Eléna Keuleyan
email: elena.keuleyan@inrae.fr

Aline Bonifacie
email: aline.bonifacie@inrae.fr

Philipp Gatellie
email: philippe.gatellier@inrae.fr

Claude Ferreira
email: claude.ferreira@inrae.fr

Sylvie Blinet
email: sylvie.blinet@inrae.fr

Aurélie Promeyrat
email: aurelie.promeyrat@ifip.asso.fr

Gilles Nassy
email: gilles.nassy@ifip.asso.fr

Véronique Santé-Lhoutellier
email: veronique.sante-lhoutellier@inrae.fr

Laëtitia Théron
email: laetitia.theron@inrae.fr

Juana Fernández-López

Design of an In Vitro Model to Screen the Chemical Reactivity Induced by Polyphenols and Vitamins during Digestion: An Application to Processed Meat

Keywords: N-nitrosation, lipid oxidation, processed meats, nitrite, differential spectrophotometry, emulsion, nitroso-compounds, polyphenols, vitamins, reformulation

Processed meats' nutritional quality may be enhanced by bioactive vegetable molecules, by preventing the synthesis of nitrosamines from N-nitrosation, and harmful aldehydes from lipid oxidation, through their reformulation. Both reactions occur during digestion. The precise effect of these molecules during processed meats' digestion must be deepened to wisely select the most efficient vegetable compounds. The aim of this study was to design an in vitro experimental method, allowing to foresee polyphenols and vitamins' effects on the chemical reactivity linked to processed meats' digestion. The method measured the modulation of end products formation (specific nitroso-tryptophan and thiobarbituric acid reactive substances (TBARS)), by differential UV-visible spectrophotometry, according to the presence or not of phenolic compounds (chlorogenic acid, rutin, naringin, naringenin) or vitamins (ascorbic acid and trolox). The reactional medium was supported by an oil in water emulsion mimicking the physico-chemical environment of the gastric compartment. The model was optimized to uphold the reactions in a stable and simplified model featuring processed meat composition. Rutin, chlorogenic acid, naringin, and naringenin significantly inhibited lipid oxidation. N-nitrosation was inhibited by the presence of lipids and ascorbate. This methodology paves the way for an accurate selection of molecules within the framework of processed meat products reformulation.

Introduction

Processed meat is a highly consumed meat product, and provides with very digestible proteins, oxidizable lipids, iron, and optional additives such as sodium nitrite. Yet, the latter is at the origin of consumers' concerns as it is involved in several chemical reactions jeopardizing the nutritional quality of processed meats. The digestive tract displays an enhancing environment for those reactions, which may lead toward negative health patterns.

Particularly, N-nitrosation is the reaction between secondary amines (stemming from proteolysis) and nitrosonium ions (from sodium nitrite) leading to nitrosamines. Some of them have been identified as carcinogenic and the rest possibly for human health by the International Agency for Research on Cancer (2015) [START_REF] Iarc | IARC Monographs evaluate consumption of red meat and processed meat[END_REF]. Yet, the main exposure to nitrosamines seems to correspond to an endogenous formation of the substances in the digestive tract [START_REF] Gushgari | Critical review of major sources of human exposure to N-nitrosamines[END_REF]. By another hand, processed meat lipids undergo the oxidative chain reaction [START_REF] Papuc | Mechanisms of Oxidative Processes in Meat and Toxicity Induced by Postprandial Degradation Products: A Review[END_REF], which is also enhanced in the gastrointestinal tract and boosts the formation of aldehydes in the gastric compartment [START_REF] Nieva-Echevarria | Food lipid oxidation under gastrointestinal digestion conditions: A review[END_REF], some of which are cytotoxic and genotoxic [START_REF] Esterbauer | Cytotoxicity and genotoxicity of lipid-oxidation products[END_REF][START_REF] Negre-Salvayre | Pathological aspects of lipid peroxidation[END_REF]. Both of those reactions concern processed meats for their composition and formulations.

Nonetheless, increasingly more vegetable extracts aimed to be used in the meat industry emerge on the market and are used to supplement processed meats [START_REF] Kumar | Recent Trends in the Use of Natural Antioxidants for Meat and Meat Products[END_REF] in order to newly formulate those products. This trend is part of global movement whereby food products are reformulated with less processed ingredients, less food additives, and more naturalness [START_REF] Kumar | Recent Trends in the Use of Natural Antioxidants for Meat and Meat Products[END_REF][START_REF] Dias | Nutritional Quality and Health Benefits of Vegetables: A Review[END_REF]. Indeed, there is ample evidence that vegetable food products (such as tea, coffee, vegetables, or fruit juices), which are rich in active compounds, namely phytonutriceuticals (fibers, vitamins, minerals, and micronutrients such as polyphenols or carotenoids), have many benefits on health [START_REF] Bartsch | Inhibitors of endogenous nitrosation mechanisms and implications in human cancer prevention[END_REF][START_REF] Pierre | Calcium and alpha-tocopherol suppress cured-meat promotion of chemically induced colon carcinogenesis in rats and reduce associated biomarkers in human volunteers[END_REF][START_REF] Kanner | Redox homeostasis in stomach medium by foods: The Postprandial Oxidative Stress Index (POSI) for balancing nutrition and human health[END_REF][START_REF] Quedebeaux | Horticulture and Human Health: Contributions of Fruits and Vegetables[END_REF][START_REF] Craig | Phytochemicals: Health Protective Effects[END_REF][START_REF] Wargovitch | Anticancer Properties of Fruits and Vegetables[END_REF].

Molecules such as polyphenols or vitamins seem to alleviate negative impacts [START_REF] Donaldson | Nutrition and cancer: A review of the evidence for an anti-cancer diet[END_REF][START_REF] Halliwell | The Gastrointestinal Tract: A Major Site of Antioxidant Action?[END_REF][START_REF] Kerem | Protection of Lipids from Oxidation by Epicatechin, trans-Resveratrol, and Gallic and Caffeic Acids in Intestinal Model Systems[END_REF] as scavengers of free radicals [START_REF] Barbieri | Processed Meat and Polyphenols: Opportunities, Advantages, and Difficulties[END_REF] or reactive nitrogen species [START_REF] Lee | The reaction of flavanols with nitrous acid protects against N-nitrosamine formation and leads to the formation of nitroso derivatives which inhibit cancer cell growth[END_REF], and as potential inhibitors of carcinogenic substances formation in the stomach (notably flavanols against N-nitrosodimethylamine) [START_REF] Lee | The reaction of flavanols with nitrous acid protects against N-nitrosamine formation and leads to the formation of nitroso derivatives which inhibit cancer cell growth[END_REF]. The place of natural substances, such as polyphenols or vitamins in food products, is therefore gaining prominence and the understanding of those molecules' roles in reformulated processed meats is thus paramount to enhance their nutritional quality [START_REF] Donaldson | Nutrition and cancer: A review of the evidence for an anti-cancer diet[END_REF][START_REF] Weir | Diet and cancer risk reduction: The role of diet-microbiota interactions and microbial metabolites[END_REF].

Yet, too few data concerning the precise characterization of phytonutriceuticals' chemical reactivity in processed meats are available for the manufacturers. There is a real need to deepen the mechanisms allowing vegetable molecules to modulate the detrimental health effects associated with their consumption. The mitigation of those negative impacts can be studied through the action of polyphenols and vitamins on two principal reactions involving the added sodium nitrite, being N-nitrosation and lipid oxidation, both mainly occurring in the digestive tract, and supposed to be spearhead of health issues after processed meat consumption. The catalysis of those reactions during digestion may be explained by the pro-oxidant environment of the gastrointestinal tract (low gastric pH, high oxygen pressure, body temperature) and the liberation of N-nitrosation and lipid oxidation, i.e., the most involved compounds (secondary amines and fatty acids, respectively) [START_REF] Nieva-Echevarria | Food lipid oxidation under gastrointestinal digestion conditions: A review[END_REF][START_REF] Hrudey | Drinking water as a proportion of total human exposure to volatile N-nitrosamines[END_REF]. The need to screen the potential modulation of N-nitrosation and lipid oxidation induced by vegetable molecules during processed meats digestion in a model is therefore a challenge to tackle. Some in vitro models have been designed to study the impacts of vegetable molecules on the chemical reactivity of those reactions' end products. Several papers studied the mechanisms involving polyphenols and vitamins on N-nitrosation [START_REF] Abraham | Ascorbic acid and dietary polyphenol combinations protect against genotoxic damage induced in mice by endogenous nitrosation[END_REF][START_REF] Ischia | Secondary targets of nitrite-derived reactive nitrogen species: Nitrosation/nitration pathways, antioxidant defense mechanisms and toxicological implications[END_REF][START_REF] Hirota | Reactions of Apple Fruit Polyphenols with Nitrite under Conditions of the Gastric Lumen: Generation of Nitric Oxide and Formation of Nitroso Catechins[END_REF][START_REF] Takahama | Possible Reactions of Dietary Phenolic Compounds with Salivary Nitrite and Thiocyanate in the Stomach[END_REF], but without a digestive environment, nor in relation with a particular product matrix. N-nitrosation in the oral cavity has been studied by working on models of acidified saliva [START_REF] Hirota | Reactions of Apple Fruit Polyphenols with Nitrite under Conditions of the Gastric Lumen: Generation of Nitric Oxide and Formation of Nitroso Catechins[END_REF][START_REF] Takahama | Possible Reactions of Dietary Phenolic Compounds with Salivary Nitrite and Thiocyanate in the Stomach[END_REF][START_REF] Peri | Apples increase nitric oxide production by human saliva at the acidic pH of the stomach: A new biological function for polyphenols with a catechol group? Free Radic[END_REF][START_REF] Rao | Drug-Nitrite Interactions in Human Saliva: Effects of Food Constituents on Carcinogenic N-Nitrosamine Formation[END_REF]. Yet, focusing on the gastric compartment environment would be of major interest as it seems to promote N-nitrosation and lipid oxidation [START_REF] Halliwell | The Gastrointestinal Tract: A Major Site of Antioxidant Action?[END_REF][START_REF] Kanner | The Stomach as a Bioreactor: Dietary Lipid Peroxidation in the Gastric Fluid and the Effects of Plant-Derived Antioxidants[END_REF][START_REF] Kenmogne-Domguia | Lipid Oxidation in Food Emulsions under Gastrointestinal-Simulated Conditions: The Key Role of Endogenous Tocopherols and Initiator[END_REF].

Indeed, in vitro digestive models have been designed to study lipid oxidation [START_REF] Kenmogne-Domguia | Lipid Oxidation in Food Emulsions under Gastrointestinal-Simulated Conditions: The Key Role of Endogenous Tocopherols and Initiator[END_REF] and its inhibition by polyphenols [START_REF] Boléa | Lipid protection by polyphenol-rich apple matrices is modulated by pH and pepsin in in vitro gastric digestion[END_REF][START_REF] Lorrain | Dietary iron-initiated lipid oxidation and its inhibition by polyphenols in gastric conditions[END_REF]. The core of their model was an oil in water emulsion, characterizing the composition and the chemical state of lipids in the tract [START_REF] Armand | Characterization of emulsions and lipolysis of dietary lipids in the human stomach[END_REF]. Lipids present in the emulsion not only allow to represent the complexity of a food bolus content, but also to model the chemical reactivity of N-nitrosation and lipid oxidation in an emulsified complex system. Nevertheless, to focus on a product of interest in a model is of major importance considering the current strategy of processed meats reformulation with plant molecules [START_REF] Kumar | Recent Trends in the Use of Natural Antioxidants for Meat and Meat Products[END_REF][START_REF] Fraqueza | Microbiological hazards associated with salt and nitrite reduction in cured meat products: Control strategies based on antimicrobial effect of natural ingredients and protective microbiota[END_REF]. Hence, to the current knowledge, the specific study of different chemical reactions of processed meats leading to a possible digestive toxicity using in vitro models is scarce.

The aim of this paper was therefore to develop a method allowing to screen several polyphenols and vitamins for their specific action during digestion in a model depicting processed meat products. To reach that goal, the method must be rapidly efficient, reliable, and reproducible, which is a greater stake when working with emulsions. The stability of the emulsionized in vitro model will constitute one step of the present study. Then, an estimation of the reactivity of polyphenols and vitamins on those two key chemical reactions is expected in a processed meat model.

Two vitamins and four polyphenols were selected for the study. Ascorbic acid (vitamin C) and trolox (hydrosoluble form of vitamin E) were used as highly reactive and used vitamins in processed meats formulations. Then, four molecules of polyphenols of different classes were chosen, in order to potentially observe an impact of the molecule's structure on the modulation of the chemical reactivity (chlorogenic acid for phenolic acids, rutin for flavonoids, and naringin and naringenin for an aglycone and a glycone form of polyphenol from the flavanones). As highly used in processed meats formulations, the combined effect of the selected plant molecules with ascorbic acid will be evaluated. Working with an emulsified medium may also affect the chemical reactivity of the molecules [START_REF] Combet | Dietary phenolic acids and ascorbic acid: Influence on acid-catalyzed nitrosative chemistry in the presence and absence of lipids[END_REF], which is why the modulation will also be assessed in two different medium: a simple aqueous medium and a complex emulsified one. Studying the combined effect of the vegetable molecules of interest with ascorbic acid and the impact of the model medium would therefore provide deeper insight on the modulation of N-nitrosation and lipid oxidation in a digestive environment of processed meat.

Materials and Methods

All the reagents, i.e., acetone, L-α-phosphatidylcholine (CAS: 8002-43-5; ≥50%), citric acid, sodium hydrogen phosphate, sodium nitrite (CAS: 7632-00-0; ≥99%), (+)-sodium L-ascorbate (CAS: 134-03-2; ≥98%), iron (II) sulfate heptahydrate (CAS: 7782-63-0; ≥99%), ethanol, N-acetyl-DL-tryptophan (CAS: 87-32-1; ≥98%), chlorogenic acid (CAS: 327-97-9; ≥95%), rutin hydrate (CAS: 207671-50-9; ≥94%), naringenin (CAS: 67604-48-2; ≥95%), (±)-naringin (CAS: 10236-47-2; ≥95%) and Trolox ((±)-6-Hydroxy-2,5,7,8-tetramethylchromane-2-carobxylic acid) (CAS: 53188-071) were purchased from Sigma-Aldrich (Saint Louis, MI, USA). Filter papers (Ref: 074121; Dim: 70 mm) were from Dutscher (Brumath, France). Sunflower oil (11 g of saturated fatty acids/100 g of oil) was from a local market (Auchan), and its amount of α-tocopherol was titrated by high-pressure liquid chromatography (HPLC) to 75.60 mg/100 g.

Oil in Water Emulsion

Emulsion fabrication process. The oil in water ultrasonic emulsion was stabilized with egg yolk phospholipids (L-α-phosphatidylcholine). Two proportions of lipids were tested: either a 5% or a 10% oil in water emulsion (stabilized with 0.4% or 0.8% of lecithins, respectively) (Figure 1). The aqueous phase was an acidic buffer solution (20 mM citric acid, 40 mM sodium hydrogen phosphate) adjusted to the pH of study, e.g., 2 or 3.5. The lipidic phase was made of crude sunflower oil. Emulsions were prepared in several steps (Figure 1). After adding the phospholipids in the buffer, a first homogenization was performed using a rotor-stator (Polytron PT 2500 E; Kinematica AG, Malters, Switzerland) at 18,000 rpm for 2 min at room temperature, in order to correctly scatter phospholipids aggregates in the buffer. Then, 2 or 4 g of sunflower oil was added in the solution. A second homogenization using the same parameters was performed on the solution before the emulsion sonication. The latter was conducted on melted ice with a Vibra Cell (VC-300; Thermo Fischer Scientific, Illkirch, France) sonicator, to prevent heating by sonication, for seven minutes: five cycles of 60 s active phase and 30 s off, at 300 W of power. The emulsion was directly put under stirring (200 rpm) in a preheated chamber (NB-205L; N-Biotek, Gyeonggi-Do, Korea) at 37 • C for 25 min after its fabrication. Emulsion granulometry analyses. Once sonicated, the emulsion was directly characterized with a flow particle image analyzer (FPIA) (FPIA-3000; Sysmex, Kobe, Japan) in triplicate as a quality control. The analysis methodology was described by Promeyrat et al. in 2010 [START_REF] Promeyrat | Evaluation of protein aggregation in cooked meat[END_REF]. The sample analysis was preceded by two tests. The first was an auto-focus calibration with a commercial solution of latex spheres of 3.2 µm of diameter (Latex Microsphere Suspensions; Duke Scientific Corporation, Fremont, CA, USA), and 100 µL of the latter solution diluted in pure water (1/7; v/v) was injected for the analysis. The second was an automated background check review, counting the remaining particles in the FPIA. It was repeated until at the most 30 particles were present in the unit. The high-power field (HPF) selection mode was elected, allowing to analyze particles ranging between 1 and 40 µm of diameter with a 20-times magnification. Each measurement was automatically diluted in an electrolytic sheath buffer (7.1 g/L NaCl, 0.8 g/L surfactant, 2.0 g/L Tris, 0.2 g/L EDTA). Then, 100 µL of diluted sample in buffer (1/50; v/v) was injected in the chamber for its characterization.

Three criterions were selected for the characterization. First, the size of the particles was examined with the perimeter equivalent diameter (PED), in µm. Then, the shape was assessed with the circularity index, in percentage. Third, the density was measured and provided with the percentage of analyzed particles belonging to the set-up standards. The latest corresponded to the acceptable range for lipid droplets in an ultrasonic emulsion, meaning a PED lower than 10 µm [START_REF] Strassner | Effect of pH on Interfacial Films and Stability of Crude Oil-Water Emulsions[END_REF] and a circularity belonging to the interval 90-100% [START_REF] Raschke | Rapid monitoring of cell size, vitality and lipid droplet development in the oleaginous yeast Waltomyces lipofer[END_REF].

Screening Model

Screening model experimental design description. The methodology designed to assess the action of polyphenols and vitamins on N-nitrosation and lipid oxidation is based on differential UV-visible spectrophotometry. For each pure molecule, four systems were created. The two firsts, A and B, were supported by reactions in the presence of the vegetable molecule; while C and D did not contain any of them. B and D were the respective blank for A and C against the polyphenol or vitamin. Different reagents were then introduced in the emulsion according to the reaction intended (Figure 2). The end products of N-nitrosation and lipid oxidation reactions were measured after 15 min of incubation in the steam room. A quantification of N-acetyl-nitroso-tryptophan and aldehydes was then obtained for each one of the four systems. Yet, the values resulting from B and D measurements corresponded to the spectral noise. Therefore, the amount of nitrosamines and aldehydes in the presence of polyphenol or vitamin, or not, was given by the subtraction of the different concentrations in each system, by considering the residual turbidity of the sample (Figure 2). The methodology was used to assess three chemical reactivities: (1) the effect of polyphenols and vitamins in an emulsified model; (2) the combined effect of polyphenols and vitamins with ascorbic acid in an emulsified model, to explore a potential interaction with the compounds and ascorbic acid; and (3) the effect of polyphenols and vitamins in a simple aqueous buffer (without lipids), to explore the effect of lipids presence on the chemical reactivity.

Screening in vitro model composition. A cooked meat model was chosen as the referenced processed meat matrix, for its highly studied chemistry and known composition [START_REF] Bonifacie | Chemical reactivity of nitrite and ascorbate in a cured and cooked meat model implication in nitrosation, nitrosylation and oxidation[END_REF]. The main compounds involved in the reactions and their concentrations in those products were identified to design a comprehensive model of phytonutriceuticals' chemical reactivity screening. Sodium nitrite is usually introduced up to 120 ppm with 300 ppm of ascorbate in France [START_REF]IFIP. Code des Usages de la Charcuterie, de la Salaison et des Conserves de Viande[END_REF]. Nitrosamines' synthesis depends notably on the presence of free iron [START_REF] De La Pomelie | Mechanisms and kinetics of tryptophan N-nitrosation in a gastro-intestinal model[END_REF] and is enhanced with acetyl-tryptophan [START_REF] Nakai | Significance of the reaction of nitrite with tryptophan[END_REF]. Their respective amounts were set according to previous work at 30 µM [38] and 3 mM [START_REF] De La Pomelie | Mechanisms and kinetics of tryptophan N-nitrosation in a gastro-intestinal model[END_REF].

The volume of each system was similar and fixed at 13 mL: 5 mL of reactive compounds was added to 8 mL of emulsion, accordingly to the system, as described in the Figure 2. NaNO 2 and FeSO 4 , at respective final concentrations of 1.74 mM and 30 µM, were systematically diluted in the buffer solution and introduced in every system. Then, according to the latter, different solutions were added. Acetyl-tryptophan (Ac-TRP) (3 mM) was prepared as stock solutions in pure ethanol, i.e., 120-fold stock, with 325 µL of this solution added in the system. N-acetyl-DL-tryptophan was selected according to Nakai et al. [START_REF] Nakai | Significance of the reaction of nitrite with tryptophan[END_REF] at 3 mM in order to target the exclusive generation of the N-nitroso-tryptophan nitrosamine in the system (and not several species such as nitroso and/or nitro-tryptophan).

Chlorogenic acid, rutin, naringin, naringenin, and trolox, at a final concentration of 1 mM [START_REF] Macheboeuf | Dose-response effects of essential oils on in vitro fermentation activity of the rumen microbial population[END_REF] and a volume of 325 µL, were prepared in either pure ethanol as well (system B), or in the ethanolic Ac-TRP solution (system A). When 325 µL of ethanolic solution (of either Ac-TRP or polyphenol/vitamin) was added, 675 µL of buffer was introduced to complete the requirement of 1 mL of addition. Ascorbate was solubilized in the buffer at 1 mM. All these solutions were aliquoted and stored at -80 • C.

Biochemical Assays

Nitroso-tryptophan assay. The specific absorbance of the nitrosamine bond was measured at 760 nm and 335 nm with a spectrometer (Jasco V770; Lisses, France), according to the method described by Nakai et al. in 1978 [41]. After 15 min of incubation, 500 µL of the sample was directly added to 2 mL of acetone and 150 µL of pure water for the nitroso-tryptophan concentration measurement. The solution was filtered after 2 min of vortex. The blank was composed of 2 mL of acetone and 650 µL of water. The absorption coefficient is 6100 M -1 cm -1 [START_REF] Keceli | Comparison of HNO reactivity with tryptophan and cysteine in small peptides[END_REF]. Nitroso-tryptophan concentrations are expressed in µM.

TBARS assay. Lipid oxidation was assessed thanks to the thiobarbituric acid reactive substances (TBARS) method, enabling the quantitative measuring of the aldehyde function of molecules. The major one stemming from the oxidation chain reaction is the toxic malondialdehyde (MDA) [START_REF] Folch | A Simple Method for the Isolation and Purification of Total Lipides from Animal Tissues[END_REF]. After the incubation of the system, 300 µL of sample was frozen at -80 • C for the TBARS assay. The sample was added to 150 µL of thrichloroacetic acid (TCA) and 150 µL of thiobarbituric acid (TBA). The mixture was boiled for 10 min. The samples were then extracted with 1.2 mL of butanol during 15 min of centrifugation (4000 rpm, 4 • C) (SL 40R centrifuge; Thermo Scientific; Waltham, MA, USA). Organic phase absorbance was measured at 535 nm and 760 nm by spectrophotometry (Jasco V770; Lisses, France). The blank was made of butanol. Results are expressed in µmol of MDA equivalent per mg of lipids.

Statistical Analysis

Figures are reported as mean ± standard deviation of 4 independent measurements, for each concentration of every systems studied (A, B, C and D). Variance analyses (ANOVA) were realized with the software Statistica (V13.5; Statsoft Inc. Tulsa, OK, USA), with a Tukey post-hoc test (significance assessed by p-values < 0.05). The variables considered for respective modulation of N-nitrosation and lipid oxidation were the concentration of nitroso-tryptophan and the amount of TBARS. For the modulation of N-nitrosation, the factors were the polyphenols or vitamins, the presence of ascorbate, and the presence of emulsion or not. Lipid oxidation measurements were analyzed with the vegetable molecule, as in system A.

Results and Discussion

Optimization of the Heterogeneous Reactional Medium

The impact of pH and oil amount was studied on the characterization profiles of the emulsions in order to select the best parameters for the emulsion's stability, and for the good relevance of the model. Two acidic pH were tested, 3.5 and 2, to symbolize the acidity of the beginning and mid digestion. Two percentages of oil amounts were investigated (5% and 10%) to assess the potential effect of lipids' proportions on the emulsion profile. These oil percentages represented the level of lipids that can be found in a Western diet. Sunflower oil was selected for its highly oxidizable fatty acids composition, allowing to correctly assess a modulation of lipid oxidation reaction by polyphenols and vitamins by differential spectrophotometry.

Figure 3A depicts the distribution of the particle's sizes in four different emulsions according to the cumulative frequencies, in percentage, as a function of the PED, in µm.

Emulsions have an overall droplets PED lower than 10 µm. The differences induced by the pH modulation on droplets' perimeters prevailed over the oil concentration ones. At pH 2, the heterogeneity of the reactional medium seemed to be reduced. For a given pH, no distinct difference between the emulsions was highlighted in relation to the oil amount. Indeed, at pH 2, almost 90% of lipid droplets (from both the 5% and 10% O/W emulsions) had a PED of 3.5 µm, when the size of 90% of the particles from pH 3.5 emulsions reached approximately a PED of 5.5 µm. The profiles given by the FPIA represent the PED of the particles (µm) as a function of their circularity, with an index of the counted particles represented by a blue colour scale (Figure 3B). The prominent modification observable on the profiles was the pH impact, where the increase in the latter from 2 to 3.5 induced mainly changes in the distribution of the droplets in terms of PED and density (Figure 3A,B). For the same amount of oil, lipid droplets density seemed to be reduced with the rise in the pH value, leading to the formation of bigger oil agglomerates in the emulsions. Hence, the pictures shot by the FPIA showed that the largest particles of the emulsions, which are the most likely ones to cause destabilization, are almost three times larger at pH 3.5 than at pH 2. This observation was also effective with 10% of oil, although a bit less pronounced. Nonetheless, the fusion of several droplets was concrete at pH 3.5 as pictures have been shot of the fusion of lipid particles. The rise in the oil percent had less impact on the characterization profiles, although the density seemed to be risen as well as the number of large particles eager to destabilize the emulsion. This was particularly true for the pH 3.5 with 10% O/W emulsion.

Nevertheless, as illustrated by the pictures shot, the equipment may not distinguish very well close particles and therefore count them as entities (Figure 3B). In order to overcome this bias and to exclude possible air bubbles, agglomerates, and sample noise [START_REF] Raschke | Rapid monitoring of cell size, vitality and lipid droplet development in the oleaginous yeast Waltomyces lipofer[END_REF], the interval of circularity and perimeter analysis was narrowed. Thus, it was possible to select exclusively the droplets most subjects to correspond to lipidic particles thanks to the shape (90-100% of circularity) and the size (maximum size range of 10 µm of PED [START_REF] Strassner | Effect of pH on Interfacial Films and Stability of Crude Oil-Water Emulsions[END_REF]) data, creating a window of study (blank background of the profile against the grey one). The software returned an approximate proportion of 80 to 85% of the enumerated particles belonging to this window.

The aim of this preliminary work was to set the correct parameters to optimize the emulsion. Indeed, as an emulsion is defined by its kinetics of destabilization [START_REF] Mcclements | Nanoemulsions versus microemulsions: Terminology, differences, and similarities[END_REF], reaching greater stability over time, a correct reproducibility of its internal structure, and avoiding destabilization processes, are major stakes of the present development. Yet, those phenomena are promoted by an uneven distribution of the droplets in terms of size and shape [START_REF] Goodarzi | A Comprehensive Review on Emulsions and Emulsion Stability in Chemical and Energy Industries[END_REF]. Therefore, the lower the pH, the thinner particles in the emulsion, thus leading to a pH buffer choice of 2. Working with smaller lipid droplets also allows to rise the exchange surface, which enhances the reactivity within the solution and therefore optimizes the sensitivity of the model. Furthermore, as the reproducibility of the model was paramount to ensure the following chemical reactivity screening, the amount of oil in water was set at 5% in order to minimize the part of large droplets potentially able to destabilize the emulsion. Once those parameters set, with a constant stirring of the emulsion in a preheated even at 37 • C ensuring the physico-chemical environment of a gastric digestion, the modulation of the chemical reactivity could be assessed based on processed meats chemistry.

Chemical Reactivity Modulation

Quite a few relevant compounds and an emulsified medium were used. The complexity created is thus the main asset of the model herein developed, as it could depict the most complex chemistry occurring during processed meats digestion.

The chemical reactivity modulated by polyphenols and vitamins on lipid oxidation and N-nitrosation has been assessed in different models by differential UV-visible spectrophotometry. Every modulation is given compared to the control model without pure vegetable molecule, thus meaning that it can predict the effect of the lone substance's presence in the design (Table 1).

Table 1. Polyphenols and vitamins modulation on lipid oxidation and N-nitrosation screening. The control consists in no antioxidant. Each result is given as mean ± SD of 4 independent measurements. Significate differences are given relatively to the control. (*: p-value < 0.05; ***: p-value < 0.001; NS: p-value > 0.05). There is a significative polyphenol modulation on lipid oxidation (p-value < 0.001) (Table 1). In the model without added ascorbate, chlorogenic acid, rutin, naringenin, and naringin significantly decreased lipid oxidation. This decrease was more pronounced for chlorogenic acid and rutin (about 88% fall) than for the flavanones (naringenin and naringin) (around 50% decrease). The same tendency with the same values was observed in the model with ascorbate, except for naringin. In contrast, for both models with and without ascorbate, vitamins had no effect on lipid oxidation. Hence, no effect attributed to the addition of 1 mM ascorbate with the other pure vegetable molecules (at 1 mM as well) was observed on lipid oxidation in the present design. Indeed, the rate of MDA equivalent was tantamount with or without the added ascorbate (Table 1A).

Lipid

The assessment of lipid oxidation in a modelized gastric compartment is paramount as it was demonstrated to be a bioreactor enhancing this reaction [START_REF] Kanner | The Stomach as a Bioreactor: Dietary Lipid Peroxidation in the Gastric Fluid and the Effects of Plant-Derived Antioxidants[END_REF]. The significant decrease in lipid oxidation induced by the previously cited molecules is consistent with the known chemical reactivity of these molecules. Chlorogenic acid, rutin, naringenin, and naringin display different structures as they come from different classes of phenolics (namely phenolic acids, flavonols, and flavanones, respectively), thus meaning that a a comprehensive overview of the representatives molecules' chemical reactivity could eventually be obtained [START_REF] Nieva-Echevarria | Food lipid oxidation under gastrointestinal digestion conditions: A review[END_REF]. The modulation of lipid oxidation observed therefore upholds the good functionality of the present developed experimental design. The absence of ascorbate effect on lipid oxidation may be surprising, but this result has to be taken in the overall context of the model, with its complexity arising from the emulsified medium and, therefore, the differences in compounds' solubilities, the concentrations of the different reagents, and the physico-chemical environment implemented.

Concerning N-nitrosation, the addition of rutin promoted the reaction in both emulsified models with and without added ascorbate, up to 36% and 50%, respectively. The same result was observed in the aqueous model (approximate increase of 36%). Whatever the model studied, no pure polyphenols nor vitamins could be discriminated as enhancers or inhibitors. This fact may arise from the lack of sensibility of the spectrophotometric method against the measured nitroso molecules. Working by differential spectrophotometry is a strength to complexify the model but, in the present case of less than 10% of synthetized nitroso-tryptophan (the maximum amount managed to be reached), this method might be limited to distinguish small modulations induced by the vegetable molecules. Yet, the system was efficient to highlight the effects on N-nitrosation.

Indeed, the impacts of structure and composition of the medium on N-nitrosation was studied by comparing the results obtained on the emulsionized model with those on the buffer model. Results showed a significant effect on N-nitrosation modulation (p-value < 0.001) (Table 1B). N-nitrosation was significantly reduced (by almost 30%) in the emulsified model, compared to the model containing only aqueous buffer.

Those results are consistent with previously shown mechanisms. Combet et al. demonstrated in 2010 that some phenolics modulated differently N-nitrosation according to the presence of lipids (under the form of bulk oil) or not [START_REF] Combet | Dietary phenolic acids and ascorbic acid: Influence on acid-catalyzed nitrosative chemistry in the presence and absence of lipids[END_REF]. They notably showed the enhancement of N 2 O 3 synthesis in a lipidic compartment (up to 400 times) [START_REF] Combet | Dietary phenolic acids and ascorbic acid: Influence on acid-catalyzed nitrosative chemistry in the presence and absence of lipids[END_REF][START_REF] Combet | Fat transforms ascorbic acid from inhibiting to promoting acid-catalysed N-nitrosation[END_REF]. This highly reactive species is able to react with both secondary amines leading to nitrosamines [START_REF] Combet | Dietary phenolic acids and ascorbic acid: Influence on acid-catalyzed nitrosative chemistry in the presence and absence of lipids[END_REF][START_REF] De La Pomelie | Mechanisms and kinetics of tryptophan N-nitrosation in a gastro-intestinal model[END_REF][START_REF] Combet | Fat transforms ascorbic acid from inhibiting to promoting acid-catalysed N-nitrosation[END_REF] or with lipidic peroxyl radicals, leading to nitroso-peroxyl radicals [START_REF] Berton-Carabin | Lipid Oxidation in Oil-in-Water Emulsions: Involvement of the Interfacial Layer[END_REF][START_REF] Cillard | Mécanismes de la peroxydation lipidique et des anti-oxydations[END_REF], according to chemical competitions between the different nitrite targets. In absence of lipids, the nitrosoperoxyl radicals' synthesis path does not exist and the balance may therefore lean towards a promoted N-nitrosation reaction compared to the measurements in the emulsified medium. Yet, to the current knowledge, it is the first time that N-nitrosation is assessed in an oil in water emulsion, which is the most representative medium to model in vitro digestion of food bolus. Those results not only confirm the present developed model to study chemical reactivity modulations, but also deepen a rarely explored aspect explored, i.e., the reactivity of N-nitrosation in a complex environment close to the digestive one, herein represented by the use of an oil in water emulsion.

Moreover, a slight but significant reduction in N-nitrosation was noted under the combined presence of added ascorbate to the polyphenol or vitamin in the emulsified medium (p-value < 0.05), which was around a 12% decrease (Table 1C). Nonetheless, the absence of a distinguished modulation by ascorbate in present systems with or without the different pure vegetable substances may be surprising as ascorbate has been demonstrated several times to inhibit N-nitrosation alone [START_REF] Bartsch | Inhibitors of endogenous nitrosation mechanisms and implications in human cancer prevention[END_REF][START_REF] De La Pomelie | Mechanisms and kinetics of tryptophan N-nitrosation in a gastro-intestinal model[END_REF][START_REF] Tannenbaum | Inhibition of nitrosamine formation by ascorbic acid[END_REF] or with other phytomicronutrients [START_REF] Abraham | Ascorbic acid and dietary polyphenol combinations protect against genotoxic damage induced in mice by endogenous nitrosation[END_REF]. To the current knowledge, it is the first time that the chemical reactivity of N-nitrosation is assessed in an emulsified medium. Yet, the chemical reactivity of ascorbate in presence of a multiphase system may be more complex than in an aqueous system, as it was shown that N-nitrosation modulation may vary from inhibition to promotion according to the presence of bulk lipids or not [START_REF] Combet | Fat transforms ascorbic acid from inhibiting to promoting acid-catalysed N-nitrosation[END_REF]. Moreover, ascorbate may also modulate the stability of other polyphenols when introduced jointly [START_REF] Katz | The Link between Polyphenol Structure, Antioxidant Capacity and Shelf-Life Stability in the Presence of Fructose and Ascorbic Acid[END_REF], which emphasizes the complexity of the chemical interactions between the different compounds. This effect result is interesting within the framework of processed meats reformulation, where ascorbate is very often added. The model was herein efficient to identify a modulation of N-nitrosation.

Conclusions

The main purpose of this model was to characterize the existence of modulations induced by polyphenols and vitamins on targeted chemical reactions. It was conceived to help screening several vegetable molecules in good time and to obtain a global idea of their impact in a representative medium of processed meat products. It was shown to be efficient, and was authorized to demonstrate variations induced by polyphenols and/or vitamins, the medium structure, and the medium composition. The oil in water emulsion model was optimized to be reproducible, stable over time, and practical to implement in the context of a digestive physico-chemical environment. Moreover, the modulations herein shown have to be interpreted within the overall context of the study: the nature of the different substances, the emulsionized or non-emulsionized structure of the medium, and the method by differential UV-visible spectrophotometry. The present work provides information to wisely reformulate processed meats to enhance their nutritional qualities. Thanks to the present characterized modulations, deeper analyses with more sensitive methods would bring out the mechanisms underlying the modulations highlighted, as well as the involved and the neo-formed molecules at stake in the reactions.

Figure 1 .

 1 Figure 1. Fabrication process of the emulsified screening medium, with 5% or 10% of oil in water.

Figure 2 .

 2 Figure 2. Experimental design to screen the modulation of the chemical reactivity induced by vegetable molecules. Asc: ascorbate; PP: polyphenol; Vit.: vitamin; FeSO 4 : iron (II) sulfate heptahydrate; NaNO 2 : sodium nitrite; Ac-TRP: acetyl-tryptophan; TRP-NO: N-acetyl-DL-nitroso-tryptophan, C: concentration.

Figure 3 .

 3 Figure 3. Characterization of emulsions according to the modulation of two parameters: pH (2 or 3.5) and the amount of oil in water (5% or 10%). (A): Cumulative frequencies of the droplets enumerated (%) as a function of the PED (µm). The differences of perimeters at 90% of the enumerated particles are highlighted. (B): Characterization profiles of the emulsions, representing the circularity of the particles as a function of the PED (µm). The blue colour scale indicates the density of the identified particles: from cyan blue for single droplets to dark blue for several of them. The white background corresponds to the most accurate particles eager to be lipid droplets (PED < 10 µm and circularity from 90% to 100%). Representative pictures shot by the FPIA of the largest particles of each emulsion are given.

  Effect of the ascorbate presence on lipid oxidation. B: Effect induced by the medium (emulsified or aqueous) on N-nitrosation. C: Effect of ascorbate addition on N-nitrosation in the emulsified medium.

		Oxidation (nmol MDA Equivalent/mg Lipids)		N-Nitrosation (%)
		Emulsion	Emulsion	Buffer	Emulsion	Emulsion
		-	Ascorbate	-	-	Ascorbate
	Control	0.462 ± 0.052	0.367 ± 0.044	8.148 ± 1.601	5.825 ± 0.983	5.096 ± 1.044
	Ascorbate	0.367 ± 0.044 NS	0.592 ± 0.068 NS	6.857 ± 2.653 NS	5.096 ± 1.044 NS	4.245 ± 1.045 NS
	Trolox	0.397 ± 0.051 NS	0.454 ± 0.077 NS	7.384 ± 1.283 NS	4.354 ± 0.327 NS	4.687 ± 2.096 NS
	Chlorogenic Acid	0.057 ± 0.013 ***	0.058 ± 0.020 ***	5.500 ± 2.864 NS	6.630 ± 3.310 NS	4.337 ± 1.564 NS
	Rutin	0.052 ± 0.008 ***	0.035 ± 0.007 ***	12.743 ± 1.940 ***	9.112 ± 1.317 ***	10.458 ± 0.893 ***
	Naringenin	0.227 ± 0.030 ***	0.196 ± 0.032 ***	7.485 ± 0.917 NS	6.215 ± 2.176 NS	6.026 ± 0.417 NS
	Naringin	0.287 ± 0.017 ***	0.407 ± 0.013 NS	8.351 ± 0.592 NS	6.618 ± 1.398 NS	5.053 ± 1.376 NS

A:

Acknowledgments:

We thank Laurent Aubry, Thierry Sayd, Pascale Goupy and Claire Dufour for their scientific and technical contribution to this paper.

Funding: This research was funded by the consortium ADDUITS and INRAE.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Not applicable.

Author Contributions: Writing, Investigation, Data Curation, Formal analysis, Validation: E.K., A.B., P.G., C.F., S.B., A.P., G.N., V.S.-L., L.T.; Supervision, Conceptualization, Project Administration: P.G., A.P., G.N., V.S.-L., L.T.; Funding Acquisition: P.G., A.P., G.N., V.S.-L. All authors have read and agreed to the published version of the manuscript.

Conflicts of


P Marini

J Taieb

B Laurent

G Belier

A Chatillon

D Etasse

P Morfouace

M Devlin

J A Gomez

R C Haight

K J Kelly

J M O'donnell

K T Schmitt

Prompt Fission Neutron Spectra in the 239 Pu(n, f ) Reaction

Prompt fission neutron spectra from 239 Pu (n, f ) were measured with respect to 252 Cf spontaneous fission for incident neutron energies from 0.7 to 700 MeV at the Weapons Neutron Research facility (WNR) of the Los Alamos Neutron Science Center. A newly designed high-efficiency fission chamber was coupled to the highly segmented Chi-Nu neutron liquid scintillator array to detect neutrons emitted in fission events. The double time-of-flight technique was used to deduce the incident-neutron energies from the spallation target and the outgoing-neutron energies from the fission chamber. Prompt fission neutron spectra (PFNS) were measured with respect to 252 Cf spontaneous fission down to 200 keV and up to about 12 MeV for all the incident neutron energies with typical total uncertainties well below 2% up to about 7 MeV outgoing-neutron energy. The general trend of PFNS is well reproduced by JEFF3.3 and ENDF/B-VIII.0 evaluations, although a better agreement is found with JEFF3.3 . Discrepancies were observed for the low-energy part of the spectra, especially around the opening of the 2 nd -, 3 rd -and 4 th -chance fission. Neutron average kinetic energies as a function of incident-neutron energy are obtained experimentally with reported total uncertainties below 0.5%. The measured values agree with the most recent data. The trend is fairly well reproduced by the JEFF3.3 evaluation, although it fails to reproduce the experimental values within their uncertainties.

I. INTRODUCTION

Observables related to prompt fission neutrons represent a key parameter for nuclear energy applications and technology, and provide valuable information on the fission process. As far as the applications are concerned, it has been recently shown that accurate predictions of nuclear criticality using neutron transport codes crucially depend on the underlying nuclear data, especially the prompt fission neutron spectrum [1]. While the accuracy of evaluated neutron multiplicities, ν , has improved in recent years for some nuclei, the experimental database of prompt fission neutron spectra consists of a limited number of datasets, far less precise than those on the other key fission observables and often discrepant [START_REF] Capote | Report consultants' meeting on prompt fission neutron spectra[END_REF][START_REF] Neudecker | [END_REF].

For the 239 Pu(n, f ) prompt fission neutron spectrum (PFNS) the situation is similar: the few experimental data sets that are available and adequate for an evaluation [START_REF] Nefedov | Precision measurements of 252 Cf, 233 U, 235 U and 239 Pu prompt fission neutron spectra (PFNS) in the energy range 0.04-5 MeV[END_REF][START_REF] Boytsov | Relative measurements of 233 U+n th , 235 U+n th and 239 Pu+n th prompt fission neutron spectra (PFNS) in the energy range 0.01-5 MeV[END_REF][START_REF] Starostov | Precision measurements of 252 Cf, 233 U+n th , 235 U+n th and 239 Pu+n th prompt fission neutron spectra (PFNS) in the energy range 2-11 MeV[END_REF][START_REF] Starostov | Prompt neutron spectra from fission of 233 U, 235 U and 239 Pu by thermal neutrons and from spontaneous fission of 252 Cf in the 0.01-12 MeV energy range[END_REF][START_REF] Lajtai | Energy Spectrum Measurements of Neutrons for Energies 30 keV-4 MeV from Thermal Fission of Main Fuel Elements[END_REF][START_REF] Staples | [END_REF][10][11][12][13] are often not in agreement within quoted uncertainties [START_REF] Neudecker | [END_REF]14,15]. Moreover, there are large gaps in the experimental data for important parts of the outgoing-neutron spectra, i.e., below 1 MeV and above 8 MeV. These two regions of the PFNS are particularly challenging because of technical limitations (detection efficiency at low outgoing-neutron energy and statistics at high energy). The high α activity of the 239 Pu isotope makes the measurement even more challenging to carry out.

Due to these deficiencies in experimental data, evaluated data files partially rely on models to predict the spectra. How- * paola.marini@cea.fr ever, despite the considerable progresses in recent years, microscopic models are not yet able to precisely predict the fission observables, and in particular PFN spectra, because of the complex physical processes associated with the prompt emission of neutrons from fission of actinides. Phenomenological models, mainly based on the Madland-Nix approach [16], are then used to evaluate PFN spectra in the libraries. These models rely on parameters, tuned as best fits to the measured PFN spectra. However, it has been suggested that significant systematic errors could be present in the evaluated libraries, leading to a too hard PFNS [17]. In particular, according to Ref. [18], the PFN spectra of major actinides should have more neutrons below 1 MeV and fewer neutrons above about 6 MeV outgoing-neutron energies. Recently developed Monte Carlo Hauser-Feshbach models [19][20][21] point to the same direction. For the fast-neutron induced 239 Pu(n, f ) reaction, recent data from Lestone and Chatillon [11][12][13] support current PFNS evaluations for outgoing energies between 1.5 and 10 MeV, and 0.5 and 8 MeV, respectively. But these data do not rule out the ideas proposed in Ref. [18] that there should be more prompt fission neutrons below 1 MeV and fewer above 10 MeV.

The open question on the high-energy tail of the spectrum has important implications also on the understanding of the fission process. Indeed, this part of the spectrum is very sensitive to the total excitation energy sharing at scission: the spectrum gets harder at higher excitation energy. While in the original Madland-Nix model [16,22] a thermal equilibrium between the two nascent fragments at scission is assumed, a recent model [23][24][25] describes the fission process with a constant temperature level density, where each nascent fragment would be characterised by a temperature only dependent on the mass number of the fragment. This model naturally leads to an unexpected partitioning of the excitation energy when increasing the incoming neutron energy [23], which would affect the high-energy tail of the spectrum.

Our group has been involved since the 2000's in PFNS measurements [12,13,[26][START_REF] Taieb | Proceedings of the International Conference on Nuclear Data for Science and Technology[END_REF][START_REF] Kelly | [END_REF], in the framework of a collaboration agreement between the US Department of Energy -National Nuclear Security Administration (DOE/NNSA) and the French Commissariat à l'énergie atomique et aux énergies alternatives -Direction des applications militaires (CEA-DAM). First experiments on PFN spectra of 239 Pu(n, f ) were carried out in 2007 and 2008 [12,13]. Since then special efforts in the development of a new experimental area [29], new detectors, and data collection procedures were made with the aim of improving the measured PFNS accuracy and precision. In particular, a new fission chamber was developed, with a fission fragment detection efficiency better than 95%, despite the high α-activity of the sample. Such a feature is crucial to avoid any bias of the data associated to a particular range in angle or total kinetic energy. In this work, we present the results of the 239 Pu(n, f ) PFNS measurements performed in 2017 at the Los Alamos National Laboratory (LANL). The goals of this experiment are: (i) to significantly improve the experimental accuracy of the measured PFNS, in particular in the low-and high-energy tails of the spectrum, in the 1 to 700 MeV incident neutron energy range; (ii) to produce PFNS data as a function of incident-neutron energy, for which few experimental data exist to date, (iii) to provide an independent measurement of emitted-neutron mean kinetic energy as a function of incident-neutron energies with high accuracy.

The paper is structured as follows: in Secs.II and III the experimental setup and the data analysis are presented, respectively. Section IV presents and discusses the obtained results, while Sec. V concludes.

II. EXPERIMENTAL SETUP

The experiment was carried out at the WNR facility [30,31] at Los Alamos National Laboratory. A white pulsed neutron beam, spanning an energy range from below 1 MeV to several hundreds of MeV, is produced by 800 MeV proton-induced spallation reactions on a tungsten target. The beam is delivered in 625 µs-long macropulses with an average frequency varying between 100 and 120 Hz. Each macropulse contains micropulses separated by 1.8 µs. A 5%-borated, 1.27 cm-thick polyethylene absorber is placed into the beam line to harden the spectra in order to reduce the so-called wrap-around effect, i.e., to minimize the number of slow neutrons ( 680 keV) reaching the fission target at the same time or after the fastest neutrons of the following pulse. The neutron beam is collimated along a flight path of about 20 m before impinging onto the 239 Pu fission target. A beam pipe right upstream from the experimental hall was placed under vacuum to limit neutron scattering on air.

Data were taken for 20 days of effective time with a fission rate of 150 s -1 . The experimental setup (Fig. 1) couples the 54 Chi-Nu liquid scintillator array [33] to a newly developed fission chamber and a digital data acquisition system. The detectors are placed over a get-lost pit to minimize the amount of scattered neutrons on surrounding materials (see Sec. III C).

A. Fission chamber

The multi-plate fission chamber (Fig. 2) was designed to contain 47 mg of 239 Pu arranged in 22 deposits and 11 readout channels. The fissile material was deposited on every cathode, located 2.5 mm away from its corresponding anode. The diameter of each deposit was 33 mm and the isotopic purity of the material 99.90%. The chamber, filled with CF 4 gas to ensure a fast charge collection, operates 100 mbar above the local atmospheric pressure. This allows for a reduction in the amount of structural material, as shown in Fig. 3, thereby minimizing the neutron scattering both for the incoming neutron beam and for the emitted fission neutrons (see Sec. III C). A more detailed description of the detector can be found in [32].

Front-end electronic boards containing pre-amplifiers and shapers were developed to match the detector characteristics. Thanks to the detector and electronics design, an improved α-fission fragment discrimination could be obtained, with a fission detection efficiency better than 95%, despite approximately 10 MBq α activity per channel [START_REF] Budtz-Jørgensen | Investigation of fission layers for precise fission cross-section measurements with a gridded ionization chamber[END_REF]. Two pulse height spectra (shown in Fig. 4) measured during the experiment with (in blue) and without (in red) beam illustrate the discrimination obtained. A time resolution better than 0.8 ns full width at half maximum (FWHM) could be achieved. This leads to an emitted-neutron time-of-flight resolution of about 1.5 ns (FWHM). The latter arises from summed contribution of the fission chamber and the neutron detector time resolutions.

An identical chamber, containing a 252 Cf deposit of the same size as the 239 Pu ones, was used for neutron detection efficiency measurements (see Sec. III B).

For sake of completeness, we mention here that, during the experiment two channels of the Pu fission chamber were not working. Those are the third and the seventh channels. This does not introduce any significant bias in the experimental results, since the interaction probabilities of 1 and 10 MeV fission neutrons with the material supporting each deposit are 0.3% and 0.2%, respectively. In other words, the stack of 239 Pu deposits is equivalent to a single deposit, with the advantage of a thin deposit, i.e., allowing the recoil of fission fragments out of the target.

B. Neutron detection array

The Chi-Nu neutron detector array [33] was used to measure neutrons in coincidence with a fission chamber signal. The Chi-Nu high-energy array consists of 54 EJ-309 liquid scintillator cells, read by photomultipliers, and arranged on a hemisphere with inner radius of about 1 m around the fission chamber, as shown in Fig. 1. The diameter and the thickness of each cell are 17.78 and 5.08 cm, respectively. The whole array covers close to 10% of the solid angle. The detectors are placed at nine different angles, with 6 detectors per angle, θ lab , from 30 • to 150 • , with respect to the beam axis. The angular distribution of the emitted neutrons can therefore be studied. The use of the Chi-Nu array constitutes a significant improvement with respect to previous measurements [12,13] performed with the FIGARO array, due to the higher number of scintillation detectors and the significant reduction of scattering material near the fission chamber and the detector array.

The EJ-309 liquid scintillator is sensitive to both neutrons and γ-rays. Particle identification was performed via Pulse Shape Discrimination (PSD) technique, which is based on the charge integration of the slow and fast components of the pulse. The neutron-γ discrimination was optimized adjusting the duration of the time integration windows.

A 2 mm-thick Pb shield was placed in front of each cell to reduce the amount of low energy ( 300 keV) γ-rays, impinging on the cell. A typical pulse-shape discrimination plot is shown in Fig. 5, where the slow to fast pulse-component ratio (PSD) is plotted as a function of the total pulse charge. The use of the Pb shield allowed us to obtain a clear neutron-γ discrimination down to 30 -40 keV electron equivalent energy [35].

C. Data acquisition system

The digital Fast Acquisition System for nuclEar Research (FASTER) [START_REF]LPC-Caen[END_REF] was used during the experiment. Signals were digitized by a 500 MHz, 12-bits, low noise Analog to Digital Converter (ADC) and processed by real time numerical modules implemented into Field Programmable Gate Arrays (FPGA). The signal-to-noise ratio, as well as the zero time crossing determination on the Constant Fraction discriminator (CFD) signal, are optimized by limiting the analog bandwidth with the use of an input passive low pass filter (100 MHz). This allows to obtain a time resolution as low as 7.8 ps. The use of this acquisition system allowed the near complete avoidance of numerical dead-time. The acquisition was triggered and a coincidence window of 1.82 µs opened when a signal was present in the fission chamber. Signals from the scintillators falling in the coincidence window were recorded.

III. DATA ANALYSIS

The experiment is based on the double time-of-flight technique. For each triggered event, the time of flight of the incoming neutron from the spallation target to the fission chamber and the time of flight of the emitted neutron from the fission chamber to the scintillator were measured. From the measured raw time of flight, the absolute times of flight for incoming and emitted neutrons were determined from the position of the γ-flash generated by the interaction of the proton beam on the tungsten target and from prompt-fission γrays, respectively. Distances between the fission target and each scintillator cell were carefully measured with an uncertainty better than 0.2% with a high precision laser range meter. Given the importance of knowing the distance precisely, a careful consistency check of the measured values was performed at the very beginning of the data analysis.

To measure the flight path length from the spallation source to each deposit in the fission chamber, a 0.5 inch-thick carbon absorber was inserted in the beamline upstream the experimental hall. The positions of the 2.08 and 6.3 MeV resonances in the total cross section gave the distances between each deposit of the fission chamber and the spallation target, with an absolute uncertainty of 4 mm over the 21.5 m flight path.

The combination of the time-of-flight and distance measurements gives us access to the incident and emitted neutron kinetic energies. The obtained relative uncertainty on the incident-neutrons energy is 0.08%. The uncertainty on the outgoing-neutron energy is dominated by the time-of-flight resolution (0.6 ns 1 σ).

A. Events selection

α-fission fragments discrimination

A threshold was set to discriminate fission from α-decay and nuclear reaction events in the fission chamber pulseheight spectrum (see Fig. 4). The threshold position is the best compromise between minimizing the contribution of α-decay and reaction events and preserving the full fission-fragment total kinetic energy and angular distributions.

γ-neutron discrimination

Special efforts were made to improve the γ-neutron discrimination and γ-ray rejection. A first selection based on the detected time-of-flight was performed to remove prompt γ-rays. An additional selection was placed, for each neutron detector, on the PSD vs total charge correlation, shown in Fig. 5, to remove the remaining γ-rays. The cut was determined according to the procedure described in Ref. [START_REF] Polack | [END_REF]: for each total charge interval, the fast to total pulse-component ratio was fitted with two Gaussians, as shown in Fig. 6. This allowed us to define the cut with the same criterion for all the detectors and to estimate the remaining contribution of γ-rays, which is lower than 0.1%.

To remove a large fraction of scattered neutrons impinging on the detectors, a light output vs. outgoing-neutron kinetic energy correlation, as shown in Fig. 7, was made. Since a correlation exists between the kinetic energy of the neutron impinging on the scintillator cell and the scintillator light output, only events satisfying this correlation were selected (red contour in Fig. 7).

With these constraints, neutrons down to 200 keV could be identified. As these selections are applied both to the 239 Pu and 252 Cf PFN spectra analyses as discussed below, possible systematic uncertainties associated to the selections cancel out when correcting the measured 239 Pu spectra for the neutron detector efficiency (see Sec. III B).

B. Neutron detector efficiency

Neutron detector efficiencies were obtained by measuring the PFNS of the 252 Cf spontaneous fission reaction in the same experimental conditions. For this purpose, beam-off runs were performed with a dedicated fission chamber containing a 252 Cf deposit placed on the central cathode of the chamber. All the structural materials constituting the 239 Pu fission chamber were present in the chamber used for the 252 Cf measurement. Fission signals triggered the data acquisition. The presence of a single deposit in the Cf chamber, as contrasted to the 11 deposits in the Pu chamber, does not introduce a significant distortion of the measured spectra due to the very low interaction probabilities of fission neutrons with the material supporting each deposit. Moreover the exact distance of each Pu deposit to each neutron detectors was accounted for. The efficiencies were determined from 252 Cf spontaneous fission PFNS with respect to the Mannhart evaluated PNFS standard [38], shown in Fig. 8, normalized to the evaluated standard ν tot of (3.7637 ± 0.42%) for 252 Cf(sf) [39]. An example of the typical relative neutron detection efficiency is shown in Fig. 9.

We stress that a threshold as low as 200 keV neutron energy was obtained with the present setup. The counting statistics for the 252 Cf(sf) was of 2.7 • 10 8 fission events, comparable to the one collected for the 239 Pu (n,f).

C. Scattering corrections

The presence of structural and surrounding materials, and to a lesser extent air, causes the scattering of neutrons distort-ing the measured PFNS. The whole setup was placed above a 2 m deep "get-lost" pit, the beam pipe upstream from the experimental hall was placed under vacuum, and special efforts were dedicated to the development of the fission chamber with a reduced amount of scattering material (see Sec. II A and Fig. 3). Nevertheless, the remaining scattered neutron contributions have to be corrected for. Scattering of prompt fission neutrons leads to an erroneous determination of their flight path, and thus of their kinetic energy. This contribution is accounted for, at a first order, when correcting the spectra for the detector efficiency. Indeed the efficiency measurement was performed in the same experimental conditions as the real measurement. Moreover, under the reasonable assumption that the 252 Cf and 239 Pu have similar PFN spectra, the distortions due to the remaining scattering events are compensated for in the efficiency calibration process. This is further discussed in Sec. III E.

The most significant contribution to spectrum distortion and background comes from neutrons scattered from the incident neutron beam and introduces a significant background in the PFNS. This background is not correlated with fission events, thus creating random coincidences in neutron detectors, and its contribution varies with time after the proton burst. A pulser trigger, acting as a fake-fission generator, was used to start the acquisition and record neutron-detector random coincidences during the whole experiment. As the beam was on, the various incident-neutron times-of-flight were randomly sampled and the background monitored as a function of the beam energy. The pulser rate was much higher than the rate of real fissions (≃ 150 fissions• s -1 ), so that the statistical uncertainty associated to the background contribution was 4 times smaller than the statistical uncertainty associated to real fissions. An example of measured fission neutrons and random coincidence times-of-flight is shown in Fig. 10 in blue and red, respectively. It can be noted that for times-of-flight under about 20 and above 150 ns (corresponding to energies of about 13 and 0.2 MeV, respectively) the difference between the measurement and the background vanishes, validating the correct background measurement and subtraction. Random coincidences were then subtracted offline.

D. Extraction of the PFNS

Thanks to the high statistics accumulated during the experiment and the low detection thresholds, PFNS from 200 keV to about 15 MeV could be extracted, the associated PFN observables studied, and their evolution investigated as a function of the incident neutron energy. Data were sorted in eighty-six incident neutron energy bins with energies ranging from 0.7 to 750 MeV. The bin widths were chosen based on the available statistics and on the incident-neutrons time-of-flight resolution. The bin width was 0.5 MeV at low incident neutron energies and it increased up to 20 MeV above 250 MeV. The used bin-widths are reported in Table I.

For each detector, time-of-flight spectra were measured for each incident neutron energy bin. The time spectra, corrected for random coincidences, were then converted into energy spectra and corrected for the detection efficiency normalized to the 252 Cf(sf) standard. The final spectrum for a given incoming-neutron energy range was finally obtained by combining all the detector spectra. In the following, results are presented with the absolute statistical and systematics error bars, propagated through the data analysis. The systematic uncertainty is the uncertainty on the evaluated 252 Cf spectrum. The horizontal bars indicate the width of the emitted neutron energy bin and do not represent an error bar. The chosen variable bin width for the energy spectra is a compromise between a precise shape of the spectrum, enough statistics and the outgoing-neutron time-of-flight resolution.

An example of the measured prompt fission neutron spectra is shown in Fig. 11. The spectrum was obtained for an incident neutron energy ranging from 0.7 to 1.2 MeV, with a mean energy of 0.97 MeV. The performances of the setup and the associated electronics chain, and the high collected statistics, allowed PFN spectra to be experimentally measured from 0.25 MeV to 10-to-12 MeV, depending on the incident neutron energy, with total uncertainties from 0.2% to 10% around 0.8 MeV and 12 MeV, respectively.

Extrapolation of PFNS at low kinetic energy

Despite the rather low outgoing-neutron energy threshold, it should be kept in mind that quantities such as the mean kinetic energy of prompt fission neutrons, E, are sensitive to the low-energy part of the spectrum. Owing to simple theoretical descriptions of PFNS based on either Watt [40] or Maxwellian [START_REF] Bloch | Atomic Energy Commission Document AECD-3158[END_REF] spectra, the measured spectra were extrapolated at energies from 0.2 MeV downwards by fitting the low energy part of the spectra with a Watt-type and a Maxwell-type distribution [42]. The Watt-based extrapolation was limited to incident energies below the opening of the second-chance fission, around 6 MeV. The fitting ranges were from 0.2 to 1.2 MeV for the two functions. The uncertainties on the extrapolated points at 0.05 and 0.15 MeV were given by the uncertainties and covariances on the fit parameters. Consistent results were obtained below 6 MeV incident-neutron energy when using Watt-type and Maxwell-type distributions. This validates the use of a Maxwell-type distribution at energies above 6 MeV. As a test case, the same extrapolation method was applied to identically truncated PFNS generated by the General Description of Fission Observables (GEF) code [43]. The procedure was applied to GEF PFNS from 1 to 20 MeV incident neutron energies. From the comparison of the extrapolated and the full distributions, we observe differences smaller that 0.1% on the PFN spectra, as well as on the PFN mean kinetic energy, E, thus validating the extrapolation method. An example of the result is shown in the insert in Fig. 11, where blue points are experimentally measured and red points are extrapolated. In the following these extrapolated spectra will be used, unless differently specified.

E. Study of possible experimental bias

As mentionned neutron distorsion spectra corrections are obtained through the measurement of neutron detection efficiencies with a 252 Cf fission chamber (see Sec. III B). Under the reasonable assumption that the 252 Cf PFNS is sufficiently close to the 239 Pu, this is justified since the 252 Cf and the 239 Pu fission chambers are exactly the same. In order to validate it the fission chamber as well as neutron detectors were simulated with the GEANT4 toolkit [START_REF] Allison | Nuclear Instruments and Methods in Physics Research Section A: Accelerators[END_REF] using the NPTool package [45]. The custom neutron interaction model, MENATE_R, was used, where the inelastic neutron-carbon and neutron-hydrogen reactions are modeled as discrete reaction channels based on experimental information [46]. The input 252 Cf PFNS was assumed to be the evaluated Mannhart's spectrum [38], while experimentally measured PFN spectra for incident mean energies of 1, 7.4 and 14 MeV were used as input for 239 Pu(n,f) PFN spectra. Fifty million events were generated and the simulated 252 Cf(s.f.) and 239 Pu(n,f) PFN spectra extracted. The detector efficiencies and the 239 Pu spectra were determined following the same procedure as for the experimental data.

The influence of the neutron detector and of the fission chamber materials were studied separately. The biggest distortion to the 239 Pu(n,f) PFN spectra comes from neutron scattering on the neutron detector materials. It is of about 1.5% and is observed at the opening of the second-chance fission for an outgoing neutron energy below 250 keV. In the other region of the spectrum and for other incident neutron energies the distortion is negligible. A negligible distortion is also introduced by the presence of the fission chamber, as well as by two not working channels of the chamber itself (see Sec. II A).

To validate the assumption that the 252 Cf PFNS is sufficiently close to the 239 Pu, the possible systematic bias introduced by the use of the 252 Cf(s.f.) PFN spectra to determine the detector efficiencies were investigated. As an example, the ratios between the 239 Pu(n,f) PFN spectrum determined as in the data analysis and the PFN spectrum used as input in the simulation are plotted in Fig. 12 for 0.87 and 7.38 MeV incident neutron energies. The dashed line has the purpose of guiding the eyes. A very good agreement is found for all the outgoing neutron energies for 0.87 MeV incident neutron energy, and, more in general, for incident neutron energies significantly different from the opening of the 2-th chance fis- sion. Indeed it is around this energy that a significant distortion is observed for outgoing-neutron energies below 1 MeV. These results support the use of the 252 Cf PFNS to account for the presence of surrounding materials and to determine the detector efficiencies, and indicate that it does not bias the experimental results.

F. Study of wrap-around background

As discussed in Sec. II, due to the short micropulse spacing (1.8 µs) and the long neutron flight-path (∼ 20 m), neutron time-of-flight distributions are affected by the so-called wraparound background. Indeed slow neutrons ( 680 keV) remaining after the polyethylene absorber reach the fission target at the same time or after the fastest neutrons of the following micropulse. Fission events induced by high-energy neutrons and low-energy neutron background can not be discriminated on time-of-flight basis. The fraction of wrap-around background in each incident neutron energy bin was estimated using data collected with a different DAQ, where the time of flight of neutrons belonging to the same macropulse are all stored [START_REF] Kelly | Proceedings of the 20th Topical Meeting of the Radiation Protection and Shielding Division[END_REF]. This allows one to inspect seperately fission events associated to each micropulse in a macropulse. The last micropulse was considered. Indeed in this case, being two macropulses separated by about 625 µs, the slow neutrons do not overlap with the fastest neutrons of the following micropulse, and their time of flight can be cleanly characterized. This is clearly illustrated in Fig. 13 with the time spectrum of the incident neutron, in pink, which represents the last two micropulses of a macropulse. A good agreement was found between the incident-neutron time of flight measured in our experiment and the time of flight of incident neutrons belonging to the last micropulse measured in [START_REF] Kelly | Proceedings of the 20th Topical Meeting of the Radiation Protection and Shielding Division[END_REF], with the appropriate normalization. Hence these events can be use to determine the proportion of wrapped neutrons in the other micropulses. The time-of-fligh spectrum of the last micropulse was backshifted of 1.8 µs (blue line in Fig. 13). The backshifted-to- last micropulse time-of-flight ratio gives the fraction of slow neutron background present in each incident neutron energy bin. The wrap-around contribution varies from a maximum of about 10% to about 3% below 20 MeV and above 200 MeV, respectively. The associated relative uncertainty varies from 10% to few % as the incident neutron energy increases, due to the statistics available in the used data.

It is worth recalling that slow neutrons giving rise to the wraparound effect have energies 680 keV. The PFN spectra for these incident neutron energies were not measured during the experiment. However, under the reasonable assumption that PFN spectra for incident neutron energies below 1 MeV vary slowly, the PFN spectrum measured for an incident neutron energy ranging from 0.7 to 1.2 MeV was used to correct PFN spectra for higher incident energies. It is worth noting that this introduces a correlation between all the PFN spectra. The uncertainties on the 0.7 to 1.2 MeV incident energy PFN spectrum as well as on the wrap-around fraction were propagated to obtain wrap-around-corrected PFN spectra for all the incident energy bins. In the following we will refer to these wrap-around corrected spectra as "spectra" and they will be used to calculate the quantities of interest, unless differently specified.

IV. RESULTS

A. PFNS

The PFNS measured for an average incident-neutron energy of 1.44 MeV is presented in Fig. 14 and compared to data from Lestone et al. [11] and Staples et al. [START_REF] Staples | [END_REF] for 1.5 MeV incident energy. The ratio of the PFN spectrum to a Maxwellian distribution with temperature T = 1.32 MeV is provided as supplemental material (Fig. ??). Our data are in very good agreement within the error bars with data from Lestone on the whole outgoing-energy range. It should be noted that results from Lestone were obtained from underground nuclear explosion measurements, with a much higher neutron flux on the studied sample. A very good agreement is found also with data from Staples, with small discrepancies above about 9 MeV, due to a change in the slope around 6 MeV, which leads to a slightly softer spectrum. Similar conclusions can be drawn when comparing the spectrum measured at 2.5 MeV, provided as supplemental material, with the one measured by Staples.

In the lower panel of Fig. 14 the relative uncertainty on the spectrum is presented (black circles). This is a typical example of the attained accuracy in the measurement for the smallest incident energy bins (0.5 MeV bin width): between 0.3 and 3 MeV the uncertainty is smaller than 1%, it stays below 2% up to 6 MeV and it is less than 10% up to about 11 MeV. These values have to be compared to the uncertainties obtained by Lestone, which vary from 2 to 10% between 1.5 and 10.5 MeV, and to those measured by Staples, which are around 10% on the whole outgoing-energy range. Figure 15 shows spectra for four incident neutron energy bins, compared to the ENDF/B-VIII.0 [START_REF] Brown | [END_REF]49] and JEFF3.3 [START_REF]JEFF3.3 Evaluated data Library -Neutron Data[END_REF] evaluations. Spectra for the other energy bins are provided as supplemental material. All the spectra are normalized to the integral of the PFNS on the whole energy range (i.e., to the experimental neutron multiplicity). Overall, a fair agreement is observed between the data and the evaluations. Slight discrepancies are found for the low-(< 1 MeV) and high-energy tails (> 9 MeV) of the spectra, depending on the incident neutron energy. We concentrate here on outgoing-neutron kinetic energies above 3 MeV. For spectra up to the opening of the second-chance fission (≃ 6 MeV), a rather good agreement is observed between the data and the evaluations. For energies above the second chance fission, a better agreement is observed at high kinetic energy with the JEFF3.3 evaluation, while ENDF/B-VIII.0 predicts harder spectrum (a higher number of high-energy fission neutrons). Data indicate that both the evaluations predict harder spectra for energies above 18 MeV. Figures 16,17 and 18 show the ratio of PFN spectra to a Maxwellian distribution with temperature T = 1.32 MeV for five incident-neutron energy bins, compared to ENDF/B-VIII.0 and JEFF3.3 evaluations. In Fig. 17 only emitted neutrons with kinetic energies below 5 MeV are shown, to focus the attention on the low-energy part of the spectra. On the contrary Fig. 18 focuses on the high-energy part of the spectra. The spectra, as well as the evaluations, were normalized to the integral of the PFN spectra on the whole energy range. For spectra up to 3.4 MeV incident-neutron energy, predictions seem to underestimate the amount of fission neutrons below 500 keV, while a better agreement is found for higher incident energies. The situation changes for energies around the opening of the second-, third and forth-chance fission (6, 14 and 24 MeV, respectively), where discrepancies are observed for outgoing energies below 1.5 MeV.

B. PFN mean kinetic energy

The high statistics accumulated during the experiment and the Chi-Nu segmentation allows us to obtain a precise shape of the PFNS as a function of the neutron emission angle with respect to the beam direction (θ lab ) for each incident-neutron energy range studied. Nine spectra, one for each measured θ lab , were therefore obtained by combining the spectra obtained from the six detectors at the considered angle. The average neutron kinetic energy, E, was computed from the spectra for every θ lab and incident energy bin. No threshold was applied. An example of angular dependence of E, E(θ lab , E in ), is plotted in Fig. 19 for an incident neutron energy ranging from 3.7 to 4.2 MeV. The total uncertainty on E(θ, E in ) is close to 0.3 %. It includes the statistical uncertainties on the 239 Pu and 252 Cf measurements, on their background measurements and on the wrap-around correction. The systematic uncertainty encompasses the uncertainty of the evaluated 252 Cf(s.f.) PFN spectra. We remind that the associated correlation matrix was not propagated. The angular distributions exhibit two main characteristics: first, they are not isotropic, even at low incident energies, with a E(0 • )/E(90 • ) of about 1.04 below 10 MeV. The anisotropy arises from the fact that PFN carry angular momentum from fully accelerated fission fragments. Information on fission fragments angular momentum at scission could therefore be extracted by model comparison, which is beyond the scope of this paper. Second, angular distributions are characterized by a certain degree of forward/backward asymmetry which increases with the incident-neutron energy, reflecting the increase in the kinematical boost and pre-equilibrium emission.

The experimentally measured mean kinetic energy angular distributions were also needed in the determination of the average neutron E(E in ) for each incident neutron energy range. They were fitted with polynomial functions and E(E in ) was taken as the sum of the experimental values and the values deduced from the fitted distribution, for those angles that were not covered by detectors during the experiment. Several different fitting functions were tested to estimate the systematic uncertainty on E due to the arbitrary choice of the functions. It amounts to about 0.2% and was calculated as the root-meansquare of the Evalues obtained with the different fitting functions for each incident neutron energy. The envelop of the different fitting functions used is shown as shaded area in Fig. 19. The total uncertainty is estimated to be between 0.2% and 0.5% depending on the incident neutron energy bin.

The obtained values are plotted in Fig. 20 as a function of the kinetic energy of the incoming neutron. All available other experimental results are also plotted on the same graph [12,13,[START_REF] Coppola | [END_REF]52]. The mean kinetic energy of the emitted neutrons increases rather slowly over the full energy range, spanning from 2.1 to 3.5 MeV. Above 20 MeV, we observe a slower increase of the kinetic energy, while fluctuations are observed below this energy. A clear dip of about 100 keV depth is observed around 6 MeV, and described with 8 experimental data points between 5 and 11 MeV. Smaller second and third dips are observed around 14 and 24 MeV, as reported also in [12]. The presence of these dips is due to pre-fission neutrons emit- ted at the opening of the second-(third-and fourth-) chance fission. Indeed pre-fission neutrons, evaporated from the compound nucleus before fissioning, have smaller kinetic energy than fission neutrons, since they do not profit from the kinematical boost from fission fragments. A good agreement with the most recent data [12] is found up to 14 MeV. At higher energy, where pre-equilibrium reactions set in, the discrepancy is explained by the fact that the setup used in Ref. [12] is most sensitive to lower energy evaporation neutrons and not to the higher energy neutrons emitted in the forward direction. A fair agreement is observed also with data from Refs. [13,52], which present large error bars. Our data are not consistent with data from Ref. [START_REF] Coppola | [END_REF].

Figure 21 shows the comparison of our data to ENDF/B-VIII.0 and JEFF3.3 evaluations. Below the opening of the second-chance fission the JEFF3.3 evaluation reproduce the trend of E, although the values are slightly underestimated. On the contrary ENDF/B-VIII.0 indicates a steeper increase of E with increasing the neutron energy, which is not observed in the data. Above 5 MeV JEFF3.3, and to a lesser extent ENDF/B-VIII.0 , reproduce the dip depth, although they are not consistent with the experimental values. Both evaluations indicate the presence of a second dip around 12 MeV, whose depth is much less pronounced in the experimental data than in the evaluations. It appears that all evaluations either underestimate (JEFF3.3 ) or overestimate the second and third chance fission probability in 239 Pu (n, f ). These features notably impact the PFNS and the mean neutron energy. None of the evaluations is in agreement with the measured data.

V. CONCLUSIONS

Prompt fission neutron spectra from 0.2 to 10 -12 MeV outgoing-neutron energy were measured with respect to 252 Cf spontaneous fission with the Chi-Nu liquid scintillator array for incident neutron energies from 1 to 700 MeV. The obtained final uncertainties are well below 2% for outgoingneutron energies up to 6 MeV, and lower than the ones from all previous measurements. In general, the data agree well with theoretical predictions based on the Los Alamos model, ENDF/B-VIII.0 and JEFF3.3, from 1 to about 10 MeV outgoing-neutron energies. Below about 3 MeV incident energy, evaluations underestimate the number of low-energy neutrons (< 500 keV) and significant discrepancies are observed below outgoing ener-gies of 1.5 MeV around the opening of the second-, third-and forth-chance fission. Above 6 MeV incident energy, a better agreement is found at high kinetic energy with the JEFF3.3 evaluation.

The mean energy of the PFNS was measured with a total uncertainty better than 0.5% for all incident neutron energies and shows a continuous increase with the beam energy. Signatures of the opening of the second-third-and fourth-chance fissions can be recognized around 6, 14 and 24 MeV. A good agreement is found with previous data from Ref. [12] up to the onset of pre-equilibrium reactions, around 10 -12 MeV. The shape, but not the measured values, is better reproduced by the JEFF3.3 evaluation.

The obtained accuracies were made possible thanks to a newly developed fission chamber with a detection efficiency close to 100%, its associated electronics, the high statistics collected and the Chi-Nu segmentation and neutron/γ discrimination capabilities. Given the success of the present experiment, further measurements should be performed to provide more accurate PFNS data than those available at present on other relevant actinides.

Figure 1 .

 1 Figure 1. Photo of the experimental setup. The photo is looking upstream towards the spallation target. The fission chamber is in the center of the photo and is viewed by 54 liquid scintillators. The floor is 1.25 cm-thick aluminum over a get-lost pit 2 meters deep.

Figure 2 .

 2 Figure 2. Photo of the interior of the fission chamber, showing the stacking of anodes and cathodes. The cathodes contain the 239 Pu deposits, the anodes are connected to the lower panel.

Figure 3 .Figure 4 .

 34 Figure 3. Photo of the low-mass 1 mm-thick aluminum outer structure of the fission chamber. 50 and 100 µm-thick tantalum foils glued on the sides ensure the airtightness of the chamber [32].

Figure 5 .

 5 Figure 5. (Color online) Correlation between the pulse shape discrimination (PSD) and the total charge deposited in an EJ309 scintillator by γ rays and neutrons. Signals falling into the area outlined by the red contour are associated to the detection of neutrons. (see Sec. III A 2).

Figure 6 .

 6 Figure 6. (Color online) Example of Gaussian fit of the fast to total pulse components ratio for a given charge interval measured in one cell. The dotted blue curve is the fit of the neutron component, while the green line corresponds to the γ-ray component. The red dot indicates the position of the used threshold to discriminate neutrons and γ-rays. Selections were applied neither on incident-neutron energy nor on emitted-neutron energy, but were used to evaluate the remaining contribution of the γ-rays (see text).

Figure 7 .

 7 Figure 7. (Color online) Correlation between scintillator light output and outgoing-neutron kinetic energy, deduced from the time-of-flight measurement, of detected neutrons. The red contour selects "good neutrons" (see text).

Figure 8 .Figure 9 .

 89 Figure 8. Evaluated252 Cf PFNS[38], normalized to 3.7637 neutrons[39], used for neutron detection efficiency determination (see text). Horizontal bars indicate the width of the outgoing-neutron kinetic energy bins. In the insert a zoom of the low energy part of the spectrum is presented. The relative uncertainties are plotted in the lower panel.

Figure 10 .

 10 Figure 10. (Color online) time of flight of emitted neutrons (blue) and associated background (red) measured for an incident neutron energy between 1.7 and 2.2 MeV and normalised to the number of events.

Figure 11 .

 11 Figure 11. (Color online) PFNS for an incident neutron energy ranging from 0.7 to 1.2 MeV. When not visible uncertainties are smaller than symbols. In the insert is a zoom of the low energy part of the experimental spectrum (blue). The dashed line is the Watt-type fitted function and the red symbols are the extrapolated values below 200 keV.

Figure 12 .

 12 Figure 12. (Color online) Ratios between the 239 Pu(n,f) PFN spectrum determined as in the data analysis and the PFN spectrum used as input in the simulation for 0.87 (red) and 7.38 MeV (blue) incident neutron energies. .

Figure 13 .

 13 Figure 13. (Color online) Incident-neutron time of flight from[START_REF] Kelly | Proceedings of the 20th Topical Meeting of the Radiation Protection and Shielding Division[END_REF]. The pink spectrum represents the last two micropulses of a macropulse whereas the blue one represents the last micropulse shifted by 1.8 µs.

Figure 14 .

 14 Figure 14. (Color online) Prompt fission neutron spectrum for an incident neutron energy ranging from 1.2 to 1.7 MeV (black squares) compared to data from Lestone et al.[11] (blue triangles) and from Staples et al.[START_REF] Staples | [END_REF] (magenta triangles), measured at 1.5 MeV. In the lower panel the uncertainties of the three measurements are compared.

Figure 15 .

 15 Figure 15. (Color online) Prompt fission neutron spectrum for four beam energy ranges, indicated among square brackets, together with the mean incident neutrons kinetic energy of each bin. Experimental data (crosses) are compared to the ENDF/B-VIII.0 (dotted blue line) and JEFF 3.3 (dashed green line) evaluations. A zoom of the low energy part of the spectra is shown in the inserts.

Figure 16 .

 16 Figure 16. (Color online) Ratio of PFNS to a Maxwellian distribution with T = 1.32 MeV for a mean incident energy of 1.44 MeV. Experimental data (crosses) are compared to the ENDF/B-VIII.0 (dotted blue line) and JEFF 3.3 (dashed green line) evaluations.

Figure 17 .

 17 Figure 17. (Color online) Zoom below 5 MeV neutron kinetic energy of the ratio of PFNS to a Maxwellian-type distribution with T = 1.32 MeV for four beam energies ranges. Beam energies are indicated in square brackets, together with the mean incident neutrons kinetic energy of each bin. Experimental data (crosses) are compared to ENDF/B-VIII.0 (dotted blue line) and JEFF 3.3 (dashed green line) evaluations.

Figure 18 .

 18 Figure 18. (Color online) Zoom above 4 MeV neutron kinetic energy of the ratio of PFNS to a Maxwellian-type distribution with T = 1.32 MeV for four beam energies ranges. As Fig. 17.

Figure 19 .

 19 Figure 19. Angular dependence of E(θ lab , E in ) for an incident neutron energy ranging from 3.7 to 4.2 MeV. The shaded area is the envelop of the best polynomial fits to the experimental data (see text).

Figure 20 .

 20 Figure 20. (Color online) Measured mean kinetic energy E(E in ) of PFN as a function of incident neutron energy compared to data from previous experiments[12,13,[START_REF] Coppola | [END_REF]52] (panel a). Among brackets is the range over which E(E in ) was calculated, when specified in the publications. Relative uncertainty on E(E in ) a function of incident neutron energy (panel b).

Figure 21 .

 21 Figure 21. Measured mean kinetic energy E(E in ) compared to ENDF/B-VIII.0 and JEFF3.3 evaluations.

Table I .

 I 7 and 2.2 MeV and normalised to the number of events.E in range E in bin width E in range E in bin width Incident-energy bin widths used in the analysis.

	(MeV)	(MeV)	(MeV)	(MeV)
	0.7 -6.2	0.5	26.4 -32.4	3.0
	6.2 -9.4	0.8	32.4 -82.4	5.0
	9.4 -20.4	1.0	82.4 -252.4	10.0
	20.4 -26.4	1.5	> 252.4	20.0

-10 3 -10 2 -

ACKNOWLEDGMENTS

We wish to acknowledge A. Moens, G. Sibbens and D. Vanleeuw from the JRC-Geel target preparation laboratory for providing 239 Pu samples and assisting their mounting in the fission chamber. We also wish to acknowledge the support of E. Bond from LANL C-NR for providing the 252 Cf sample. This work was performed under the auspices of a cooperation agreement between CEA/DAM and DOE/NNSA on fundamental sciences and benefited from the use of the LANSCE accelerator facility. The work at Los Alamos was performed under the auspices of the U.S. Department of Energy by Los Alamos National Laboratory under Contract DE-AC52-06NA25396.