.3 ×10 16	3.0 × 10 14	1.2 × 10 16	1.0 × 10 14
	(ion cm -2 )
	Maximum Energy Fluence	1.4 × 10 21	4.7 × 10 17a	1.4 × 10 21	1.0 × 10 17a
	Delivered
	(eV cm -2 )

2 :CH 4 (10:1:1) H 2 O:CO 2 :CH 4 :NH 3 (10:1:1:1) a Considering the energy delivered of ~1570 eV and ~1070 as illustrated in Fig 2 for experiments #SI-1 and #SI-1

Table 6 :

 6 Equilibrium fluence (F E ), energy fluence at chemical equilibrium (E E ) and electronic local dose (De E ) at chemical equilibrium for all experiments

	Experiment	Eq. fluence (F E ) (ions•cm -2 )	Energy fluence at equilibrium E E (eV•cm -2 )	Electronic local dose at Equilibrium De E (eV•molecule -1 )
	#SI-1	1.8 × 10 14	2.8× 10 21	144
	#SI-2 a	1.3× 10 14	2.0× 10 21	63
	#LI-1	8.1× 10 15	8.7× 10 20	170
	#LI-2 a	7.0× 10 15	7.6× 10 20	140
	a Samples with ammonia.

Acknowledgements

The authors acknowledge the Brazilian agencies FAPESP (Projects #2016/11334-5, #2017/07283-9, #2016/22018-7 and #2013/07657-5) and CNPq (Projects # 304130/2012-5 and #306145/2015-4) for financial support. We also thank the staff of CIMAP and GANIL for technical support. The experiments were performed at GANIL.

Appendix A: Column density of the "unknown species"

In this section, the procedure for estimating the mass and column density of the species that are not quantified by the IR technique is described. More details about this methodology are described in Vasconcelos et al. (2017c).

The column mass of a molecular species in the ice sample is given by:

[Da cm -2 ], (A.1) where N (F) is the column density of the species, in units of molecule cm -2 , at fluence F , and is its molecular mass, in units of Da molecule -1 . The column density of a species that is M M sputtered from the ice surface, as a function of fluence, can be estimated as N (F) = Y x F, in which Y is the sputtering yield in units of molecules per incoming ion . Substituting this expression in Equation (A.1), the column mass of a desorbed species (i) is given by:

The column mass of the species that are desorbed from the ice can be quantified using Equation (A.2) and the column mass of the species that are quantified by IR can be calculated using Equation (A.1). However, due to intrinsic limitations of IR spectroscopy, part of the molecules that remain in the ice cannot be identified and/or quantified. An estimate of the column mass of these species (that we call here "unknown species") can be done based on the conservation of mass: during the sample irradiation, the mass of the molecules on the solid sample plus the mass of the sputtered molecules should be constant, and equal to the initial mass of the sample. Taking this mass conservation and Equations A.1 and A.2 into account, the colum mass of the unknown species as a fluence of fluence is given by:

where is the column mass of the parent species in the initial sample (i.e., (F

)

is the sum of the column masses of all the species in the ice (F ) ∑ M j sample at a given fluence F (this species are the ones quantified through the IR spectrum) and M DES is the column mass of desorbed species at a fluence F , calculated using Equation (A.2).

(F ) Fig. A.1 shows the evolution of calculated column mass of the unknown species as a function of fluence. Displayed in the panels are: the column mass of the species in the ice that are quantified by IR spectroscopy (M observed ), the unknown species (M un ), calculated using Equation A.3, the desorbed species (M des ), calculated using Equation A.2, and the sum of all these column mass (M sum ). The values for the sputtering yield Y were initially estimate from Famá et al. (2008) and Rothard et al. (2017) and then "fine-tuned" to make the slope of the M un curve at high fluences similar to the slope of the M observed curve at high fluences. This "fine-tuned" is made based on the assumption that the desorption rate of the unknown species is equal to the desorption rate of the observed species (in mass). After this procedure, the estimated values for sputtering yields Y in our experiments with MeV ions are 1000 and 1200 molecules ion -1 for the experiments #SI-1 and #SI-2, respectively. At lower projectile energy, Y was found to be 30 and 40 molecules ion -1 , for the experiments #LI-1 and #LI-2, respectively.

Considering the column mass of the non-observed species at a given fluence, M un (F), and adopting a molar mass for these species, which we approximated to be equal to the average molar mass of the parent species in the initial sample ( ), the column density of the unknown species produced during the ion bombardment (N un ) can be estimated by: #SI-2; c) #LI-1; d) #LI-2. Displayed in the panels are: i) the column density of the species that remain in the ice sample added to the mass of the species desorbed by sputtering, called M sum (constant), in pink; ii) the sum of the column mass of the species quantified by IR spectroscopy, M observed , in black; iii) the column mass of the species that are not quantified by IR spectroscopy but remain in the solid phase ,M unknown (calculated using Equation A.3), in blue; and iv) the column mass of the species that are sputtered from the ice, M des (calculated using Equation A.2), in red. When M observed and M unknown reach a linear decrease with fluence, the chemical equilibrium has been reached. The sputtering yield used in Equation A.2 is indicated near the top axis. Further details are described in the text.

Appendix B: Chemical equilibrium fluence

For estimating the fluence at which the sample reaches the equilibrium, the derivative of the function N(F) is calculated. We considered that the sample reaches the equilibrium when dN/dF ≤ 10 -5 molecules per eV. This value is adopted because at this production/destruction rate, a variation of 10 17 cm -2 in the column density of a molecular species i in the sample (ΔN i ) happens after fluences on the order of 10 17 ions cm -2 for keV ions irradiation and 10 16 for MeV ions irradiation (considering that ∆N ≤ 10 -5 ∆F ). To obtain smaller changes in the column density of a given species (smaller ΔN i ), at these small production/destruction rates, longer irradiation fluences would be necessary. At these conditions, we consider that the sample is in equilibrium. Figure 8 illustrates the derivatives of N(F) for the parents and daughter species (including the unknown species) in the different experiments as well as the fluence at which the sample reaches the equilibrium.