Hui-Ying Coudour

Wang
email: wang@ensma.fr

H Q Dong

B Magnognou

J P Garo

B Coudour

Hui-Ying Wang

Fully Coupled CFD Simulation of the Ignition Risk of Unburnt Gases in an Exhaust System Connected

Keywords: enclosure fire, liquid fuel, ventilation rate, ignition risk, extraction duct, dilution duct

Introduction

Liquid pool fires are a significant hazard to industrial facilities. The liquids could originate e.g. from leaking transformers generators or other machinery. Knowing the fire burning rate is the starting point of any fire safety analysis. The factors affecting the burning rates of liquid pool fires in open atmosphere are well known for a wide variety of liquids. The empirical correlation of Peatross [START_REF] Peatross | Ventilation effects on compartment fire characterization[END_REF] for fuel mass loss rate of a liquid fuel is limited to the large enclosure where the heat fluxes from hot wall can be negligible. The theoretical model developed by Utiskul [START_REF] Utiskul | Theoretical and experimental study on full-developed compartment fires[END_REF] allows to predict mass loss rate solely for small-scale pool fire experiments, since flame radiation heat feedback to the liquid surface was neglected. The study of Tewarson [START_REF] Tewarson | The influence of oxygen concentration on fuel parameters for fire modelling[END_REF] was focused on a steady-state heat balance at the condensed fuel surface with a radiation adjustment through the Spalding number. The work of Orloff [START_REF] Orloff | Froude modelling of pool fires[END_REF] illustrated the application of Froude modelling to the development of a homogeneous fire radiation correlation. Based on the measured radiative heat feedback, the work of Hamins [START_REF] Hamins | A global model for predicting the burning rates of liquid pool fires[END_REF] developed a global approach to predict the mass burning flux for liquid pool fires. In the analytical correlation of Beaulieu [START_REF] Beaulieu | Effect of oxygen on flame heat flux in horizontal and vertical orientations[END_REF], the measured flame temperature is required to quantify the effect of enhanced ambient oxygen concentration on flame heat flux. However, many liquid pool fire scenarios involve fires in confined spaces [START_REF] Merci | Numerical simulations of full-scale enclosure fires in a small compartment with natural roof ventilation[END_REF][START_REF] Wahlqvist | Validation of FDS for large-scale well-confined mechanically ventilated fire scenarios with emphasis on predicting ventilation system behavior[END_REF][START_REF] Beji | Numerical Simulations of a Mechanically-Ventilated Multi-Compartment Fire[END_REF][START_REF] Gay | MAGIC and Code_Saturne developments and simulations for mechanically ventilated compartment fires[END_REF][START_REF] Tang | Experimental study on flame height and temperature profile of buoyant window spill plume from an under-ventilated compartment fire[END_REF]. This problematic is especially encountered in the highly confined nuclear facilities equipped with forced interconnecting ventilation system [START_REF] Prétrel | Pressure variations induced by a pool fire in wellconfined and force-ventilated compartment[END_REF] in order to contain the potential release of radioactive material and avoid dispersion to the outside environment. The situation is even more complex if ventilation is mechanically controlled, and the burning rate can be significantly different from the ones measured in open atmosphere [START_REF] Vilfayeau | Numerical simulation of under-ventilated liquid-fueled compartment fires with flame extinction and thermally-driven fuel evaporation[END_REF]. These differences are mainly caused by air ventilation and heat radiation from hot walls and the hot gas layer. Relatively few attempts have been made of predicting rather than prescribing the burning rates in compartments [START_REF] Novozhilov | Computational fluid dynamics modelling of compartment fires[END_REF][START_REF] Nasr | Fuel mass loss rate determination in a confined and mechanically ventilated compartment fire using a global approach[END_REF]. An empirical treatment of soot formation in the work of Nasr [START_REF] Nasr | Fuel mass loss rate determination in a confined and mechanically ventilated compartment fire using a global approach[END_REF] has a profound influence on the radiation emission with regard to the heat feedback, and consequently, to the burning rate. The liquid pool fire problematic in a confined environment can be separated in several individual processes: during the initial phase, the fire growths as long as it is fuel-controlled; the fire can become limited by the available oxygen with generation of unburnt fuel gases; the fire enters the exhaust phase in a progressively vitiated air enclosure. In a typical ignition scenario, the atmosphere in the extraction duct consists of large uncombusted gases with a concentration generally above the lower flammability limit at elevated temperature. The experimental study of Lassus [START_REF] Lassus | Influence of ventilation on ignition risk of unburnt gases in the extraction duct of underventilated compartment fire[END_REF][START_REF] Lassus | Estimation of species concentration during a fire in a reduced scale room[END_REF] showed that in a highly confined setting with interconnecting ventilation ducts, an extraction duct is an important pathway for the onset of ignition of a flammable mixture of pyrolysis gases and vitiated air with presence of a dilution duct.

Ignition risk is an important concept, especially for establishing evaluation methodologies of a scenario regarding its hazard and adverse impact for fire safety applications. Despite the mechanisms involved in ignition are well known [START_REF] Gavilanes | Hot surface ignition and flow separation, 25 th ICDERS[END_REF], a rigorous definition of situations leading to ignition inside an extraction duct is still vague. This phenomenon generally occurs in conditions where a compartment containing a fire has a very limited fresh air supply, and the fire is considerably ventilation-controlled or extinguished. The aim of this research is to discover if there are critical conditions leading to ignition inside an extraction duct by combining theory and experiment for different fuels and ventilation rates. Quantitative comparisons are made between several computational results and measurements from a liquid pool fire scenario in a confined facility [START_REF] Lassus | Influence of ventilation on ignition risk of unburnt gases in the extraction duct of underventilated compartment fire[END_REF][START_REF] Lassus | Estimation of species concentration during a fire in a reduced scale room[END_REF].

Experimental set-up

The experimental facility and its geometry are shown in Figure 1(a,b,c). The reduced-scale enclosure with a length/height and width of 2 m is equipped with an external ventilation system consisting of two intake ducts and an extraction duct. Ducts have a square section of 0.2x0.2 m 2 . The intake is placed closer to the floor at a height of 0.3 m and the exhaust is placed near the ceiling at a height of 1.7 m. Walls of the enclosure are made of concrete with a thermal conductivity of 1 W/m.K, a density of 2100 kg/m 3 , a specific heat of 0.88 kJ/kg.K, and a thickness of 0.2 m. The stainless-steel circular pan containing heptane or dodecane with a diameter D varying from 23 to 40 cm is placed in the middle of the enclosure, slightly elevated at a height of 0.3 m. Measurements performed include the fuel mass loss rate, fire duration, temperature and chemical species concentrations of gases filling the enclosure. As shown in Fig. 1(b,c), the gas temperature in the enclosure is analysed from seven vertical profiles near the fire source and at the extraction/dilution ducts. Each of the seven profiles comprises eight thermocouples positioned at regular intervals over the height of the enclosure. The temperature measurements in the compartment were performed with chromel-alumel thermocouples (type K) of a 0.5 mm wire. The response time of the thermocouples used in our experiment is close to a second by including thermal mass inertia and accumulation of soot particles. Thus, accurate measurement of flame temperature by using the thermocouples is quite difficult due to a multitude of potential errors, including surface reactions, radiation, stem loss, etc. Concentrations of the chemical species, such as O2, CO, CO2, H2 and primary fuel were measured by using a sampling probe connected to a chemical analyser.

Since experiments in full scale are expensive, the numbers of tests are limited. With reducedscale enclosure, more tests may be carried out but the scale reduction must respect several scaling laws adapted to the studied problem. Fire compartment tests have been conducted at a reduced geometric scale, maintaining a constant Froude number, Fr=u 2 /gL where L and u denote the characteristic length and velocity, respectively. Reynolds number is large enough to ensure the turbulence of the flow. The Froude number is then made constant by L u ) between heat release rate ( Q  ) and characteristic length (L).

Moreover, in order to obtain a good similitude between a full scale and a reduced scale compartments, radiative heat flux from wall must not have an influence on heat release rate (HRR). Thus, the experimental fire power in the reduced scale enclosure with a volume of 8 m 3 should be lower than 130 kW. Such reduced scale enclosure corresponds to a full scale one with a volume of approximately 100 m 3 and a HRR of 1 MW [START_REF] Prétrel | Pressure variations induced by a pool fire in wellconfined and force-ventilated compartment[END_REF]. 1a) 3D view of the computational domain and coordinate system 1b) Measurement positions from the side (x, z) view 1c) Measurement positions from the top (x, y) view Figure 1. Scheme of the mechanically ventilated enclosure fire with a connection to an exhaust system

Theoretical analysis

Figure 1a) is a picture of 3D view of the computational domain which consists of four rectangular meshes connected to an enclosure. The coordinate system and the reduced scale enclosure geometry are also shown in Figure 1a). Advanced fire physics model, which is the subject of the current work, requires state-of-the-art submodels (combustion, multidimensional participating radiation, soot formation, heat transfer, liquid fuel vaporization, etc.) which are coupled with the flowfield governing momentum solution. The basis of the analysis is the conservation equations of mass, momentum, energy and species, a set of three-dimensional elliptic, time-dependent Navier-Stokes equations. Turbulence is modelled using a Smagorinsky sub-grid scale model in a Large Eddy Simulation. The precise formulation of the differential equations describing the model and the numerical technique can be found in FDS user guide [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF].

Note that in the version 5 or 6 of FDS [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF], the Stefan problem model is used for the liquid evaporation rate, which involved only mass transfer, since it was assumed that the liquid surface temperature was a known parameter. Moreover, the empirical parameter as soot yield is used for soot formation, which is well known for well-ventilated fires (for example, 0.042 for dodecane and 0.037 for heptane), but cannot be applied to under-ventilated enclosure fires. For a heavily sooting heptane or dodecane fire, the radiation feedback from the hot gas layer to the liquid-vapour interface is significantly affected by the soot production. In the current work, the proposed liquid evaporation model and soot one vary in complexity. In order to properly calculate the evaporation rate of liquid fuel, a classic principle of smoke point for soot formation and the liquid evaporation model in combustion environments were implemented in FDS5 for performing this study. Currently, implementation of the same soot and liquid evaporation models in FDS6 is in progress, and this will be the subject of future study and publications.

Evaporation rate of liquid fuel

For a liquid fuel, if the concentration of fuel gas in the flowing gas is less than the concentration of fuel at the liquid-vapor interface, a driving force for mass transfer exists and species fuel will diffuse from the liquid-gas interface to the freestream flow. In combustion environments, the freestream gas temperature, Tg, is much greater than the liquid boiling point, the surface temperature, Ts, is nearly equal to but slightly less than the liquid boiling point. Physically, heat from the flame to the liquid surface supplies the energy necessary to vaporize the liquid fuel, and the fuel vapor then diffuses from the liquid surface into the freestream reacting flow. Moreover, for a mechanically ventilated enclosure fire, the ventilation flow over the liquid surface steepens concentration and temperature gradients, and hence, increases mass-and heattransfer rates at the liquid surface, implying that convection enhances liquid vaporization rate. The film theory approach is used to incorporate convection in the liquid surface in keeping with our desire for simplicity. Mathematically, the overall conservations of mass and energy for this system can be integrated for determining the mass flux of liquid fuel [START_REF] Kanury | Introduction to Combustion Phenomena[END_REF], as follows,

) 1 B ln( Nu D m " F      ( 1
)
where  is the gas density, D the mass diffusivity and  the convective length scale. Physically, the Nusselt number, Nu, is the dimensionless temperature gradient at the liquid surface, and the following correlation is recommended to evaluate it.

Re Pr m Nu

n 3 / 1  (2)
Where Pr is Prandtl number, and

    u Re
denotes the local Reynolds number calculated from the local velocity u and viscosity  . The empirical constants are given [21] as m=0.037 and n=4/5 for the Reynolds number beyond 3x10 5 , and m=0.664 and n=1/2 for Re below that value. The B denotes the mass transfer number, it is defined as,

) T T ( C L ) T T ( C Y H B 0 s pl v s g p 2 O c O / F       (3)
where O / F  is the stoichiometric fuel/oxygen ratio, Hc the heat of combustion, Cpl the liquid specific heat, Cp the gas specific heat, Lv the fuel latent heat, and T0 the liquid initial temperature. The liquid evaporation rate via the number B depends on the local oxygen concentration, 2 O Y , in a progressively vitiated air enclosure. The convective length scale  , in Eq.( 1) is attached to the mesh size of the computational nodes immediately adjacent to a liquid surface. The Reynolds (Re) and the mass transfer (B) numbers are also dependent on the same mesh size via the thermo-physical properties, the oxygen mass fraction and the temperature in the flowing gas. Much more detailed information about the thermo-physical and combustion properties of the liquid fuel is provided in Table 1 for heptane and dodecane [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF][START_REF] Kanury | Introduction to Combustion Phenomena[END_REF]. Energy is conserved at the liquid-vapor interface. Heat is transferred from the gas to the liquid surface. Some of this energy goes into heating the liquid, while the remainder causes the phase change, as,

v " F " pyro L m q    (4)
This equation can be used to calculate the net heat transferred to the interface if the evaporation rate is known. The liquid fuel is assumed to be thermally-thick, a one-dimensional heat conduction equation for the material temperature is solved. The surface temperature, Ts, of an evaporating liquid is affected by gains and losses of the heat at the interface :

q q q dn T d " pyro " rad " conv s         (5)
Here,  is the thermal conductivity of condensed fuel. The Couette flow is assumed to prevail near the wall surface, and the convective heat feedback q " conv  , is calculated from a wall function [START_REF] Djilali | Calculation of convective heat transfer in recirculating turbulent flow using various near-wall turbulence models[END_REF] far away from the wall for viscous effects to be negligible.

             P ) y E ln( 1 Pr k C C ) T T ( q 2 / 1 4 / 1 p s g " conv  (6)
Here  C and E are the constants in logarithmic law of the wall,  is the von Karman constant, Pr the Prandtl number, y  the nondimensional distance from the wall and P an empirical function defined by Djilali [START_REF] Djilali | Calculation of convective heat transfer in recirculating turbulent flow using various near-wall turbulence models[END_REF]. Flame radiation flux, q rad  " , over the liquid fuel surface is computed from a discrete representation of the radiative intensity which is obtained from a radiative transfer equation [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF].

Soot formation

In fire plumes, the effect of soot production on radiation is significant via a mean absorption coefficient in a grey medium [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF]. For simplicity, six bands are selected to give an accurate representation of the most important radiation bands of CO2 and H2O in addition to the soot formation. For the calculation of the grey or band-mean gas absorption coefficient, a narrowband model (RadCal) has been implemented in FDS [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF]. Soot production is a highly complex subject due to the spatially-varying formation and oxidation processes in addition to the influences of turbulent fluctuations, temperature and fuel type. Nevertheless, a number of researchers [START_REF] Leung | A simplified reaction mechanism for soot formation in nonpremixed flames[END_REF][START_REF] Moss | Modelling soot formation and burnout in a high temperature laminar diffusion flame burning under oxygen-enriched conditions[END_REF][START_REF] Beji | Determination of soot formation rate from laminar smoke point measurements[END_REF] have had some success in identifying factors which allow simplified analysis. The current model is based on a classic principle of a Laminar Smoke Point (LSP) [START_REF] Beji | Determination of soot formation rate from laminar smoke point measurements[END_REF], to relate soot production to material properties. A fuel's smoke point is the maximum height of a laminar flame burning in air at which soot is not released from the flame tip.

A global soot formation model is incorporated into a flow calculation in a convection-diffusion equation for the soot mass fraction, Ys.

                        s j s t t j j s i s x Y Sc x x ) Y u ( t Y (7)
The soot production rate is written as :

                ) Z , 0 Z ( o ) Z , Z Z ( o so c so f s     (8)
Two mixture fraction limits delimit the soot formation and oxidation regions. The incipient mixture fraction is Zc=0.15, and the mixture fraction threshold where soot oxidation starts is Zso=0.1. Soot formation is assumed to be controlled by second-order homogeneous gaseous reaction processes, and thus, is expressed as a function of the mixture fraction, Z, and gas temperature, T :

) T / T exp( T Z 1 Z Z A st st 2 f f                (9)
Here the temperature exponent 25 . 2   and activation temperature K 2000 T   are assigned. The parameter to differentiate the sooting behaviour of different fuels is the pre-exponential factor, Af, determined as 2.9x10 -5 and 3.1x10 -5 , for heptane and dodecane, respectively. This parameter is reversely proportional to the measured smoke point height [START_REF] Beji | Determination of soot formation rate from laminar smoke point measurements[END_REF].

The soot oxidation in Eq.( 8) is assumed to proceed through a single reaction step,

  2 s O C CO2 (10)
The soot oxidation is considered as a surface-area dependent mechanism, and its rate is evaluated from an Arrhenius expression for laminar flame [START_REF] Beji | Determination of soot formation rate from laminar smoke point measurements[END_REF]. In turbulent flame, soot oxidation can be significantly enhanced due to turbulence interactions. There remain some approximations by assuming that the mixing time in sub-grid scale is the limiting mechanism for soot oxidation, and its specific rate is expressed by the following EDC approach [START_REF] Magnussen | The eddy dissipation turbulence energy cascade model[END_REF] :

) T T ( H ) Y , Y min( dt Y d lim eav 2 O s mix s O            ( 11
)
where  denotes the stoichiometric coefficient for burning 1 kg of soot. The source term is multiplied by a Heaviside unit step function Heav(T-Tlim), which is zero when its argument is negative (T< Tlim) and 1 when it is positive (T> Tlim). This implies that soot oxidation occurs as long as the local temperature is beyond a critical value of Tlim=700 K. Note that such model contains no chemically kinetic mechanism to suppress homogeneous soot production by O2.

Assessment of an ignition risk

It is assumed that the combustion proceeds via two reaction steps :

O H 2 n CO m O 4 n 2 m H C 2 2 n m           (12) CO O 2 1 CO 2 2   (13)
The combustion rate in turbulent regime occurring at resolved scales is controlled by the eddy mixing rate. The local reaction rates of fuel and CO are calculated from an Eddy Dissipation Concept [START_REF] Magnussen | The eddy dissipation turbulence energy cascade model[END_REF].

) Y Y ( H ) s Y , Y min( dt Y d lim , 2 O 2 O eav 2 O i mix i i           ( 14
)
where s denotes the stoichiometric coefficient and Yi the fuel/CO mass fractions. The key timescale, mix , is supposed to be related approximately to the mixing time. This is based on the local state of the flow field associated to the processes of diffusion and subgrid-scale advection [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF]. In the expression ( 14), the source term is multiplied by a Heaviside unit step function, Heav(YO2-YO2,lim), which is zero when its argument is negative (YO2<YO2,lim) and 1 when it is positive (YO2>YO2,lim). This implies that flame extinction occurs once the local oxygen concentration is below a critical value, YO2,lim. The critical value is evaluated from a control volume with a bulk temperature Tm and a specific heat Cp in addition to the adiabatic flame temperature Tf, as :

  o m f p lim , 2 O H T T C Y    (15)
Here, Ho  equals to 13100 kJ/kg, corresponding to the amount of energy released per unit mass of oxygen consumed. This model shows also the feasibility for simulations of an ignition inside the extraction duct in closed, air vitiation environment. For example, when the fire has been established for sufficiently long, the elevated temperature of the hotter smoke layer near the ceiling contributes to a reduction in the critical value of the oxygen concentration. An ignition inside the extraction duct can occur if the local oxygen concentration is above the critical value due to a return of air from the dilution duct after the fire extinction in vitiated air enclosure. Note that such ignition model contains no chemically kinetic mechanism which is temperaturedependent. Thus, the time delay for ignition of the unburnt fuels cannot be accurately determined.

Due to lack of specie as H2 in the current combustion model, its concentration is derived from the conservation of the two chemical species, such as CmHn and CO, as the following relation [START_REF] Lassus | Estimation of species concentration during a fire in a reduced scale room[END_REF]:

         n m 2 H C H CO ( 16
)
The aim of this study is to verify if the auto-inflammation risk occurs when the unburnt fuel concentration is beyond the Low Flammability Limit (LFL) at the point of Auto-Ignition Temperature (AIT) [START_REF] Babrauskas | Ignition handbook[END_REF]. The LFLi of each fuel and the LFL of gas mixtures are determined as a function of the molar fraction Xi of each fuel and the gas temperature with the following equations:

          0 0 0 i i T 1300 T T 1 ) T ( LFL ) T ( LFL ( 17
) 1 i i i ) T ( LFL X 100 ) T ( LFL           ( 18
)
where i denotes the fuel type. The values of the AIT and LFL at T0=25°C [START_REF] Babrauskas | Ignition handbook[END_REF] for the four fuel species are summarized in Table 2. Note that the concentration of unburnt gas like H2 is used only for determining approximately the Low Flammability Limit (LFL), and has no influence on the prediction of the ignition risk.

Results and discussion

In LES as used in FDS, turbulence is modelled with an eddy viscosity attached to the grid size as a filter width. The convective length scale used in the liquid evaporation model is also attached to the mesh size. Globally, the numerical model uses the quantities that are mesh dependent. Choice of the grid size is guided by the smallest characteristic length of the liquid pool fire of 23 cm [START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF]. A structured mesh with a spatial resolution of 5 cm for the liquid pans of 23 cm and 40 cm is first employed, giving reasonable burning rate predictions. The calculations were performed using a grid resolution, 40 x 40 x 40, for the enclosure with a length/height and width of 2 m. The ducts have a square section of 0.2x0.2 m 2 with 4 x 4 cells.

The extraction duct has a length of 1.1 m with 22 cells, and the dilution duct has a length of 2.5 m with 50 cells. The measured mass loss rate is used for activating the fire at the beginning of the simulation during 100 s. The simulated physical time is about 2000 s in transient mode with a time-step of about 10 -3 s. In the current simulation, the computational domain consists of multiple meshes which can be treated with 16 processors through parallel processing of a Linux cluster with a CPU time in the order of 2 days. Refining the mesh size from 5 cm to 2.5 cm changes slightly the results. With each halving of the grid size, the time required for the simulation increases by a factor of 2 4 =16 (a factor of two for each spatial coordinate, plus time).

The coarse grids used in the compartment fire simulations are adequate. This can be attributed to the fact that the compartment quickly fills with smoke, reducing the relative importance of the direct flame heat flux prediction. The layered structure in a compartment fire can be resolved using significantly fewer grid points compared to the structure of the flame. We focus on the chemical species and the gas temperature in transient mode mainly at the entrance of the extraction duct for assessing the ignition risk there.

Mass loss rates of heptane and dodecane were registered in the enclosure at various ventilation conditions, corresponding to 3 and 5 Air Change Per Hour (ACPH). The theoretical HRR inside the enclosure is derived by multiplying the measured mass loss rate by the energy released per kilogram of fuel completely consumed. Two fire regimes, such as well-ventilated and underventilated fires, as a function of ACPH can be distinguished. The typical trend of the HRR for heptane and dodecane with different boiling point, latent heat, etc. is described in Figs. 2(a-e).

For the heptane pan of 23 cm (cf. Fig. 2a,b) and dodecane pan of 30 cm diameter (cf. Fig. 2d) at 3 or 5 ACPH, the oxygen concentration initially present in the enclosure and the one supplied by mechanical ventilation entrains a sufficiently ventilated fire. For the heptane pan of 23 cm, the increasing amount of oxygen entering the enclosure contributes to an increase of HRR from 35 kW at 3 ACPH (cf. Fig. 2a) to 50 kW at 5 ACPH (cf. Fig. 2b). The model correctly predicts the HRR as long as the fire is well ventilated, following the trend of the theoretical HRR because the reaction is almost complete. For the dodecane pan of 30 cm (cf. Fig. 2d), the HRR rises progressively up to a peak value of 70 kW. The HRR is over-predicted as compared to the theoretical one with an error below 15% as long as the fire becomes slightly under-ventilated during the fire growth period.

Burning heptane pan of 30 cm (cf. Fig. 2c) or dodecane pan of 40 cm (cf. Fig. 2e) leads to underventilated fire. Evolution of the predicted and the theoretical HRRs can be said to follow three main stages : 1) the initial growth phase, in which burning is fuel-controlled with a stable flame; 2) the fully developed, post-flashover phase, in which burning is ventilation controlled with an unstable flame; and 3) the decay phase, in which burning returns to fuel-controlled one before extinction is achieved with burnout of the fuel load. As long as the fuel-controlled fire regime is maintained during the initial phase, there is a good fit between the predicted HRR and the theoretical one derived from the mass loss rate. The dodecane pan of 40 cm at 5 ACPH conducts to a sharp increase of the HRR to 100 kW at the initial phase. Changing dodecane by heptane would change the fire dynamics, specifically during the initial phase (around 150 s). Flashover is clearly identified by a rapid increase of HRR from 50 to 150 kW for the heptane pan of 30 cm. Starting from 200 s, oxygen concentration initially present and supplied by mechanical ventilation becomes insufficient to maintain an intensive combustion; the fire becomes progressively under-ventilated with an accumulation of unburnt gases. Once the hotter smoke spreads towards the liquid base, the lowed oxygen vitiation induces an unstable flame due to the ignition/extinction of the liquid fuel pan. Oscillations of the HRR observed experimentally due to an unstable flame in under-ventilated conditions are apparently not well captured by the model with a discrepancy up to 50%. It should be noted that for the tests, the liquid fuel was completed with 10 cm-height of water in the pool, and the depth of fuel added was 10 cm-height.

The HRR is more gradual in the simulations than in the experiments because the liquid is treated as a solid and the evaporation model is applied on a cell by cell basis. This kind of modelling allows the pool to burn out in the middle before all fuel is consumed. In the experiments, the flowing liquid would remain as a large burning surface until the fuel is consumed. Convective motions inside the liquid are likely to be important in explaining the experimental HRR profiles. The one-dimensional heat transfer model does not seem to accurately predict the temperature distribution within the liquid. Comparison of the numerical results to the measured oxygen concentration at the entrance of the extraction duct is presented in Figs. 3(a-e). The first situation includes well ventilated fires for the heptane pan of 23 cm diameter (cf. Fig. 3a,b). During the initial fire growth stage, there is sufficient oxygen available to maintain a stable flame attached to the liquid surface and a good agreement between the prediction and the experiment is obtained. Starting from 800 s, the oxygen starvation begins for an oxygen concentration of around 11% and the oxygen-lean/fuelrich hot upper layer is being formed near the ceiling. For the dodecane pan of 30 cm diameter (cf. Fig. 3d), the measured oxygen starvation begins from 1400 s, and the predicted oxygen concentration is lower than the measured one. In the numerical simulation, starting from 250 s, oxygen is quickly consumed due to the excessive pyrolysis products in the vicinity of the fire source, resulting in a quick oxygen starvation at the extraction duct. This highlights the shortcoming of the use of a fast combustion model, irrespective to the chemical kinetic depending on the gas temperature. At 5 ACPH, for the heptane pan of 30 cm (cf. Fig. 3c) and the dodecane pan of 40 cm (cf. Fig. 3e), the fire becomes very under-ventilated with oxygen concentration around 7%; the unstable flame takes place and the fire finally stops due to insufficient amount of oxygen with a concentration of 5%. When the fire extinction occurs, the rise of the O2 concentration at the entrance of the extraction duct is mainly attributed to an accumulation of oxygen supplied by mechanical ventilation. During the fire decaying phase, starting from 1200 s, the prediction follows approximately the experimental trend and is better for the dodecane pan. The predicted and measured carbon monoxide, hydrogen and primary fuel concentrations at the entrance of the extraction duct for the dodecane pan of 40 cm are analysed in Figs. 4(a-c).

Occurrence of an auto-ignition in this case was identified experimentally. The first period to 200 s, corresponds to sufficiently ventilated conditions with a low carbon monoxide production (cf. Fig. 4a), because there is sufficient oxygen available for its oxidation into CO2. The underventilated condition takes place for an oxygen concentration of around 10% (cf. Fig. 3e) in the second period between 250 and 750 s, and carbon monoxide production remains the more important. Carbon monoxide production reaches a maximum in the last period around 1200 s in the very under-ventilated conditions for an oxygen concentration of around 7% (cf. Fig. 3e). This is attributed to the excess combustible gas from pyrolysis of the liquid fuel enhanced by the relatively high temperature for many minutes in the vitiated air enclosure. The calculated molar fraction of CO reaches a peak value of 3.5% at the time of 500 s, whereas the measured one reaches a peak value of 2.5% with a time delay of 1200 s.

A correlation is proposed in the literature [START_REF] Lassus | Estimation of species concentration during a fire in a reduced scale room[END_REF] to evaluate the carbon monoxide concentration as a function of the oxygen concentration, which presents three parts as follows:

                                co , MOC 2 O MOC co , MOC 2 O MOC MOC co , MOC 2 O MOC , 2 O MOC 2 O CO X , 0 X ( X X 1 c d X X d ) X , X X ( c X c ) X , X X ( 0 X (19)
Here XMOC represents the Minimum Oxygen Concentration for a nearly complete reaction of a given fuel, and XMOC,co for oxidation of CO to CO2. The empirical constants c and d slightly depend on the fuel type, as given in Table 3. The CO production is zero when the oxygen concentration is beyond XMOC, corresponding to a sufficiently ventilated condition. The range of oxygen concentration between XMOC,co and XMOC implies an under-ventilated condition with a significant CO production due to an incomplete oxidation reaction. The oxygen concentration below XMOC,co (about 7%) results in a maximum CO production, implying a very underventilated condition. A relationship is also proposed in the literature [START_REF] Lassus | Estimation of species concentration during a fire in a reduced scale room[END_REF] to relate the unburnt fuel concentration with the CO one, as follows:

      n mH C 2 CO
(20) The H2 concentration is derived from the conservation of the chemical species as Eq.( 16). Based on the predicted oxygen concentration (cf. Fig. 3e), a trend of the molar fraction of the species as H2, CO and primary fuel, derived from the correlations [START_REF] Lassus | Influence of ventilation on ignition risk of unburnt gases in the extraction duct of underventilated compartment fire[END_REF][START_REF] Zukoski | Fluid dynamics aspects of room fires[END_REF][START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF] is also added in Figs. 4(a-c). As compared with the measurement, the correlation ( 16) for the hydrogen concentration is with acceptable accuracy, while the correlations [START_REF] Zukoski | Fluid dynamics aspects of room fires[END_REF][START_REF] Mcgrattan | Fire Dynamics Simulator-Technical Reference Guide[END_REF] under-estimate the CO and primary fuel concentrations. The difference between the prediction, correlation and experiment for the amplitudes and the temporal variation of chemical species originates from the inherent complexity in chemical reaction.

4a) Carbon monoxide concentration within 40% error 4b) Hydrogen concentration within 2% error 4c) Primary fuel concentration within 80% error Figure 4. Comparison between the calculated and the measured chemical species concentrations at entrance of the extraction duct with a discrepancy varying from 2% to 80% for dodecane pan size of 40 cm at 5 ACPH An ignition represents very complex chemistry and physical processes, there is still a lack of knowledge for complete understanding of such phenomenon. Globally, issues involved for occurrence of auto-ignition near the extraction duct are amount of accumulated unburnt volatiles above LFL, gas temperature above 350°C, oxygen concentration above 10%, and phenomena leading to fire extinction with an oxygen concentration below 5% in the enclosure. As illustrated in Fig. 5a for the dodecane pan of 40 cm at 5 ACPH, starting from 250 s, a stratified hotter unburnt fuels layer with a concentration beyond the Lower Flammability Limit (LFL) is formed at entrance of the extraction duct. Analyse of the predicted and measured gas temperature at the entrance of the extraction duct is performed in Fig. 5b in addition to the global equivalence ratio, as the expression, m / s m

A F    
where mF  denotes the fuel supply rate (kg/s), mA  the mass inflow rate of air (kg/s), and s stoichiometric coefficient. In the early stages of a fire, the gas temperature reaches the Auto-Ignition Temperature (about 220°) of the primary fuel (dodecane or heptane, see Tab.2). It seems that this temperature level is not high enough for triggering an auto-ignition of the mixture of unburnt gases (hydrocarbons, CO, H2) and air inside the extraction duct. However, we lack the ability to accurately quantify the auto-ignition temperature of a mixture of unburnt fuel and air through bench-scale experiments, which is chemical composition-dependent. With a long time delay of about 1000 s, the energy released per mass of oxygen consumed allows to raise the smoke temperature above 350°C, which seems high enough for an auto-ignition of a mixture of the unburnt gases and air. However, during this stage, the large vaporized fuel due to enhanced heat transfer does not completely contribute to the heat release, thus forming significant unburnt gases with a concentration considerably higher than LFL. Consequently, there is insufficient oxygen available near the ceiling for triggering the ignition. Occurrence of flame extinction in vitiated air enclosure with an oxygen concentration below 5% makes a sudden decrease of the pressure level inside enclosure due to cooling effects. This induces a sudden supply of fresh air from dilution duct characterized by a sharp increase of oxygen concentration, which can be identified from the evolution of the oxygen (cf. Fig. 3e) at the extinction point of about 1250 s. This provides a sufficient oxygen concentration with a molar fraction of about 10% for triggering the ignition of a hotter fuel-air mixture with a temperature above 350°C near the extraction duct. Note that the predicted ignition delay is about 1150 s, which is shorter than the ignition time of about 1250 s in the experiments [START_REF] Lassus | Influence of ventilation on ignition risk of unburnt gases in the extraction duct of underventilated compartment fire[END_REF]. Besides, by using the thermocouples, accurate identification of a typical flame temperature in space and time during the unburnt gas ignition is quite difficult. This may be attributed to the discrepancy between the predicted temperature peak of 550°C and the measured one of 420°C. Evolution of the temperature of unburnt gases (cf. Fig. 5b) as a function of  indicates that the equivalent ratio higher than 1.5 represents a set of dangerous conditions when the fire has been established for sufficiently long, as any return of air from dilution duct could lead to spontaneous ignition near the extraction duct after extinction in enclosure.

The empirical, numerical and experimental approaches suggest that the ignition phenomena near the extraction duct can be identified by a sharp decrease of the molar fraction of unburnt fuels towards a stoichiometric fuel-air mixture, and an elevated temperature peak. Evolution of the molar fraction of unburnt fuels for the dodecane pan of 40 cm at 3 ACPH is presented in Fig. 6. It is found that the decreasing amount of air entering the enclosure at 3 ACPH contributes to a significant increase of the molar fraction of unburnt fuels near the extraction duct. With a time delay of 1600 s, the predicted molar fraction of unburnt fuels decreases sharply towards LFL due to air dilution. This implies that for a given dodecane pan of 40 cm, a decrease of ACPH from 5 to 3 contributes to an increase in the delay time for occurrence of an ignition, corresponding approximately to the experimental trend. The heptane pan of 30 cm (cf. Fig. 7) at 3 ACPH contributes to an important formation of the stratified unburnt fuels layer at the extraction duct with a predicted time delay of about 1300 s for occurrence of the ignition there. Such auto-ignition was identified experimentally by visual identification of fire with a probability of 50% due to the heat leakage through the walls of the experimental facility. When the compartment is more heat-tight by using an insulating material, the auto-ignition occurs for each fire tests. The numerical simulation and the empirical correlation are qualitatively promising for the risk assessment of unburnt gases ignition, but identification of the ignition time delay and location controlled by the fire scenario is within 15-30% error. 5a) Unburnt fuels concentration within 5% error between prediction and measurement 5b) Gas temperature within 20% error between prediction and measurement Figure 5. Risk assessment of unburnt gases ignition near the entrance of the extraction duct for dodecane pan of 40 cm at 5 ACPH Figure 6. Comparison between experiment and prediction for the molar fraction of unburnt fuels within 30% error for dodecane pan of 40 cm at 3 ACPH Figure 7. Comparison between experiment and prediction for the molar fraction of unburnt fuels within 60% error for heptane pan of 30 cm at 3 ACPH The heptane pan of 23 cm (cf. Fig. 8a,b) and the dodecane pan of 30 cm (cf. Fig. 8c) correspond to well ventilated condition with a global equivalent ratio lower than unit during the fire. The reaction is almost complete in such situation without ignition risk near the extraction duct. For heptane pan of 23 cm at 3 ACPH (cf. Fig. 8a), the gas temperature at the entrance of the extraction duct (TE1, cf. Fig. 1c) increases progressively during the fire growth period, reaching a plateau with a value of 200°C in a quasi-steady period. Similar trend is found for the same pan at 5 ACPH, but the gas temperature reaches a peak value of 230°C due to the enhanced convective transport. A good agreement between the predicted and the measured gas temperature is found for the heptane pan of 23 cm. For the dodecane pan of 30 cm at 5 ACPH (cf. Fig. 8c), the gas temperature increases monotonously up to fire extinction. The heptane pan of 30 cm at 5 ACPH (cf. Fig. 8d) corresponds to under-ventilated fire with a global equivalent ratio higher than unit. Such under-ventilated condition induces an unstable flame due to lowered oxygen vitiation in the enclosure, characterized by a large oscillation of the gas temperature varying from 250°C to 350°C. 8a) Heptane pan of 23 cm at 3 ACPH corresponding to a sufficiently ventilated fire within 5% error 8b) Heptane pan of 23 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 5% error 8c) Dodecane pan of 30 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 35% error 8d) Heptane pan of 30 cm at 5 ACPH corresponding to an under-ventilated fire within 30% error Figure 8. Comparison between the calculated and the measured temperature at the entrance of the extraction duct with a discrepancy varying from 5% to 35% as a function of the fuel type As an illustration, the gas temperature in the dilution duct (TD7, cf. Fig. 1c) is presented in Figs. 9(a-e) for heptane and dodecane pans. The heptane pan of 23 cm (cf. Fig. 9a,b) and the dodecane pan of 30 cm (cf. Fig. 9d), correspond to a well ventilated condition with a gas temperature below 200°C inside the dilution duct. An increase of heptane pan size from 23 (cf. Fig. 9b) to 30 cm (cf. Fig. 9c) leads to a rise of gas temperature from 120°C to 230°C due to accumulation of the hotter gas inside the dilution duct, following the experimental trend. Both the prediction and the experiment indicate that the onset of auto-ignition inside the extraction duct for the heptane pan of 30 cm (cf. Fig. 9c) and the dodecane pan of 40 cm (cf. Fig. 9e) results in the rather high temperature of about 250-300°C even in the dilution duct. 9a) Heptane pan of 23 cm at 3 ACPH corresponding to a sufficiently ventilated fire within 5% error 9b) Heptane pan of 23 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 10% error 9c) Heptane pan of 30 cm at 5 ACPH corresponding to an under-ventilated fire within 30% error 9d) Dodecane pan of 30 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 10% error 9e) Dodecane pan of 40 cm at 5 ACPH corresponding to an under-ventilated fire within 16% error Figure 9. Comparison between the calculated and the measured gas temperatures inside the dilution duct with a discrepancy varying from 5% to 30% as a function of the ventilation condition or fuel type Comparison of the numerical results to the measured local gas temperature in the vicinity of the fire source (TL1_5, cf. Fig. 1b,c) is performed in Figs. 10(a-e) for heptane and dodecane pan size varying from 23 cm to 40 cm at 3 or 5 ACPH. It seems that evolution of the gas temperature depends strongly on the compartment fire dynamics regime, such as well-or under-ventilated fire. In well ventilated condition as for heptane pan of 23 cm (cf. Fig. 10a,b), the fire behaved in a very consistent manner and the temperature remains relatively high with a value of 500°C for many minutes. An increase of the ACPH from 3 to 5 contributes to a reduction of 50°C in the gas temperature. The model is found to under-predict the temperature as compared to the experimental data at low ventilation rate of 3 ACPH, whereas to agree with measurement at 5 ACPH. Both the experimental data and the prediction show that for a given ACPH, an increase of pan size from 23 (cf. Fig. 10b) to 30 cm (cf. Fig. 10c) contributes to an increase of gas temperature from 500°C to 800°C due to enhanced fire plume dynamics. For the dodecane pan of 30 cm at 5 ACPH (cf. Fig. 10d), the gas temperature reaches sharply a peak point of 700°C during the initial fire growth period due to a considerable increase of the HRR, and then, approaches a plateau in a quasi-steady period. For the dodecane pan of 40 cm (Fig. 10e), the predicted temperature trend corresponds well with the measured one solely during the initial fire growth period. Generally, the model exhibit a more conservative behavior, and the discrepancies between the experimental data and the prediction are mainly attributed to the over-prediction of the HRR in the under-ventilated conditions. 10a) Heptane pan of 23 cm at 3 ACPH corresponding to a sufficiently ventilated fire within 20% error 10b) Heptane pan of 23 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 20% error 10c) Heptane pan of 30 cm at 5 corresponding to an under-ventilated fire within 25% error 10d) Dodecane pan of 30 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 17% error 10e) Dodecane pan of 40 cm at 5 ACPH corresponding to an under-ventilated fire within 50% error Figure 10. Comparison between the calculated and the measured gas temperatures near the fire source with a discrepancy varying from 17% to 50% as a function of the ventilation condition or fuel type

Conclusions

In an engineering context, the calculated heat release rate (HRR), the temperature and the oxygen concentration agree well with the experimental results within 15% error, especially for the maximum values, in over-ventilated conditions. Quality of the agreement between the prediction and the experiment deteriorates in under-ventilated conditions. Oscillations of the HRR observed experimentally due to the ignition/extinction of the liquid fuel pan in underventilated conditions are apparently not well captured by the model with a discrepancy up to 50%. This highlights the shortcoming of the use of a fast combustion model, irrespective to the chemical kinetic depending on the gas temperature. In medium-scale enclosure of 8 m 3 , ignition near the extraction duct can happen for heptane or dodecane pan with a diameter beyond 30 cm, as long as the gas temperature is high enough for auto-ignition. In general terms, comparison between the prediction and the experiment is reasonably good for the occurrence of an ignition, although identification of the ignition time delay and location controlled by the fire scenario is within 15-30% error. In a full scale enclosure with an equivalent ratio higher than 1.5, when the fire has been established for sufficiently long with a temperature above 350°C near the ceiling, there is significant ignition risk of unburnt fuel gases in an exhaust system as long as any return of air from dilution duct occurs. The extinction/ignition criteria delivered in this work can be applied only in the case where the remaining flames as ghosting flame in the enclosure do not exist. With presence of a pilot flame as ghosting flame, ignition of unburnt volatiles near the exhaust system may occur more easily at temperature down to 350°C. Any attempt to draw a general conclusion for all configurations is discouraged due to the uncontrollable fire dynamics which depends strongly on the distribution of the oxygen available in under-ventilated enclosure. The uncertainties in the ignition/extinction criteria are mainly due to our inability to measure detailed chemical species through bench-scale experiments, and other idealizations inherent in such empirical definition.

2a) 2 .

 2 Heptane pan of 23 cm at 3 ACPH corresponding to a sufficiently ventilated fire within 10% error 2b) Heptane pan of 23 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 20% error 2c) Heptane pan of 30 cm at 5 ACPH corresponding to an under-ventilated fire within 50% error 2d) Dodecane pan of 30 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 25% error 2e) Dodecane pan of 40 cm at 5 ACPH corresponding to an under-ventilated fire within 35% error Figure Comparison between the calculated HRR and the theoretical one with a discrepancy varying from 10% to 50% as a function of the ventilation condition or fuel type

3a) 3 .

 3 Heptane pan of 23 cm at 3 ACPH corresponding to a sufficiently ventilated fire within 30% error 3b) Heptane pan of 23 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 25% error 3c) Heptane pan of 30 cm at 5 ACPH corresponding to an under-ventilated fire within 30% error 3d) Dodecane pan of 30 cm at 5 ACPH corresponding to a sufficiently ventilated fire within 18% error 3e) Dodecane pan of 40 cm at 5 ACPH corresponding to an under-ventilated fire within 50% error Figure Comparison between the calculated oxygen concentration and the measured one with a discrepancy varying from 18% to 50% as a function of the ventilation condition or fuel type

Table 1 .

 1 Temperature-independent, thermo-physical and combustion properties of the liquid fuels as heptane and dodecane

	Property	Heptane	Dodecane
	Conductivity (W/m.K)	0.17	0.14
	Density (kg/m 3 )	684	750
	Heat capacity (kJ/kg.K)	2.24	2.21
	Pyrolysis heat, Lv (kJ/kg)	321	256
	Combustion heat, Hc (kJ/kg)	44500	44147
	Boiling temperature (°C)	98	216

Table 2 .

 2 Values of the Low Flammability Limit (LFL) and the Auto-Ignition Temperature (AIT) for the major fuel species

	Parameter	CO	H2	Heptane	Dodecane
	LFL (T0=25°C) 12.5%	4%	1.05%	0.6%
	AIT (°C)	588	520	223	204

Table 3 .

 3 Empirical constants used in the correlation[START_REF] Zukoski | Fluid dynamics aspects of room fires[END_REF] for CO concentration

	Parameter	Heptane	Dodecane
	XCMO	11.55%	11.1%
	XCMO, co	6.25%	6.25%
	c	1.96	1.98
	d	8	8

The work is continuing with the aim of improving the quality of the predicted chemical species concentration by using more complex chemistry reaction kinetics. Besides, effects of the internal liquid-phase circulation on the pyrolysis rate of liquid fuel should be modelled properly by taking into account the enhanced heat transfer within the liquid phase by e.g., lateral convection.


Christopher P Rüger
email: christopher.rueger@uni-rostock.de

Julien Maillard

Johann Le Maître

Mark Ridgeway

Christopher J Thompson

Isabelle Schmitz-Afonso

Thomas Gautier

Nathalie Carrasco

Melvin A Park

Pierre Giusti

Carlos Afonso

Structural Study of Analogues of Titan's Haze by Trapped Ion Mobility Coupled with a Fourier Transform Ion Cyclotron Mass Spectrometer

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

Introduction. Titan, the second largest moon in our solar system, possesses a thick atmosphere mainly composed of nitrogen mixed with a few percent methane. In this gaseous environment, nitrogen radicals are created by, for example, UV radiation from the sun. Their reaction with methane leads to the formation of a thick haze. [START_REF] Israël | Complex organic matter in Titan's atmospheric aerosols from in situ pyrolysis and analysis[END_REF] Because of this particular formation, the study of this fog represents a substantial interest for prebiotic chemistry and planetary sciences. Space missions (Voyager and Cassini-Huygens) provided the first information on the chemical composition of this haze. They revealed the presence of mainly NH 3 and HCN chemical motif. However, due to technical limitations of the on-boarded instruments, the exact composition of this dust remains mostly unknown. [START_REF] Vinatier | Analysis of Cassini/CIRS limb spectra of Titan acquired during the nominal mission II: Aerosol extinction profiles in the 600-1420cm-1 spectral range[END_REF] These limitations can be overcome, and further knowledge on the Titan atmosphere can be gained by producing analogs of the haze on earth, socalled tholins. [START_REF] Szopa | PAMPRE: A dusty plasma experiment for Titan's tholins production and study[END_REF] Tholins were investigated by multiple mass spectrometric approaches, such as in coupling gas/liquid chromatography [START_REF] Gautier | Nitrogen incorporation in Titan's tholins inferred by high resolution orbitrap mass spectrometry and gas chromatography-mass spectrometry[END_REF][START_REF] Gautier | Development of HPLC-Orbitrap method for identification of N-bearing molecules in complex organic material relevant to planetary environments[END_REF] and various, direct infusion experiments. [START_REF] Somogyi | Organic environments on Saturn's moon, Titan: simulating chemical reactions and analyzing products by FT-ICR and ion-trap mass spectrometry[END_REF][START_REF] Carrasco | Chemical characterization of Titan's tholins: solubility, morphology and molecular structure revisited[END_REF][START_REF] Vuitton | Very high resolution mass spectrometry of HCN polymers and tholins[END_REF][START_REF] Maillard | Comparison of soluble and insoluble organic matter in analogues of Titan's aerosols[END_REF] Very recently, ion-mobility spectrometry coupled with a time-offlight mass spectrometer (IMS-TOF MS) was performed to obtain structural and isomeric information. [START_REF] Maillard | Tridimensional chemical structure of the soluble organic matter in analogues of Titan's aerosols[END_REF] By comparison with common structural elements, several structural motifs could be excluded, and an overview of potential shapes was allowed. However, the conclusions of this and other previous investigations revealed limitations due to the restricted resolution of the mass spectrometer and the extreme complexity of tholins samples. This previous investigation was limited to a relatively narrow mass range focusing on small constituents. Commonly, far heavier species are detected in tholins; thus, a significant proportion of the structural information might be lost.

The present work was motivated to improve on the prior limited view on the molecular structure of tholins by using higher resolution mass and mobility analyzers -namely trapped ion mobility spectrometry (TIMS), to Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS). FTICR MS with its unbeaten mass accuracy and resolving power serves as the ideal analyzer for the ultra-complex tholins samples. TIMS-FTICR MS was recently deployed for the description of petroleum and other complex natural mixtures. [11][START_REF] Benigni | Analysis of Photoirradiated Water Accommodated Fractions of Crude Oils Using Tandem TIMS and FT-ICR MS[END_REF][START_REF] Lanucara | The power of ion mobility-mass spectrometry for structural characterization and the study of conformational dynamics[END_REF] To the best of the author's knowledge, this is the first proof of principle study addressing a planetary science subject. As an example, the soluble fraction of a tholins sample is investigated by electrospray ionization (ESI) coupled to TIMS-FTICR MS. The unique information derived by ion mobility separation -i.e., such as mobility peak position, width, and shape, provides more detailed structural insight than mass spectrometry alone. [START_REF] Lanucara | The power of ion mobility-mass spectrometry for structural characterization and the study of conformational dynamics[END_REF][START_REF] Tose | Coupling trapped ion mobility spectrometry to mass spectrometry: trapped ion mobility spectrometry-time-of-flight mass spectrometry versus trapped ion mobility spectrometry-Fourier transform ion cyclotron resonance mass spectrometry[END_REF] Experimental Tholins were produced according to the PAMPRE process. [START_REF] Szopa | PAMPRE: A dusty plasma experiment for Titan's tholins production and study[END_REF] Briefly, after a few hours of cold plasma discharge of a nitrogen/methane mixture, a brown powder, the tholins sample material, was recovered. For electrospray analysis, the sample was dissolved in methanol, stirred and filtered, extracting the soluble fraction. Directly prior analysis, a water/methanol (50/50 v-%) mixture was prepared. A mixture containing phosphazene derivatives (Agilent Tuning Mix) was used for collision-cross section calibration.

Mobility-mass analysis of the tholins soluble fraction was performed by a TIMS 12 T FTICR MS. This prototype instrument was equipped with an electrospray ionization source, and spectra were recorded in positive ion mode (5 kV, sample flow rate 120 µL/h). The nature of tholins referred to be as HCN-polymer derivative with a certain degree of aromaticity (see S11 for comparison to previous laser desorption ionization data) allow ionizing the major proportion of the tholin soluble fraction by positive mode ESI.The trapped ion mobility cell replaced the standard inlet funnel. Briefly, reduced mobility (K 0 ) was scanned from 1.21 -4 to 3.37 -4 m 2 s 1 V 1 in 72 steps. Absorption mode spectra were recorded with a dynamically harmonized ICR cell and a 0,7 s transient (full-sine apodization, one zerofill). Consequently, a mass resolving power of over 500,000 at m/z 400, was achieved.

After mass calibration utilizing characteristic CHN homolog rows, each scan of the time-resolved data was peak picked (S/N 9) and exported. The exported mass spectra were processed by self-written MATLAB routines. The extracted mobilograms are fitted to an asymmetric Gauss shape, and peak parameter are exported for each individual signal. Finally, elemental compositions were assigned with the following common boundaries for tholins: C 1-50 H 1-120 N 1-15 O 0-3 S 0 . A mass error of 1 ppm and only protonated species were considered. The mean assignment error was found to be below 100 ppb. More details on the experimental can be found in the supporting information (S1).

Results and Discussion

The results gave evidence of the high complexity of this artificial planetary science material, and roughly 1,300 elemental compositions could be attributed up to m/z 540. The complexity of tholins was previously pointed out but the previous direct infusion experiments missing the added dimension of mobility separation and, thus, the further structural information. [START_REF] Benigni | Analysis of Photoirradiated Water Accommodated Fractions of Crude Oils Using Tandem TIMS and FT-ICR MS[END_REF] The mass spectral inset in Figure 1 emphasizes the mass spectral complexity. The ultra-high resolving power of the FTICR mass analyzer could fully resolve those close signals. Most critical for the tholins sample was a 2.6 mDa split caused by N 6 versus C 4 H 4 O 2 and a 4 mDa split resulted by N 2 O 2 versus C 5 , requiring at least a resolving power of 300k and 200k at m/z 400, respectively. More importantly, Figure 1 reveals the global view of the ion mobility dimension in combination with the fully resolved mass spectral pattern. Previous work performed with IMS-TOF MS was not able to resolve the increasing spectral complexity at higher m/z-values, and, thus, was focusing on the lower m/z-proportion of the tholin chemical space (Figure 1, red square). [START_REF] Maillard | Tridimensional chemical structure of the soluble organic matter in analogues of Titan's aerosols[END_REF] The TIMS-FTICR MS coupling was able to significantly enlarge the accessible chemical space revealing CCS-values ranging from 70-170 Ų with an intensity-weighted CCS-value of 120 Ų almost in the center of the detected distribution.In an initial attempt to gain insight into tholins structural motif, the global trend of CCS versus m/z can be compared to CCS-values of different characteristic homolog series. S1 and Figure S1.

The global trend of CCS versus m/z can be compared to CCS-values of different characteristic homolog series. This approach is visualized in Figure 1 for the tetraalkylammonium species (TAA) and the polycyclic aromatic hydrocarbons (PAH). Noticeably, neither series agree very well with the observed pattern and moreover an overall slightly flattening of the pattern (decrease of the slope) at higher m/z is revealed. Based on previous molecular level studies on tholins [START_REF] Gautier | Development of HPLC-Orbitrap method for identification of N-bearing molecules in complex organic material relevant to planetary environments[END_REF][START_REF] Carrasco | Chemical characterization of Titan's tholins: solubility, morphology and molecular structure revisited[END_REF][START_REF] Maillard | Comparison of soluble and insoluble organic matter in analogues of Titan's aerosols[END_REF], we hypothesize ramified archipelago-type nitrogen-containing PAHs (N-PAHs) as the primary structural element (Figure S1). Theoretical calculations of the cross-sections for those species, given as blue line in Figure 1, revealed an excellent agreement to the experimentally observed data. This first comparison already reveals for structural information accessible only via TIMS-FTICR MS. The elemental compositions assignments reveal CHN x -class constituents are prevalent, and compositions with up to 13 nitrogen could be found (Ø#N 6.8) in this soluble methanol fraction. This observation is in agreement with previous studies, which highlight the dominant presence of pure CHN x -class constituents. [START_REF] Gautier | Nitrogen incorporation in Titan's tholins inferred by high resolution orbitrap mass spectrometry and gas chromatography-mass spectrometry[END_REF][START_REF] Maillard | Comparison of soluble and insoluble organic matter in analogues of Titan's aerosols[END_REF] Oxidized components (artifact from the rapid oxidation when exposed to Earth atmosphere) were found to be below 15 % of the overall abundance which was an acceptable level, as the focus of this study was to proof TIMS coupled to FTICR MS as a preferable approach for the investigation of extraterrestrial relevant materials. In contrast to the classical van Krevelen diagram visualizing H/C versus O/C, the modified representation utilizing the N/C is ideal for the study of tholins. [START_REF] Gautier | Nitrogen incorporation in Titan's tholins inferred by high resolution orbitrap mass spectrometry and gas chromatography-mass spectrometry[END_REF] In Figure 2 the respective N/C-Van-Krevelen diagram is given for all CHN x -class constituents. The pattern centered close to the respective intensity weighted values of 1.56 and 0.44 for the H/C and N/C, respectively. Species with a nitrogen-number up to equaling the carbon number were found. Noticeably, the peak apex CCS-value as a measure of the mean size of the specific molecular formula is low at the edges of the pattern and increasing towards the central point of the pattern. This behavior is caused by the stepwise addition of building blocks with an average composition of C 2 H 3 N with N/C and H/C similar to the central point. Thus, the start of an isomeric tholin series was found to be rather noncharacteristic covering a broad region space in the van Krevelen diagram, whereas with increasing m/z caused by the addition of C 2 H 3 N-building blocks to the molecular formula results in the size increases and consequently the CCS-value rises towards H/C 1.5 and N/C 0.5. As C 2 H 3 N was identified as an essential building block, the respective Kendrick mass defect diagram can be drawn with the C 2 H 3 N-homolog rows at the horizontal lines (see Figure S2). The correlation pointed out in Figure 1 between m/z and CCS can be seen. Moreover, a less prevailing effect of increasing CCS with increasing KMD-C 2 H 3 N is observed. Thus, different homolog rows might exhibit the same nominal mass but different size (reflected by CCS), which correlates with KMD-C 2 H 3 N. Nonetheless, this effect is weak, and we can conclude, that the size-span of the homolog rows is rather low compared to the increase in CCS with raising m/z. Aside from the CCS, allowing to hypothesize structural aspects, the full-width-at-half-maximum (FWHM) serves as a measure for the isomeric diversity. [START_REF] Farenc | Effective Ion Mobility Peak Width as a New Isomeric Descriptor for the Untargeted Analysis of Complex Mixtures Using Ion Mobility-Mass Spectrometry[END_REF] Due to time-offlight mass spectrometric instrumentation, this approach was previously limited to relatively simple mixtures or low m/z ions. TIMS-FTICR MS with significantly higher mass resolving power and accuracy allows to push these limitations drastically, and Figure 3 visualizes the mobility FWHM versus m/z of the tholins signals. It can be observed that the standard tune mixture FWHM (containing a specific isomer) increases linearly, whereas the tholin signals reveal an apparent flattening of the pattern. In the lower m/z range from 150-350 a linear trend can be found, whereas for the heavier constituents (> m/z 350) a lower increase or eventually at above m/z 400 a near plateau effect is observed. Thus, the isomeric diversity is increasing linearly for the low m/z ions (m/z 150-300). We hypothesize that structural changes due to increased flexibility cause the observed plateau effect of the TIMS FWHM at higher m/zvalues (starting ~ m/z 370). We presume a folding effect, which was previously reported in multiple IMS-MS studies for polymers. [START_REF] Trimpin | Ion mobility spectrometry/mass spectrometry snapshots for assessing the molecular compositions of complex polymeric systems[END_REF][START_REF] Winter | Size dependence of the folding of multiply charged sodium cationized polylactides revealed by ion mobility mass spectrometry and molecular modelling[END_REF][START_REF] Haler | Multiple Gas-Phase Conformations of a Synthetic Linear Poly(acrylamide) Polymer Observed Using Ion Mobility-Mass Spectrometry[END_REF] As tholins are referred to be HCNpolymers with carbon and hydrogen insertion, we could vaguely assume folding of larger tholin species can occur and will lower the isomeric diversity in terms of most compact and largest structure.

Conclusion

The presented study gives a proof of principle for deploying trapped ion mobility spectrometry coupled to Fourier transform ion cyclotron resonance mass spectrometry for analysis in the field of planetary science. Tholins, a highly complex artificial mixture mimicking the products on Titan, could be successfully described on the molecular level by mass spectrometry and on the isomeric level by ion mobility. Thus, IMS serves as a beneficial and complementary separation technique for FTICR MS, in particular for such complex mixtures. We hypothesized structural motif for tholins in the upper m/z-region. Peak shape parameters from the mobilograms are mined to gather additional information, such as the peak width as a measure for isomeric complexity. Future studies will focus on a comparison of different tholins materials, e.g., solubility fractions. The utilization of the ion mobility peak shape for complex mixtures will be further investigated as a promising tool for the structural assessment. In particular, complex mixtures which are far from being resolved by IMS can be approached.

Figure 1 .

 1 Figure 1. Apex collision-cross-section ( TIMS CCS N2 , at room temperature) versus m/z color-coded by abundance. The behavior of the theoretical cross-sections of different structural motif is provided for tetraalkylammonium salt species (TAA, red) and polycyclic aromatic hydrocarbons (PAH -black). A proposed structural motive for the tholins homolog series is presented in blue (archipelago ramified N-PAH). The mass spectrometric excerpt of the nominal mass 436 visualizing the high isobaric complexity. Detailed information on the homolog rows can be found in Table S1 and Figure S1.

Figure 2 .

 2 Figure 2. H/C versus N/C van Krevelen representation of all C x H y N z -class constituents color-coded according to peak apex TIMS CCS N2 -value. A clear center of the pattern can be seen at H/C 1.5 and N/C 0.5 (marked in blue).

Figure 3 .

 3 Figure 3. Full width at half maximum (FWHM) versus m/z colorand size-coded to the summed abundance of the extracted mobilograms. Interestingly, the pattern of the FWHM is flattening towards higher m/z allowing for implication of the isomeric complexity growth. As comparison, the standard mixture values are displayed and interpolated for lower m/z-values (dotted black line). The insert gives the mobilogram for three selected components with a low (blue), a medium (purple) and a large m/z (green).

Acknowledgment

Thanks to the EU for funding via the ERC PRIMCHEM project (No. 636829). This work was supported at Chimie Organique Bioorganique Réactivité Analyse (COBRA) laboratory by the European Regional Development Fund (ERDF) N°31708, the Région Normandie, and the Laboratoire d'Excellence (LabEx) Synthèse Organique (SynOrg) (ANR-11-LABX-0029).


Guillaume David

Marie-Laure Fogeron

Maarten Schledorn

Roland Montserret

Uta Haselmann

Susanne Penzel

Aurélie Badillo

Lauriane Lecoq

Patrice André

Michael Nassal

Ralf Bartenschlager

Beat H Meier
email: beath.meier@ethz.ch

Anja Böckmann
email: a.bockmann@ibcp.fr

Towards structural studies of self-assembled subviral particles: combining cell-free expression with 110 kHz MAS NMR

Keywords: Solid-state NMR, cell-free protein expression, duck hepatitis B virus, subviral particles, proton detection

Viral membrane proteins are prime targets in the combat against infection. Still, their structure determination remains a challenge, both with respect to sample preparation, and the need for structural methods allowing analysis in a native-like lipid environment. Cell-free protein synthesis and solid-state NMR are promising approaches in this context, one with respect to its high potential of native expression of complex proteins, and the other for its ability to analyze membrane proteins in lipids. We here show that milligram amounts of the small envelope protein of the duck hepatitis B virus (DHBV) can be produced using cell-free expression, and that the protein self-assembles into subviral particles. 2D proton-detected NMR spectra recorded at 110 kHz magic angle spinning on < 500 μg protein show a number of isolated peaks with linewidths comparable to model membrane proteins, paving the way for structural studies of this homologous protein to a potential drug target in HBV infection.

Infection with hepatitis B virus (HBV) entails acute or chronic diseases of the liver, the latter often associated with liver cirrhosis and hepatocellular carcinoma. HBV is a spherical enveloped virus with a 42 nm outer diameter [1] that possesses a circular partially doublestranded DNA genome contained in an icosahedral capsid formed by multiple copies the core protein (HBc). It is surrounded by a lipid envelope into which three different HBV surface proteins designated small (S), medium (M) and large (L) hepatitis B surface antigen (HBs) are embedded. One particularity of the virus is that infected cells massively produce subviral particles (SVPs), which are only composed of capsid-less (i.e. empty) virus envelopes, mainly formed by the S protein embedded into a phospholipid membrane derived from the host. [2] The three viral envelope proteins S, M and L differ by their N-terminal domain: in addition to S, M carries the preS2 domain while L carries both the preS1 and preS2 domains. The S protein is the most abundant in both virion envelopes and SVPs, [3] and can form particles on its own. [4] The topology proposed for this protein consists of 4 transmembrane helices and a cytosolic loop as well as an antigenic loop. [5] The protein is a potential drug target for HBV; but while topology models are available, its high-resolution structure has not been determined, as the virion envelope shows heterogeneity as observed by electron microscopy. [6] This manifest variability suggests that in-vitro reconstituted SVPs represent an interesting alternative to virions for structural studies.

To produce the HBs S protein, we chose wheat-germ cell-free protein expression [7][8][9] (Figure S1) and tested the human and duck HBs S protein in this system. Due to its fundamental similarity to HBV, duck HBV (DHBV, see schematic representation in Figure 1a for a representation of the viral particle, as well as SVPs) is an important model for the human virus. [10] The duck hepatitis B virus S protein is similar to the one of HBV, but lacks the cysteine-rich antigenic loop of HBs S, reducing the total size of DHBs S to 167 amino acid residues versus 226 residues for HBs S (see Figure S2 for sequence alignments and Figure 1b for a predicted model of S). While CF HBs S expression still needs further optimization as the yields were rather low and may require the presence of chaperones to keep the protein in solution (data not shown), the DHBV protein expressed well in the presence of mild detergent and assembled spontaneously. Together with its reduced size, this feature makes DHBV SVPs a highly attractive pilot for a structural study by solid-state NMR. Importantly, the recent development of > 100 kHz magic-angle-spinning (MAS) solid-state NMR proton detection techniques, which reduce the requested sample amount by nearly two orders of magnitude, opens the possibility to analyze the protein amounts typically obtained in cell-free expression (vide infra). While > 100 kHz MAS NMR, [11][12][13][14][15] cell-free expression, [16][17][18] NMR of large assemblies [19,20] and of membrane proteins [21,22] have been demonstrated before, we here show that, despite the already high complexity hidden behind every single of these elements, their combination is possible and allowed us to obtain NMR data of DHBV self-assembled SVPs showing suitable resolution and sensitivity. This should lead the way for investigations of these, and similar, large membrane protein assemblies which structures remained intractable.

Cell-free expression of DHBs S was tested in small-scale bilayer reactions (see Material and Methods section in the Supporting Information), where the wheat germ extract (WGE) is overlayed with feeding buffer. [8] The expression level of the protein is good, as can be seen on the Coomassie gels and western blots in which the total reaction, as well as supernatant and pellets fractions were analyzed (Figure 1c). Expression was tested both in the absence and presence of MNG-3 detergent, which we previously identified as a powerful additive for solubilization of membrane proteins and compatible with the cell-free reaction. [23] Indeed, while in the absence of the detergent, the protein was found in the pellet, it is mainly soluble in presence of 0.1% MNG-3. b Membrane topology model of the S protein, with the third helix (in grey) predicted only for the HBV S protein. [5,10] c Expression tests of DHBs S in (analytical) bilayer mode. [8] -, expression without detergent; +, expression in the presence of 0.1% MNG-3. SDS-PAGE Coomassie blue staining and Western blots using In order to analyze the soluble protein fractions, we loaded the supernatant from a larger reaction carried out in a dialysis cassette on a discontinuous 10-60 % sucrose gradient. The protein is mainly detected in the fractions 40 % and 50 % sucrose fractions (Figure 2a), corresponding to a density of 1.17-1.23 g/mL like authentic SVPs, whereas the bulk of nonrelated proteins remains mostly at the top of the gradient. The electron micrograph (EM) analysis of the 40 % fraction is shown in Figure 2b and displays spherical particles with a diameter of 29 ± 3 nm (average measured on n = 164 particles). This homogeneity relates them better to SVPs from HBV than to the heterogeneous empty particles of 30-60 nm reported for DHBV. [24] As the DHBs S protein self-assembles into particles and is a transmembrane protein, but no lipids are added to the reaction mixture, it is likely that these SVPs contain residual lipids present in the WGE. Indeed, when preparing WGEs, we found [25] (c), or a DHBs-S-specific antibody [26] (d).

As negative control, an anti preS-specific antibody was used (e). Scale bar 100 nm.

To corroborate the identity and authenticity of the observed particles, we determined their antigenic properties. SVPs from the sucrose density gradient were analyzed by electron microscopy after immunogold labeling using Strep-tag II (Figure 2c) and DHBs S antigenspecific antibodies (Figure 2d). [26] A preS specific antibody was used as a control (Figure 2e).

The close proximity of the electron-dense gold particles to the SVP-like particles in c and d

but not e indicates their specific recognition by anti-Strep II and anti-DHBs antibodies. The interaction with the anti-Strep-tag II antibody shows that the particles observed correspond indeed to particles composed by DHBs S, and are no artefacts. The interaction with the DHBs S antigen-specific antibody confirms that the protein is in a state where the linear epitope against which the antibody reacts is exposed, similar as in SVPs and viral particles. [26] In order to assess secondary structure by circular dichroism, we purified DHBs S using affinity chromatography via the Strep-tag II (Figure 3a). The CD spectra recorded on DHBs S are characteristic of a structured protein, mainly folded into α-helices (Figure S3b) as expected from DHBs S structural models (see Figure 1b). Purification also allowed to assess expression yield, which was determined to 0.8 mg DHBs S per mL WGE used. We also prepared a triple C48,65,69S mutant (Figure S4a), in which all cysteine residues located in the cytosolic loop are mutated to serine. This mutant does not assemble into SVPs on expression (Figure S4b) but shows, after purification (Figure S4c), a very similar profile in CD spectra (Figure S4d), indicative of a high α-helical content, meaning that also monomers or smaller oligomers of the protein show the expected secondary structure content. As the WT protein assembles into SVPs, one can deduce that not only the helical scaffold, but also the cytosolic loop (which constitutes the major extra-helical region in the protein) in WT HBs S must show a conformation compatible with assembly of the protein into SVPs, indicating the functional fold of our sample. If it is perturbed, no assembly takes place.

We have prepared NMR samples of the protein using different protocols. As affinity purification resulted in particle dissociation, it was not used, and all samples had in common that the protein-containing fractions from the sucrose gradient were diluted twice and directly sedimented into the NMR rotor using dedicated filling tools. [27] Variation of parameters included sucrose gradients, amino-acid mixtures used for expression, rotor-filling procedures and constructs. We evaluated the sample quality using 2D 1 H-15 N 100-110 kHz MAS solidstate NMR spectra recorded on 0.7 mm NMR rotors, which are shown in Figure S5. It can be seen there that spectrum quality depended on sample preparation; with the use of an algal amino-acid mix resulting in poor expression and signal-to-noise ratio (SNR), and with protein more efficiently filled using modified filling tools (#1 vs #2-4) (for details see Figure S5 caption). Whereas first trials were made using productions containing 2 mL of WGE, the use of 0.5 mL proved sufficient in the end to fill a rotor. While here home-made WGE was used [9] resulting in costs of 650 € per triply labeled sample, the cost remains in the range of standard NMR samples also with commercial extracts (approx. total of 1000 € per sample). Figure 3 shows the NMR spectrum recorded on sample #4 where the (unused, as for solid-state NMR sample preparation the protein is exclusively purified by the sucrose gradient centrifugation)

Strep-tag II was removed from the expression plasmid. It shows the highest sensitivity (SNR = 8 as measured on isolated signals) compared to all other preparations (Figure S5), and the 2D spectrum recorded in 19 h shows many distinct signals. We processed the spectrum using a 60° shifted sine-bell function (SSB = 3 in BRUKER Topspin), and plotted it just above noise level. Figure S6 shows the spectrum processed with other apodization functions, in order to illustrate the artificial resolution-enhancement that can be achieved. We measured linewidths for different signals (on a spectrum processed without resolution enhancement using a pure cosine wave, SSB = 2), and obtained values of 128-192 Hz for the four resolved lines marked by crosses in Figure 3. Global T 2 ' times measured on series of 1D spectra were 3.9 ± 0.6 ms, and T 1ρ 18 ± 3 ms (see Table S1). Linewidths of DHBs S are larger than linewidths of microcrystalline proteins as ubiquitin, [28] SH3 [29] or GB1, [30] but are found close to the ones observed for deuterated, HN backexchanged and fully protonated model membrane proteins, as OmpG [29] and proteorhodopsin, [14] which show around 100 and 190 Hz proton linewidths respectively. While deuteration is always benefitial in terms of linewidth, it only reduces the coherent linewidth, and depending on the size of incoherent contributions, the effect can be larger or smaller. To separate the effects as much as possible, we therefore use only perdeuterated proteins in this study. 1D traces along different nitrogen dimensions are shown in Figure 3 to illustrate the signals in the proton dimension and their signal-to-noise ratio. The signals in the spectrum are distributed over a spectral width that can be expected for a fully α-helical protein, which shows by nature a smaller chemical-shift dispersion than proteins containing β-strand or both α-helical and β-strand conformation. Indeed, as shown in Figure S7, the spectral region of the backbone amide correlations in the DHBs S spectrum highly coincides with NH correlations simulated from BMRB chemical shifts of a mainly αhelical protein, here proteorhodopsin, [31] and lacks the typically larger distribution of a βbarrel protein chemical shifts, as OmpX. [32] Besides the backbone NH correlations, one sidechain signal is observed for His60 (only His in the protein, located in the cytosolic loop) and three or four for Trp (total of 7), with dispersed chemical shifts due to sequence-specific environments. The signal in the upper left corner likely stems from an Arg side chain (three total), which shows an outlier Hε chemical shift. This might be indicative for it being involved in interaction, likely with the membrane, since all three arginines are predicted to be located at the membrane interface, at the beginning or the end of the cytosolic loop. One can notice a certain distribution of linewidths and intensities of the peaks in the spectrum, likely reflecting different structure/order and/or dynamics in different parts, as transmembrane or turns, of the protein. Uncovering these features will be subject of our further steps. mm (outer diameter) rotor was filled using the 40% and 45% fractions of a discontinuous sucrose gradient which were directly sedimented into the rotor using a dedicated filling tool. [27] Linewidths here have been measured on spectra processed with pure cosine waves as apodization function (SSB = 2 in BRUKER Topspin), and are given for a selection of four signals likely presenting single resonances. The 2D spectrum has been processed using a 60° shifted sinebell function (SSB = 3 in BRUKER Topspin), and is plotted just above noise level. Figure S6 shows the spectrum with other apodization functions, in order to illustrate their effect on the resolution observed in the 2D plots. 1D traces show extracts of the 2D plot to illustrate S/N ratio.

We have shown here that DHBs S can be successfully expressed in wheat germ cell-free reactions in an isotope labeled form, and that the assembly of the protein into subviral particles is spontaneous in the presence of the mild detergent MNG-3. Cell-free expressed DHBs S particles show a rather narrow distribution of diameters, close to the ones formed in vivo by the human virus HBs S, [33] and their constituent subunits display mainly α-helical secondary structure. They show similar antigenic properties as envelopes and SVPs isolated from DHBV-infected ducks. The 2D selective labeling strategies as easily achieved in cell-free reactions, sequential assignments of the protein and subsequent structure determination get into the range of the possible, either using 3D spectroscopy, or alternatively using approaches combining defined selective labeling schemes with 2D spectroscopy. [34] Indeed, as described in the literature, [35] and also shown by us recently on the HCV NS4B protein, [17] virtually clean selective carbon-13 labeling can be achieved in cell-free systems. These approaches thus shall open the way to structure investigations of HBs S from the duck and ultimately the human virus, and eventually enable to elucidate the structural features of complex membrane protein assemblies like these viral surface proteins, central in infection.

Figure 1 .

 1 Figure 1. Expression of the small envelope protein of the DHBV virus. a Schematic representation of the DHBV virion, composed of an envelope (in pink) consisting of small (S) and large (L) surface proteins (in the human virus, a middle (M) protein exists in addition); a capsid formed by the DHBc protein (in grey), and the DNA encoding for the viral proteins (in black). The viral polymerase (black oval) is present in the virion as well.

  Strep-tag II antibodies are shown. CFS, total cell-free sample; Pellet, pellet; SN-beads, supernatant of CFS, incubated with Strep-Tactin magnetic beads. Comparable amounts were loaded on the gel for Pellet and SNbeads.

  the supernatant and the lipid fraction is not quantitative on extract preparation.

Figure 2 .

 2 Figure 2. DHBs S self-assembles into SVP-like particles in a WGE cell-free expression system. a Analysis on a sucrose gradient of DHBs S produced in a dialysis reaction (supernatant only). SDS-PAGE (top panel) and Western blotting (bottom panel) using a Strep-tag II antibody. I, input; 10%-60%, sucrose concentration; P, pellet. Arrowheads indicate the protein of interest. A red star indicates the fraction used for electron microscopy (negative staining) shown in b; scale bar, 100 nm. c-e Transmission electron microscopy analysis of immunogold labeled DHBV SVPs using a anti Strep-tag II antibody[25] (c), or a DHBs-S-specific antibody[26] (d).

Figure 3 .

 3 Figure 3. 2D 1 H-15 N spectrum of DHBs WT at 110 kHz MAS and 850 MHz proton Larmor frequency. The 0.7

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  combination of cell-free protein expression and 110 kHz magic-angle spinning solidstate NMR allows to obtain spectra of less than 500 μg in-vitro self-assembled sub-viral particles of the duck hepatitis B virus. This should pave the way for investigations of this kind of large membrane protein assemblies which structures remained intractable. Guillaume David, Marie-Laure Fogeron, Maarten Schledorn, Roland Montserret, Uta Haselmann, Susanne Penzel, Aurélie Badillo, Lauriane Lecoq, Patrice André, Michael Nassal, Ralf Bartenschlager, Beat H. Meier* & Anja Böckmann* Page No. -Page No.

Acknowledgements

This work was supported by the Swiss National Science Foundation (Grant 200020_159707), the French ANR (ANR-14-CE09-0024B), and the LABEX ECOFECT (ANR-11-LABX-0048) within the Université de Lyon program Investissements d'Avenir (ANR-11-IDEX-0007). Electron microscopy images were recorded at the IBISA CIQLE platform (CNRS UMS3453 / INSERM US7) and we thank Elisabeth Errazuriz, Bruno Chapuis and Denis Ressnikoff for technical assistance. CD spectra were recorded at the Protein Science Platform SFB UMS 3444 / US8. R.B. was supported by the Deutsche Forschungsgemeinschaft, TRR83, TP13 ; LL was supported by the Marie Skłodowska-Curie program (H2020-MSCA-IF-2016 748516); BHM was supported by the European Research Council (ERC grant agreement n° 741863, FASTER) ; and MN by the Deutsche Forschungsgemeinschaft (NA154/9-4) References