Antoine Armandineleslandes
email: a.armandineleslandes@brgm.fr

Julie Maury

Théophile Guillon

Simon Lopez

Arnold Blaisonneau

Van Hieu Tran

Annick Loschetter

Mariane Peter-Borie

Hydrothermal simulation in a fault zone: Impact and efficiency of different stimulation methods

Keywords: fluid flow, heat transfer, stimulation, scenarios, fault, geothermal, numerical modeling, DEEPEGS

, the permeability variations (around the well and in the matrix surrounding the fractures) are implemented into the hydrothermal model in order to assess the impact of thermal stimulation. The main aim of this study is to assess the influence of different stimulation methods into a unique hydrothermal model in order to test different stimulation scenarios. The final goal of this work is to provide numerical tools in order to investigate the relative efficiency of stimulation methods in the context of EGS.

INTRODUCTION

In some contexts, it is often not possible to extract the Earth's thermal energy under economic conditions without implementing technological solutions (so called "Enhanced/Engineered Geothermal System", abbreviated EGS) to increase the injectivity/productivity of the wells. To be able to generalize the exploitation of deep geothermal energy, these cases must be addressed through appropriate technological solutions. The H2020-DEEPEGS project (grant agreement No 690771) aims at demonstrating the feasibility of EGS for delivering energy from renewable resources in Europe. In this framework, two deep geothermal wells in Iceland and in France were drilled to demonstrate the EGS technology in different geological contexts (Peterborie et al., 2020).

In France, the Vendenheim (VDH) doublet is located in the Upper Rhine Graben (URG), in Eastern France. The target is a fault zone in the granitic basement. The reached temperature at around 4400 m TVD is estimated around 200°C. The initial injectivity/productivity index, is far from the economically viable target. Under such conditions, several operations are considered to enhance the output of the wells, either by improving near-well permeability, or by opening hydrological connections to permeable zones not directly intersected by the well. The methods generally used are based on the activation of mechanical, thermal and/or chemical mechanisms that drive to rock permeability enhancement as well as multi-drain well geometry (see [START_REF] Peter-Borie | Assessment of Geothermal Well Productivity Improvement Technologies: an Overview from the DEEPEGS Project[END_REF] for a detailed description concerning the stimulation methods and the context of this study).

Within the H2020-DEEPEGS project, in order to study the impact of stimulation scenarios on the permeability development, we assess different stimulation methods and well architectures for both demonstrators by numerical modelling. This paper aims to assess the relative impact of several technologies for the VDH demonstrator using a hydrothermal model and based on the results of hydromechanical and thermomechanical models presented in companion papers [START_REF] Blaisonneau | Hydromechanical modelling of the hydraulic stimulation of a fault zone as deep geothermal target[END_REF][START_REF] Peter-Borie | Thermal stimulation of the deep geothermal wells: insights from the H2020-DEEPEGS project[END_REF].

CONCEPTUAL MODEL OF VENDENHEIM RESERVOIR

The VDH demonstrator is located in the URG, which is part of the European Cenozoic Rift System (ECRIS, Ziegler, 1990 among many others). This approximately 300 km-long and 40 km-wide rift is bounded on the French side by the Vosges Mountains and on the German side by the Black Forest (Figure 1).

The VDH demonstrator targets a N10°E-striking and 82°W-dipping fault in the plutonic basement in the North of Strasbourg. Based on the tectonic history (polyphasic tectonic) of the Rhine graben and the orientation of the main faults surrounding the target fault of the VDH demonstrator, it can be assumed that this target fault in the basement has been formed by a sinistral shearing during the Paleozoic and reactivated during Cenozoic Times [START_REF] Edel | The Variscan tectonic inheritance of the Upper Rhine Graben: evidence of reactivations in the Lias, Late Eocene-Oligocene up to the recent[END_REF]Schumacher, 2002, among others). A conceptual model of the fault zone is proposed in Figure 1 [START_REF] Peter-Borie | Assessment of Geothermal Well Productivity Improvement Technologies: an Overview from the DEEPEGS Project[END_REF]; it is based on drilling data and cutting analyses. Here are recalled some of the main characteristics (especially those related to hydraulic features) of this model. In the basement, based on the identified losses, the fault zone can be distinguished in three main zones (see Figure 1 where blue stars correspond to losses):

(1) A damage zone in the upper part of the openhole with one main loss at the top of the damage zone and then several minor losses distributed along the damage zone

(2) A sealed fault core with a low permeability (with no losses) (3) A transmissive fault core (heavily fractured zone: cataclasite) with diffuse losses. Note that Euhedral quartz has been found in the cuttings, probably linked to hydrothermal sealing of discontinuities.

From a hydraulic point of view, the major interfaces that delineate the three main zones of this fault zone appear favorable to flow. Firstly, the major loss is located at the top of the damage zone. Then, two anomalies of chlorite crystallization temperature are localized between the two fault cores or at the interface between altered and moderately altered zones. These anomalies characterize preferential circulations. These observations are in agreement with in-situ measurements of Rittershoffen wells where interfaces are considered as the major circulation zones [START_REF] Glaas | How do the geological and geophysical signatures of permeable fractures in granitic basement evolve after long periods of natural circulation ? Insights from the Rittershoffen geothermal wells ( France )[END_REF].

Little data is available with respect to hydrogeological functioning of the reservoir. Due to the lack of information and based on measurements from the Cronenbourg wells (few km from the study area), a hydrostatic state is considered, where a pressure of approximately 279 bars is measured at a depth of 2755 m [START_REF] Cruz Mermy | Evaluation des potentiels géothermiques profonds de la Communauté urbaine de Strasbourg[END_REF]. Note that in its upper part (above the basement), the target fault intersects some permeable units at many depths, which can act as a reservoir. For the final measured depth of wells, around 4400 m TVD the temperature estimated is around 200°C and the salinity of the fluid within the reservoir is estimated around 100 g/L. If a hydrostatic state is assumed for the reservoir, a pressure of 431 bars at a depth of 4290 m is expected. This pressure value is in accordance with other wells pressure measured in the same hydrogeological context (Rittershoffen, Soultz-sous-Forêts). Based on these first observations, we can notice that the major loss is located at the top of the damage zone and then several minor losses are distributed along the damage zone until to the sealed fault core. This distribution of losses is not a feature of a decreasing of permeability (fracture density) with the distance to the fault core. Then, the structural organization of the fault zone is very heterogeneous. Moreover, data issued from previous studies, such as Soultz-sous-Forêts or more recently Rittershoffen [START_REF] Baujard | Hydrothermal characterization of wells GRT-1 and GRT-2 in Rittershoffen, France: Implications on the understanding of natural flow systems in the rhine graben[END_REF] demonstrate that the hydraulic behavior of this reservoir is controlled by discontinuous structures at pluri-hectometric scale with multiple orientations related to the orientation of the Euclidian structures and the nature of the fault (formation context). On this basis (considering these discontinuous structures), the functioning of the fractured reservoir can be explained (see [START_REF] Gentier | A flow model of the deep geothermal reservoir of Soultz-sous-Forêts (France)[END_REF]. Considering the importance of discrete fractures, it appears appropriate and relevant to consider discrete element methods to assess and understand this kind of reservoir.

Here, as previously mentioned, borehole data to identify fracture orientations are not available. To overcome this lack of information and go further in the understanding of the flow paths around the well during stimulation methods, a Discrete Fracture Network (DFN) is built based on the assumptions that: i. the URG is globally an Andersonian system; ii. the fault has been formed by a sinistral shearing. Rocks which are sheared by brittle or cataclastic processes often develop a characteristic structural pattern of fractures [START_REF] Cloos | Experimenten zur inneren Tektonic[END_REF][START_REF] Katz | Geometry and kinematic evolution of Riedel shear structures[END_REF][START_REF] Riedel | Zur Mechanik Geologischer Brucherscheinungen[END_REF] and then can serve as basis to develop a theoretical geometry of the subfracturing. Then

NUMERICAL MODEL

Numerical codes

The 3D numerical model is constructed using three successive different codes.

3DEC

Firstly, we used the 3DEC software (which is based on the Distinct Element Method (3DEC TM)) to generate the DFN. The 3DEC software will be used to simulate the hydromechanical stimulation (see Blaisonneau et al., 2020a for more details). The same geometry will be used for the hydromechanical and thermohydraulic models in order to facilitate the exchanges. The building step of the geometry is described in section 3.2 Geometry below.

SALOME

The open-source software platform named SALOME is used to rebuild the same geometry (resulting from the mechanical model) and to mesh the whole domain, in order to, ultimately, simulate hydrothermal flows in the fault zone using the ComPASS platform. The platform is available under Lesser General Public License (LGPL) at http://www.salome-platform.org. SALOME is actively developed with the support of Open CASCADE. SALOME results from a collaborative development approach between the CEA and EDF. SALOME uses two languages, Python and C++. The main functionalities of these parts are accessible by scripting languages and/or the graphical user interface. The platform also takes distributed meshes into account, thus facilitating parallel computations [START_REF] Ribés | SALOME : an Open-Source simulation platform integrating ParaView SALOME[END_REF].

ComPASS

This part describes briefly the ComPASS platform (its main components and characteristics). The reader interested in further details is referred to the works of [START_REF] Xing | Parallel numerical modeling of hybrid-dimensional compositional non-isothermal Darcy flows in fractured porous media[END_REF] for the description of the theoretical and numerical aspects of the modeling of compositional multiphase flows in fractured media, Beaude et al.,(2017) for the integration of complex well architectures (Beaude et al., 2017b) and the specification of complex boundary conditions [START_REF] Beaude | Numerical Modeling of High Energy Geothermal Systems with Soil Atmosphere Boundary[END_REF]. Additional information is also available on http://www.anr-charms.org and in [START_REF] Lopez | Geothermal Modeling in Complex Geological Systems with the ComPASS Code[END_REF].

The continuous multiphase multicomponent model

The ComPASS code is based on a Coats type formulation [START_REF] Coats | Implicit Compositional Simulation of Single-Porosity and Dual-Porosity Reservoirs[END_REF] which extends the work by [START_REF] Eymard | Vertex-centred discretization of multiphase compositional Darcy flows on general meshes[END_REF] to nonisothermal flows. It accounts for an arbitrary nonzero number of components in each phase allowing to model immiscible, partially miscible or fully miscible flows. The number of phases and number of components are hard-coded for each thermodynamical module. As the model takes into account phase change reactions which are assumed to be at equilibrium, phases can appear or disappear. Thermodynamical properties of each phase depend on the phase pressures, the temperature, and the phase molar fractions. These properties are specified by the user as hard coded functions along with their derivatives. The reader interested in further details is referred to the paper of [START_REF] Lopez | Geothermal Modeling in Complex Geological Systems with the ComPASS Code[END_REF] and references therein for the description of the theoretical and numerical aspects of the modeling of compositional multiphase flows in fractured media.

Hybrid model including a discrete fracture network

Two classes of models, dual continuum and discrete fracture models, are typically employed and possibly coupled to simulate flow and transport in fractured porous media. Discrete fracture models (DFM) represent explicitly the fractures as codimension one surface immersed in the surrounding matrix domain. ComPASS uses the DFM approach with a lower dimension physical model along the fracture which is derived from the equi-dimensional model of the previous paragraph by integration and averaging along the -possibly variable -width of each fracture. The resulting so-called hybrid-dimensional model couples the 3D model in the matrix with a 2D model in the fracture network taking into account the jump of the normal fluxes as well as additional transmission conditions at the matrix fracture interfaces. These transmission conditions depend on the mathematical nature of the equi-dimensional model and on additional physical assumptions depending on the fracture behavior (drain vs. barrier). The interested reader is referred to the paper by [START_REF] Xing | Parallel numerical modeling of hybrid-dimensional compositional non-isothermal Darcy flows in fractured porous media[END_REF] for further details.

Wells integration

A first version of reservoir well interaction has been implemented into the ComPASS platform and validated for monophasic cases (Beaude et al., 2017a). The well is modeled as a Dirac source term along the well trajectory. Most well models in reservoir simulations are defined by a set of connected perforations, each perforation belonging to a cell of the mesh (e.g. source block in TOUGH2). In order to take advantage of unstructured meshes and of the nodal feature of the Vertex Approximate Gradient VAG scheme, it is more convenient in our case to discretize each well as a subset of edges of the mesh. This alternative approach provides an efficient way to represent slanted and multi-branches wells. The fluxes connecting the well with the 3D matrix and the 2D fracture network at each node of the well are computed using Peaceman's approach [START_REF] Chen | Well flow models for various numerical methods[END_REF][START_REF] Peaceman | Interpretation of well-block pressures in numerical reservoir simulation with nonspace grid blocks and anisotropic permeability[END_REF][START_REF] Peaceman | Interpretation of Well-Block Pressures in Numerical Reservoir Simulation[END_REF]. It is based on a Two Point Flux Approximation (TPFA) with a transmissibility taking into account the unresolved singularity of the pressure (or temperature) solution in the neighborhood of the well. The non-isothermal flow model inside the well is defined using a single implicit unknown for each well corresponding to a reference pressure often coined as the bottom hole pressure. The pressures along the well are then deduced from this bottom hole pressure with the crude assumption that the pressure is hydrostatic inside the well. The temperatures along the well are computed assuming thermal equilibrium and a stationary flow inside the well.

Geometry

The domain is chosen large enough to enable hydrothermal simulation and integrate the size of major discontinuous elements. The numerical model domain is a block of rock measuring 500 m in the x-y-and z-directions and centered on the open-hole of the well. This domain is delineated with four major discontinuities (DZup, DZdown_FC1up, FC1down_FC2up and FC2down, see Figure 3a) that correspond to four major interfaces, which can be considered as the major circulation zones. These major discontinuities are used to delineate major zones (subdomains): the Damage Zone (DZ), the Sealed Fault Core (FC1), the Transmissive Fault Core (FC2) and the surrounding impermeable matrix (Figure 3b).

The second step is to generate a conceptual DFN in accordance with the number of productive fractures that intersect the well along the fault. Prior to fracture generation, a domain must be specified. Here, the generation volume is constrained by the two major discontinuities that delineate the DZ zone. Three fracture sets are defined and generated in separate steps. For each set, the DFN is defined according to the size and orientation distributions. Then fractures are generated until the target fracture frequency (number of fractures intersecting the well: P10) is reached. Here, we consider the number of intersections with the well in the DZ. We do this because the DZ has the more distributed losses, we consider the FC1 is only involved peripherally in the circulation and the FC2 is heavily permeable so a unique structure is enough to model it. Three families are considered (Table 1): R, R2 and Y (DZup, DZDown_FC1up, FC1down_FC2up, FC2down) according to the Riedel concept (Figure 3c). In order to perform the hydromechanical simulations, the DFN has been simplified. First, fractures can be isolated, disconnected from the largest cluster (here we assumed that the largest cluster is connected to the well). Then, isolated fractures are deleted. A second simplification is achieved by combining fractures that are too close together and subparallel (in our case when they belong to the same family). Here for each set (R and R2) the smaller fractures are deleted and replaced by a larger fracture when the normal distance with one other fracture is less than 23 m. Note that the area of the larger fracture is increased in accordance with the size of the deleted ones. Thus, some properties of the DFN are modified. The resulting DFN is shown in Figure 3d. The last simplification of the DFN corresponds to the deletion of dead-end of fractures (above the DZup and below the FC1down_FC2up limits). The following step is to build the geometry, introduce the DFN into the 3D domain (Figure 3e and Figure 3f) and then mesh the model (tetrahedral conformal meshing) using the SALOME code (Figure 3g). The final mesh is composed of more than 183 000 nodes and more than 1 billion of elements. Note that this geometry is implemented in the hydromechanical and hydrothermal models. To be consistent with the conceptual model, the permeable fault core (FC2) will be an equivalent porous media (permeable) and the impermeable fault core (FC1) will be fractured (surrounded by an impermeable porous media) as a prolongation of the fractures within the DZ. The fractures through the FC1 zone allow a possible connection between the DZ zone and the FC2 permeable zone.

Hydraulic and thermal parameters

To carry out model computations, distributions of thermo-hydraulic properties (e.g., permeability, porosity, thermal conductivity, specific heat, etc.) for all the elements (fractures and porous media), and boundary conditions along the faces of the model are prescribed. During the development of the intial-state model for the fault zone reservoir considered, the formation properties (i.e. permeabilities of fractures) were varied in order to match the injectivity index and the main losses observed. Numerous simulations have been performed to match these constraints; in the following, we only present the final test that constitute the reference case of this study. The following Table 2 and Table 3 synthetize the values from this first step. The Figure 4 shows the permeability of the fractures, the permeability of the subdomains and the differential of pressure for the initial injection test (40 m 3 /h during 12 hours). Note that the injectivity index obtained for the reference case is about 0.23 L/s/bar.

Initial and boundary conditions

As a first approximation, a hydraulic no-flow boundary condition is specified for the lateral (North, South, East, and West) and bottom model boundaries. For the top of the model, a Dirichlet boundary condition is applied (temperature and pressure). As mentioned previously, a hydrostatic state is assumed for the reservoir, then the pressure is fixed in accordance with the depth of the top of the reservoir . The initial temperature of the reservoir is constant around 200 °C and fixed at the top of the model.

SIMULATIONS

The main idea of this work is to provide an overview of the impact of different stimulation methods considered to enhance the productivity of the targeted reservoir. The impact of the different technologies used to enhance the injectivity of the well such as stimulation methods (the hydraulic and thermal methods are considered) or such as multi-drain well geometries are studied. Here, we detailed the first results of this on-going work based on the results of companion papers [START_REF] Blaisonneau | Hydromechanical modelling of the hydraulic stimulation of a fault zone as deep geothermal target[END_REF][START_REF] Peter-Borie | Thermal stimulation of the deep geothermal wells: insights from the H2020-DEEPEGS project[END_REF]. To assess the impact of each stimulation method, an injection test is performed (considering an injected fluid at a temperature of 50°C and a flow rate of 40 m 3 /h during 12 hours). For each case, the injectivity index is calculated and then compared to others.

Hydraulic stimulation

In order to assess the injectivity gain by hydroshearing, hydro-mechanical numerical simulations are performed. The hydraulic stimulation is modelled as a multi-step fluid pressure increase. Modelling process details are available in the companion paper [START_REF] Blaisonneau | Hydromechanical modelling of the hydraulic stimulation of a fault zone as deep geothermal target[END_REF]. The hydraulic aperture variations (considering the hydraulic criterion "irreversible residual apertures") resulting from the hydromechanical simulation [START_REF] Blaisonneau | Hydromechanical modelling of the hydraulic stimulation of a fault zone as deep geothermal target[END_REF] are imported into the hydrothermal model to modulate the initial reservoir properties in accordance with the hydraulic stimulation (Figure 5 left).

Well architecture

Multilateral well configurations are sophisticated well architectures developed to increase the well productivity/injectivity. A multilateral well consists of one primary well and one or more secondary wells issuing from the first [START_REF] Aubert | Variations in Multilateral Well Design and Execution in the Prudhoe Bay Unit[END_REF]. The fault-zone reservoir of Vendenheim seems to be a reasonable candidate for multilaterals configuration. The two-legs configuration is presented in the Figure 5 (middle and right). The performance of this well configuration is compared with a configuration with only one well (Figure 5 left). This well configuration is assessed in the reference case (initial permeability, before stimulation) and then in the case following the hydraulic stimulation in order to assess the combined effect on the injectivity.

Thermal stimulation

Thermal stimulation appears as a promising technique to enhance the productivity/injectivity of the reservoir. In line with the previous numerical simulations, the cooling of the reservoir will be different according to the stimulation methods applied and the well architecture implemented. Based on the combination of the results provided by the study of Peter-Borie et al., ( 2019) and the temperature field resulting from hydrothermal simulations (thermal field), the permeability variations (around the well and the matrix surrounding the fractures) will be implemented to assess the impact of thermal stimulation. Hereafter, we provide an example of the work carried out by Peter-Borie et al., (2019), which has been used to consider the impact of thermal stimulation. The Figure 6 demonstrates the permeability variations (around a fracture) resulting from a differential of temperature of 150°C (due to the injection of a cold fluid of 50°C). The fracture is at the center of the domain (y = 0, where the injection is considered) and the domain is subdivided in two subdomains (Figure 6). The upper part represents a granite and the bottom part a hydrothermalised granite sealed by quartz. After the injection of the cold fluid, thermal cracks have been created (Figure 6, left). The contours of cracks are delineated and the permeability of cracks calculated (Figure 6, middle). Then, an average permeability is estimated in Y-directions (Figure 6, right) according to this following relationship:

𝐾 𝑎𝑣𝑔 = ∑ 𝐿 𝑖 𝑛 𝑖=1 ∑ ( 𝐿 𝑘 ) 𝑖 𝑛 𝑖=1 = 1 ∑ ( 1 𝑘 ) 𝑖 𝑛 𝑖=1
Where 𝐾 𝑎𝑣𝑔 is the average permeability (m²), 𝐿 𝑖 the length of the subdomain i (m) in the Y-direction and 𝑘 the permeability (m²) of the subdomain i. Based on these results, we can notice that for a short lapse of time and a temperature difference of 150°C in a hydrothermalised granite, the permeability reached a value around 5x10 -13 m² close to the fracture. This contrasts sharply with the granite (upper part) where the permeability is slightly modified very close to the fracture. Note that this study has been carried out for different kinds of granites, as well as different temperature contrasts and also for different configurations, such as around the well providing a set of values of permeability variations that can be used to assess the impact of thermal stimulation. As a first approximation, a simulation considering an injection test of a fluid at 50°C (40 m 3 /h during 30 days) is performed. The resulting thermal field (differential of temperature, see Figure 7, left) is used to identify zones impacted by thermal cracks and then in order to implement the permeability variations in accordance with these zones (see Figure 7, right). Then, the new permeability field is used to assess the impact of thermal stimulation using the same injection test (40 m 3 /h during 5 days) as for previous simulations.

Results

The different methods and their combined impacts are compared in terms of injectivity (Figure 8). Firstly, we can describe the respective impact of each method (hydraulic stimulation, thermal stimulation and well architecture) in comparison with the initial state of the reservoir. For the hydraulic stimulation (HM), the injectivity index is multiplied by 1.5. As well, in this particular case and for the specific well architecture tested (two-legs) the injectivity index is multiplied by a factor of 1.4. The impact of the thermal stimulation is slightly inferior, with the injectivity multiplied by 1.2. Based on these first results, it seems that these methods are almost equivalent to enhance the initial productivity of the targeted reservoir (even if these specific results show a slight difference between these methods in favour of the hydraulic stimulation). However, the HM results are highly dependent on the mechanical parameters implemented into the hydromechanical model, which require further analysis (assessment of the mechanical parameters, see Blaisonneau et al., 2020a). The main difference between these methods can be assessed through the pressure and temperature differentials (Figure 9 and Figure 10). In comparison with the reference case, the impact of the TM stimulation (Figure 9, TM) is localized within the first main fracture, which results from the main zone impacted by thermal cracks (Figure 7). The results of the HM stimulation (Figure 9, HM) is clearly different: the pressure differential is very localized and lower due to higher permeability of some fractures which were almost impermeable and, therefore, result in a better distribution of the pressure within the reservoir. Then, more fractures are permeable and the temperature differential is reduced (Figure 10, HM). The "two-legs" architecture increases the number of points to distribute the injection and then results in a better injectivity. However, the envelope of the pressure differential is comparable to the reference case (Figure 9, Two-legs).

Then, simulations were performed to study the combined impact of these respective methods (scenarios). The results of scenarios are summarised in Figure 8 (injectivity). Overall, the combined impact of methods allows an increase in injectivity. The successive effect of the hydraulic stimulation and the well architecture would appear highly beneficial to the reservoir injectivity. In comparison with the reference case, the injectivity index is multiplied by a factor of 2.6. The combined impact of the TM stimulation seems relevant in all cases, except for the case (HM + 2 legs + TM) where the TM stimulation can be slightly negative. In that specific case, the permeability variations (around the well and the matrix surrounding the fractures in accordance with the differential of temperature) is related to the quantity of cold water injected into the reservoir. An increase of the flowrate (or a longer duration) could be considered due to the better injectivity after the first two methods, then the zones impacted by thermal cracks will be greater and thus the injectivity index could be greater. This latter finding requires further investigation.

CONCLUSION

The aim of this paper is to provide an overview of a study carried out in the framework of the H2020-DEEPEGS project. In this paper, we propose to investigate the impact of well architecture for a fault zone geothermal reservoir using a hydrothermal model based on a hybrid approach (including a DFN). The hydrothermal model developed for this specific demonstrator is used to study the impact of hydraulic stimulation (HM) (based on the results provided by the hydromechanical study, [START_REF] Blaisonneau | Hydromechanical modelling of the hydraulic stimulation of a fault zone as deep geothermal target[END_REF] and the impact of the well architecture. Then, this hydrothermal model is also used to test the impact of the permeability variations resulting from the thermo-mechanical numerical modeling (Peter-Borie et al., 2019), which results from the "cold" water injection and the associated thermal cracks is also implemented in order to assess the impact of thermal stimulation. The impact of each method is assessed through the increase of the injectivity accoding to pressure differential as well as the resulting thermal field. For the case study considered here, it appears that the different methods investigated (HM, TM, two-branches architecture) lead to the same order of magnitude in terms of injectivity improvement. The injectivity for each method considered separately is multiplied by a factor comprised between 1.2 and 1.5. The combination of methods (HM + two-legs) enables further improvement of injectivity, with multiplication factor around 2.6. It should be kept in mind that results are very dependent from the choice of parameters an should thus be considered cautiously.. The last step of this study will be to implement the effect of the chemical stimulation (acid injection) and test the impact of different scenarios (successive stimulation methods) based on the presented work. The import of constraints provided by other numerical codes into this unique hydrothermal model offers a way to test different scenarios of stimulation in order to identify the most appropriate solution as well as to better understand the mechanisms related to each stimulation methods.

Figure 1 :

 1 Figure 1: Conceptual model of the geometry of the targeted fault zone based on the drilling data (modified from Peter-Borie et al. 2020). Blue stars correspond to losses.

Figure 2 .

 2 Figure 2. Riedel concept: Fractures classically developed in shear zones with blue and gray arrows are the sense of shear. R: Riedel shears which are normally the first subsidiary fractures to occur. R2 shears are antithetic fractures, conjugate with R shears. Y shears are synthetic fractures subparallel to the main fault. T are theoretical distribution of tensional fractures.

Figure 3 .

 3 Figure 3. Main steps to build the geometry of the model

Figure 4 .

 4 Figure 4. Initial model (reference); Left: Permeability of fractures (m²); Middle: Permeability of subdomains; Distribution of the differential of pressure (Pa) between initial state and after 12 h of injection

Figure 5 .

 5 Figure 5. Permeability distribution for each model and well architecture. Left: Permeability resulting from hydraulic stimulation. Middle: Well architecture (two-legs). Right: Combined method: Hydraulic stimulation and well architecture are both deployed.

Figure 6 .

 6 Figure 6. Left: Thermal cracks (and thermal field) in hydrothermalised granite sealed by quartz (bottom part) and granite (upper part). In the middle: Contours and permeability of thermal cracks. On the right, average permeability estimated around the fracture.Based on these results, we can notice that for a short lapse of time and a temperature difference of 150°C in a hydrothermalised granite, the permeability reached a value around 5x10 -13 m² close to the fracture. This contrasts sharply with the granite (upper part) where the permeability is slightly modified very close to the fracture. Note that this study has been carried out for different kinds of granites, as well as different temperature contrasts and also for different configurations, such as around the well providing a set of values of permeability variations that can be used to assess the impact of thermal stimulation. As a first approximation, a simulation considering an injection test of a fluid at 50°C (40 m 3 /h during 30 days) is performed. The resulting thermal field (differential of temperature, see Figure7, left) is used to identify zones impacted by thermal cracks and then in order to implement the permeability variations in accordance with these zones (see Figure7, right). Then, the new permeability field is used to assess the impact of thermal stimulation using the same injection test (40 m 3 /h during 5 days) as for previous simulations.

Figure 7 .

 7 Figure 7. Left: Differential of temperature (between initial and last step: 30 days). Right: the resulting zones impacted by thermal cracks on the fractures and within the matrix.

Figure 8 .Figure 9 .Figure 10 .

 8910 Figure 8. Injectivity (L/s/bar) for each case

Table 1 . Fracture set properties

 1

	Fracture set	Property	Distribution	Parameters
	R	positions	Uniform	Positions generated in all DZ space
		orientations	Uniform	Dip: 82.48°, Dip direction 259.82°
		lengths	Power law	Scaling exponent: a = 2, lmin = 20, lmax = 200
		density		P10
	R2	positions	Uniform	Positions generated in all DZ space
		orientations	Uniform	Dip: 87.27°, Dip direction 209.82°
		lengths	Power law	Scaling exponent: a = 2, lmin = 20, lmax = 200
		density		P10
	Y	positions	Deterministic	Interfaces
		orientations		Dip: 82.24°, Dip direction 280°
		lengths		500m

Table 2 Hydraulic parameters Names of element Hydraulic parameters Subdomains Permeability [m²] Porosity

 2

	Matrix			10 -2	0.15
	DZ			10 -21	0.15
	FC1			10 -19	0.15
	FC2			10 -14	0.15
	Fractures
	R (set)			2.08x10 -14	0.999
	R2 (set)			8.33x10 -16	0.999
	Fractures in FC1			10 -19	0.999
	DZup			3.33x10 -13	0.999
	Y (DZDown_FC1up, FC1down_FC2up, FC2down)	2.08x10 -14	0.999
		Table 3 Thermal parameters
	Names of element	Thermal parameters
	Solid	Spe. Heat capacity	Thermal conductivity	Rock density
		[J.kg -1 .K -1 ]	[kg.m.s -3 .K -1 ]	[kg.m -3 ]
	Matrix, DZ, FC1, FC2, Fractures	800	2.3		2650
	Liquid
	Fluid	4200	0.6		f(T,P)

ACKNOWLEDGMENTS

This study was part of the DEEPEGS project, which received funding from the European Union HORIZON 2020 research and innovation program under Grant agreement no. 690771.


Morshed Mahbub

Simonaire Hervé

Alem-Marchand Halima

Roizard Denis
email: denis.roizard@univ-lorraine.fr

author. ROIZARD Tel Denis

Investigation of OSN properties of PDMS membrane for the retention of dilute solutes with potential industrial applications

Few commercially available membranes can be used for Organic Solvent Nanofiltration (OSN).

Applying OSN in chemical industries is nevertheless of high interest to cut with energy consumption linked to solvent recycling and soluble catalysts recovery. A commercial membrane, PERVAP4060, was used to investigate the retention of dilute solutes in toluene feeds and to mimic metathesis medium. The studied solutes were R-BINAP a neutral polyaromatic molecule used in metathesis chemistry, tetraoctylammonium bromide (ToABr), a charged molecule used as a homogeneous catalyst and n-hexadecane.

Retention of polar ToABr (95%) was higher than that of neutral R-BINAP (80%). The transfer mechanism, either pore flow or solution-diffusion, was discussed. All the results obtained suggested that the transport is governed by the solution-diffusion mechanism. The measured retentions could be explained in terms of solubility affinities and diffusion coefficients. The stability and performances of PERVAP4060 were well established, showing the strong potential for industrial applications.

INTRODUCTION

The application of membrane technologies for the retention of dilute organic solutes, such as soluble catalysts, is an essential target from an industrial viewpoint. An early paper from Gosser [1] and several patents from the late 20 th century [START_REF] Livingston | A1[END_REF] clearly indicate the interest in and the issues with membrane separation methods, such as pervaporation (PV) or organic solvent nanofiltration (OSN) [3] [4]. This study aims to investigate the retention of diluted diphosphine ligand R-BINAP and a phase transfer catalyst ToABr from a toluene feed using commercial composite polydimethylsiloxane (PDMS) membrane PERVAP4060 in order to favor industrial catalyst separation by membrane instead of distillation.

From an industrial viewpoint, the availability of membranes that provide a high solvent flux is very important and can be a decisive point in the design of a new process, as they can dramatically reduce capital cost expenditures (CAPEX). OSN is a highly attractive and relatively new method that can be used to purify and recycle low-volatility solvents at low cost or to concentrate valuable solutes, such as homogeneous catalysts dissolved in organic media like alcohols or aromatics. Distillation can also be used for these applications, but this benchmarked technology has two significant drawbacks: the evaporation of large quantity of solvent is very energy demanding, and the temperature increase may alter the properties of the solutes. In such media, it is desirable to extract the reaction products while preserving the homogeneous catalyst, which is generally a very expensive component based on chelating ligands and specific metallic cations, such as rhodium or ruthenium.

The potential of OSN to increase the catalyst turnover number in such industrial applications [START_REF] Marchetti | [END_REF] has been recognized for approximately two decades since its early industrial application in lube oils upgrading by EXXON [5]. However, the lack of availability of appropriate membranes for OSN with suitable molecular separation performances is a bottleneck. In this work, polymeric membranes were evaluated for the retention of 2,2′bis(diphenylphosphino)-1,1′-binaphthyl (BINAP) and tetraoctylammonium bromide (ToABr).

The neutral molecule BINAP is a ligand that is key to the activity of many metal complex catalysts [6], while the charged molecule ToABr is mainly used as a phase transfer catalyst.

These two solutes are highly soluble in toluene, which is often used as the reaction media.

Nowadays some studies involving inorganic membranes are emerging [7]. But most of the polymeric membranes that have been used for OSN are highly crosslinked membranes based on rigid polymer backbones, such as the aromatic polyimides P84 [8], Matrimid [9], PI Starmem [10], polysulfone, polyether ether ketone, polybenzimidazoles [11], and more recently PIM [12]. Koch developed the MPF series based on a PDMS active layer in the 1990s (Koch, 2014; www.kochmembrane.com). However, the number of commercially available OSN membranes is very limited. Currently the leading suppliers are Evonik (http://duramem.evonik.com/product/duramem-puramem/en, 2018), which supplies the Starmem, Duramen, and Puramem series, and Solsep (http://www.solsep.com/OSN.htm, 2018), Koch (http://www.kochmembrane.com/Membrane-Products/Spiral/Nanofiltration .aspx, 2018), and Inopor®, which supply inorganic membranes (Inopor, 2018; http://www.inopor.com).

The retention of some solutes, including soluble catalyst using Starmem and MPF membranes, has reported mainly from EtOH feed. Unfortunately, many of these membranes are no longer available, probably due to their lack of stability over time. Thus, this work was intended to study the retention of diphosphine ligand R-BINAP from a toluene feed using a commercial composite polydimethylsiloxane membrane (PDMS), PERVAP4060.

PDMS is a well-known rubbery polymer that is widely used for liquid, VOC, and gas separations [13]. However, polydimethylsiloxane (PDMS) is often considered to be unstable in non-polar solvents, as it is a very hydrophobic polymer and can undergo severe swelling in low-polarity solvents, such as alkanes or aromatics, with swelling degrees of well over 100 wt% being observed (g of solvent/g of dry polymer) [14]. Nevertheless, this swelling property could be very interesting for OSN applications, because a high degree of polymer swelling induces high solvent permeance, which is desirable in OSN. However, a high degree of swelling is often considered to be detrimental to the high retention of solutes because the solutes could easily flow through the membrane due to the high solvent flux [15]. This issue is even more significant when highly dilute solutes are considered. Hence, the strength of the coupling effect induced by the high solvent flux when using a dense membrane may represent a significant obstacle to their use in OSN.

In order to clarify these points, two series of OSN experiments were carried out under tangential flow to investigate the performance and stability of PERVAP4060 and to determine the retention values of ToABr and BINAP in diluted toluene mixtures. ToABr was studied in toluene as well as in an alcoholic mixture for comparison with literature data. The system was operated in steady-state mode, and the parameters studied were the feed pressure, feed flow, and feed mixture composition.

To the best of our knowledge, this multilayer membrane has never been used under OSN conditions for the retention of these catalysts at low concentration in toluene. R-BINAP is a ligand that is used to form soluble ruthenium complexes for olefin metathesis synthesis, and toluene is a typical solvent for this reaction [START_REF] Chen | A[END_REF] [START_REF] Mashima | [END_REF]. Before the investigation of the diphosphine ligand R-BINAP retention, we characterized the retention of ToABr from a toluene feed using PERVAP 4060 for comparison with previous results from the literature. By comparing the retention of R-BINAP, a neutral molecule, and ToABr, a charged molecule, under similar OSN conditions, we hoped to obtain further insight into the mechanism of mass transfer through PERVAP4060 and the influence of the solvent.

EXPERIMENTAL

Materials

(R)-BINAP (white powder; purity >94%), ToABr (white powder; purity 98%) and n-hexadecane (density 770 kg m -3 ; purity >99%) were purchased from Sigma Aldrich and used as received.

The solvents toluene (purity 99.8%) and ethanol (purity 96%) were also obtained from Sigma Aldrich.

The membrane used for the nanofiltration experiments was PERVAP 4060, which was provided by DeltaMem AG (https://www.deltamem.ch/) in flat A4 sheet form and used as received. PERVAP 4060 is a composite membrane with an active layer of 1-2 µm of PDMS (Figure 1).

Methods

OSN setup

An OSN setup reported in a previous publication [14] In addition to the previously reported setup, the applied pressure was regulated using an IP 65 solenoid valve connected to a digital pressure transmitter system and controlled using the Flow DDE Bronchorst software. (Figure 2b). This system allowed precise pressure control over the 0-40 bar range with a maximum fluctuation of 10% from the set value. The temperature was controlled using a Thermo Haake K50 with a precision of ±2 °C, and the cross-flow was set to 7-10 kg/h as measured using a Cori flow (digital mass flow) meter.

Membrane conditioning procedure

Before the OSN experiments, the membrane was immersed overnight in the solvent at room temperature (pre-conditioning). The membrane coupons had dimensions of 8 cm × 12 cm (including the area of the O-ring), corresponding to an effective useful membrane area of 34 cm 2 .

After quickly wiping the membrane surface, the coupon was mounted into the OSN cell using a double O-ring Viton seal. Next, both the upstream and downstream cells were sealed using an SPX hand pump, which ensured that the unit was free of leaks in the pressure range of 0-40 bar.

The conditioning began with circulating the feed through the circuit at a flow rate of 7-10 kg h -1 and a temperature of 30 °C. Next, a transmembrane pressure (TMP) of 10 bar was applied in steps of 2/3 bar using the flow DDE software interface. At each step, the set point was compared to the actual value in the OSN, ensuring the stability of the TMP in the upstream.

Once a pressure of 10 bar was achieved, the unit was monitored for 10-15 minutes to confirm that the pressure, cross-flow, and temperature were stable. The same procedure was repeated at 20, 30, and 40 bar. After conditioning at 40 bar, the TMP was gradually decreased to atmospheric pressure following the same conditioning protocol. The aim of this pretreatment was to avoid possible hysteresis effects due to the pressure increase. The same conditioning procedure was followed for the experiments at elevated temperature.

OSN procedure

The OSN experiments were performed in a cross-flow rig, in which NF was carried out in continuous mode. The permeate was continuously recycled to ensure a steady-state concentration of the feed.

Approximately 1 L of 0.05 wt% diphosphine ligand R-BINAP and phase transfer catalyst ToABr were separately prepared offline by dissolving the solutes in toluene. Very low feed concentrations (below 0.05 wt% R-BINAP) were prepared by dilution. High R-BINAP concentrations (higher than 0.07 wt%) were partially achieved inline by concentrating the OSN feed. TMPs of 0-40 bar and temperatures of 30-50 °C were studied in the OSN experiments. The conditioning procedure described above was repeated at each temperature. For the ternary mixture feed, initially, a 0.05 wt% R-BINAP solution was used, and gradually, 1 wt%, 5 wt%, and 10 wt% n-hexadecane (C16) were added to feed.

After conditioning, an upstream pressure was applied with a stepwise increment of 2/3 bar.

At each applied pressure, a 15-20 min blank run (no data point) was conducted to achieve stable permeate flow at the desired temperature and cross-flow. The permeate samples were then collected in a custom-made permeate vial with a small opening on the top to attach the vial to the OSN permeate line. This arrangement minimized evaporation loss of the solvent and ensured better measurement accuracy. At least 3-5 grams of the permeate was collected and weighed for each data point, and the corresponding collection time was recorded. At each applied pressure, at least three permeate samples were collected, with an interval of at least 20 minutes between each sample. The sample size, number of repetitions, and length of the interval between each sample ensured better measurement accuracy and system stability.

In most cases, after the data collection at 40 bar was completed, the permeate flux and retention measurements at 10 bar were repeated. In several experiments, the used membrane was placed in a second OSN unit with a smaller surface area of 20 cm 2 , and the reproducibility of the data was verified using a random TMP. The maximum deviation between different OSN units was 10% for the flux. Most of the experiments were repeated more than two or three times using new membrane samples from different batches, obtained at different times.

Analytical methods

The flux (J) and rejection (R) were calculated according to the formulas given below:

𝐽 = 𝑉 𝐴. 𝑡
Where J is the flux (Lm -2 h -1 ), V is the volume of the collected permeate (L), A is the active surface area (m 2 ), and t is the time (h).

𝑅 (%) = (1 - 𝐶𝑝 𝐶𝑓 ).100
where Cp is the concentration of solute in permeate and Cf is the concentration of the feed.

Quantitative analysis of the solutes was carried out using gas chromatography. The operational conditions of the analysis method were as follows:  Carrier gas: He, pressure 15 psi.

 Detector: FID (H2/air: 1/10), 380 °C.

In the dilute feed stream, the peak area of the feed and permeate were significantly lower than that of the solvent peak. Therefore, calibration and measurement were carried out using a suitable external standard, and the constant volume addition method. Each sample test was carried out in triplicate, and the results of the individual experiments were compared for the determination of solute retention.

In addition, at very dilute concentrations (as low as 0.0001 wt% of R-BINAP), the feed and permeate samples were first measured directly by GC, and then separate feed and permeate samples were concentrated by a factor of ten using a rotary evaporator. The new concentrations were re-measured using GC and compared with the initial results and were found to be reproducible with no more than 5% deviation. Three separate measurements were conducted using very low feed concentrations, and a new membrane sample was used each time. The retention was reproduced in each measurement. Data are given in Appendices C.

RESULT AND DISCUSSION

At the industrial scale, the use of highly dilute homogeneous catalysts for metathesis synthesis is preferable to the use of immobilized catalysts from an efficiency viewpoint. The current mature technology to recover the reaction products is distillation, but this method has the major drawback of causing the catalyst to lose its catalytic properties. OSN is considered to be a "soft" technology that can allow the separation of the product from the soluble catalyst at room temperature or moderate temperatures, thus avoiding the degradation of the expensive catalytic complex.

An overview of the literature related to the retention of BINAP and ToABr by OSN is given in Table 1, and their schematic representations in Figure 3. As can be seen, a few OSN studies have dealt with the retention of highly dilute BINAP complexes in MeOH feed solutions with MPF or STARMEM membranes [18] [19] [20], but none have utilized toluene, which is one of the preferred solvents for some catalytic reactions, such as olefin metathesis.

Using MPF membranes, de Smet [18] and Vankelecom [20] reported rejection (R%) ranging from 70 to 98% in MeOH and of up to 93% in iPrOH for the complex Ru-BINAP. A flux of ≈1.2 L m -2 h -1 was reported for MPF60, but no stable flux data were reported for the MF50 membrane, while a strong flux decline was observed with MeOH. The transport mechanism was explained using the pore flow model, which is controversial for dense active layers [21] [14] [22]. The authors suggested that the swollen dense PDMS layer became compacted at an OSN pressure of 16 bars, which was not supported by the work of other authors [21] [14].

They cited the work of Paul as a reference, but surprisingly, in the cited paper, Paul did not support the compaction hypothesis in this low-pressure range.

The two other reports of the retention of BINAP from MeOH [10] or ionic liquid (IL)/methanol solutions [23] made use of the Starmem 112 membrane. In both cases, high initial retention values of up to 99% in pure MeOH were obtained. In the IL/MeOH solutions, the retention of the catalytic Ru-BINAP complex was >92%. Interestingly, both papers also reported that the retained catalyst was still active and could be recycled. The retention of the ligand BINAP itself (using the P atom as a marker) was higher than the retention of the Ru-catalyst, indicating the presence of metal species that were able to permeate the membrane more easily.

In the case of ToABr, more OSN studies have been reported (Table 1), using both alcohol and toluene media. In each solvent, high solvent retentions in the range of 70-100% were obtained, depending on the type of membrane used. The highest flux was recorded for PMF60, a PDMS based membrane, along with surprisingly low retention of 48% [START_REF] Livingston | A1[END_REF]. The best retention results were obtained in toluene solutions [24] [25]. Using a PDMS-PEO composite membrane, Stamatialis showed that concentration polarization occurred when the ToABr feed concentration was below 8 wt%. Peeva analyzed the mass transfer through Starmem122 a polyimide membrane, using the solution-diffusion mechanism [26] and showed concentration polarization at 20 wt% (0.35 M) of ToABr. 1 From literature 2 Molar volumes calculated using HSPiP [START_REF] Hansen | Hansen Solubility Parameters: A User's Handbook[END_REF] except for that of ToABr [26] 3 Diffusion coefficient of toluene and ethanol [14], other diffusion coefficient values were calculated using a modified Gierer-Wirtz equation [START_REF] Evans | [END_REF] 4 Solubility parameters were obtained from HsPiP estimation [START_REF] Hansen | Hansen Solubility Parameters: A User's Handbook[END_REF] except for ToABr [39].

a) Study of the retention of ToABr

The active layer of PERVAP4060 is a dense layer of crosslinked PDMS approximately 1 to 2 microns thick. Despite the thickness and density of this layer, under OSN conditions, PERVAP4060 allowed fairly high toluene permeance of about 2 L m -2 h -1 bar -1 (Table 3). Note that while this was the most frequently obtained value, higher values were measured for some coupons without a reduction in retention. This can be explained by variation in the thickness of the active layer from one membrane sample to another without invoking any compaction phenomena. Indeed, for a given coupon, no flux hysteresis was observed when the pressure was varied from 1 to 40 bar (Figure 4). The high permeance was in good agreement with the well-known affinity of dimethyl siloxane networks with toluene; toluene is a low-polarity aromatic solvent, and the active layer is a rubbery polymer that exhibits significant swelling in toluene. The solubility parameters (δ i ) of PDMS and toluene are quite similar: 15.4 MPa 1/2 and 18.2 MPa 1/2 , respectively. MPF 60 toluene 3 0.2 to 1.9 (25 °C) 48 to 86 [31] MPF 60 MeOH 0.3 0.13 (30 °C) 98 [18] As mentioned above, the permeance was stable at pressures up to 40 bar, indicating that increased pressure does not have any effect on the swelling of the dense layer as previously reported [14]. Moreover, as PERVAP4060 has a composite structure with three layers, i.e., polyethylene terephthalate (PET) non-woven fibers as a mechanical support, polyacrylonitrile (PAN) as an ultrafiltration support, and PDMS as the top layer (Figure 2 a,d ,e) the steady i SI units are J 1/2 m -3/2 , equivalent to M Pa 1/2 permeance also indicates that this structure has good mechanical resistance that prevents any significant compaction phenomena at pressures of up to 40 bar.

Conversely, the permeance of EtOH was approximately ten times lower than that of toluene.

The much higher solubility parameter of EtOH, δ = 26.5 MPa 1/2 , qualitatively explains this result. As shown in Table 3, these results are in good agreement with those obtained by Stamatialis [24] using a composite PDMS-PEO membrane: both the flux and retention are high under analogous experimental conditions. These results demonstrate the good performance of PERVAP4060, which combines high permeance and retention above 92% in toluene and 95% in EtOH. Previous data reported for commercial PDMS-based membranes (MPF series)

showed highly variable retention and permeance values in toluene, ranging from 48% to 100% and 0.2 to 1.9 L m 2 h -1 bar -1 , respectively. Clearly, the retention of ToABr from alcoholic feed solutions was superior for both the commercial MPF membranes and PERVAP4060 [18] [31],

but the permeance in MPF50 was at least 10 times lower. On the other hand, the STARMEM PI-based membrane series showed promising ToABr retention according to the literature data given in Table 1; unfortunately, for technical reasons, these membranes are no longer available.

b) Retention of diphosphine ligand R-BINAP

The results obtained using BINAP as a dilute solute in toluene are presented in Figures 567, which show the effect of the applied pressure on the flux increase, the effect of the applied pressure over time on the OSN flux and BINAP retention, and the effect of temperature, respectively.

Figure 5 shows the OSN fluxes and retention values obtained after the conditioning procedure (feed crossflow 7-10 Kg/h, 15-20 min at each TMP in the range of 0-40 bar). Under these conditions, the retention of R-BINAP was almost constant and was independent of the applied pressure for pressures of up to 40 bar, reaching an average value of 80 ± 1%. The permeate fluxes increased steadily with the applied transmembrane pressure, corresponding to permeance of ≈2.3 L m -2 h -1 bar -1 , i.e., the same value as obtained previously using ToABr as the solute. Even though the two solutes should obviously have distinct mass transfer coefficients due to their different solubility parameters and molecular sizes (Table 2), because their molar concentrations are very low, the permeate solute flux respectively remains very low compared to the solvent flux. In the case of R-BINAP, a large neutral aromatic phosphine solute, a difference in its mobility in the PDMS network must be the main reason for the retention. These results also indicated that no significant compaction phenomena occurred with an increase in pressure. In Figure 7, it can be seen that for all the studied temperatures, the flux increased almost linearly with the pressure, leading to a very high flux of 180 L m -2 h -1 at 50 °C and 40 bar. The steady increase in the flux with an increase in pressure clearly indicates that the composite membrane was highly stable in the range from 30 to 50 °C: no apparent compaction or flux limitation related to the porous structure was observed. Taking into account the solutiondiffusion mechanism through the dense active layer, and knowing that the sorption of toluene decreases slightly with temperature, (Ea ≈ -7.3 J mol -1 ) [35], the strong increase in the flux is clearly related to the increase in the diffusion coefficient of toluene. The effect of temperature was then investigated using dilute feed mixtures of 0.05 wt% R-BINAP in toluene at a transmembrane pressure of 10 bar. Data were obtained for three temperatures, 30, 35, and 40 °C, and are given in Table 4. First, the retention of R-BINAP, i.e., R ≈ 80%, was not altered by the increased temperature, while the flux more than doubled between 30 and 40 °C. This phenomenon is striking because normally in membrane separations, a tradeoff between selectivity and permeance is observed, with a strong decrease in selectivity (or retention) occurring when the permeance is increased for any reason (temperature, pressure, or membrane thickness). Once again, these results attest to the fact that the mass transfer of toluene and that of the solute were apparently fully independent, despite the active layer being highly swollen by toluene.

In membrane separation, when the mass transfer is increased by temperature or by a pressure effect applied at the upside stream of the membrane, some coupling phenomena is often observed that induces of loss of selectivity. With R-BINAP, the increase in temperature did not induce this phenomenon. Thus it means that In the swollen PDMS active layer, the higher toluene flux due to an increase of its diffusion coefficient did not induce a significant increase of the convective force towards the solute. Hence the mass transfer of R-BINAP is not modified by the toluene mass transfer due to the increased temperature, that keeps the same ratio of solvent and solute in permeate, resulting to a constant rejection of R-BINAP from toluene.

Moreover, for porous NF membranes, the opposite situation is usually observed: with an increase in temperature, the molecular cut-off increases, leading a strong reduction in the retention values. This can be explained by an increase in the mean pore size [36].

Second, the results also indicated that the total OSN flux was unchanged compared to that of the pure solvent series, which in turn demonstrated that the high retention of R-BINAP did not influence the solvent flux and that no significant polarization concentration effect occurred during the experiment. Two factors contributed to this result: first, the concentration of R-BINAP was rather low, and the relative increase in its concentration at the membrane interface could not induce significant osmotic pressure; second, as the permeate was systematically recycled to the upstream reservoir, the average concentration of the solute could not increase in the feed.

The increase in the flux with temperature was not linear but instead followed a power law.

This effect is well-known in gas permeation and pervaporation but has rarely been studied in OSN [37]. Figure 8 shows the effect of temperature on the increase of the OSN flux using the Arrhenius law:

ln(𝐽) = 𝐴 -𝐸𝑎 𝑅𝑇
where J has units of mol m -2 h -1 , Ea is the activation energy in J/mol, and R is 8.3141 J mol -1 K - 1 . Both the data obtained for pure toluene and the binary mixtures were used. In the feed mixture, the concentration of BINAP was below 0.05 wt%, and as discussed in the previous paragraph, the OSN flux was the same with and without diphosphine ligand R-BINAP. -First, at higher pressure there is an effect of compaction that affects the porous support layer and hence limits the overall mass transfer;

-Second, as the mass transfer increased a lot at 40bars, the porosity of the support becomes a physical barrier to the mass transfer and so an additive resistance.

The hypothesis of compaction at 50 °C is unlikely; if any compaction does occur, it seems to be fully reversible, that is fairly not likely. On the other hand, as mentioned above, the sorption of toluene into the PDMS layer is known to be exothermic [35]. Hence, the higher the temperature is, the higher the decrease in sorption. This effect might partially explain the observed phenomenon. Also, such phenomena may occur when the polymer network is in an unsteady state or can rearrange. For PERVAP 4060, the active layer, PDMS, is a chemically crosslink rubbery network and it is unlikely for this network to get a morphological change that would decrease the mass transfer. However, mass transfer can also be dependent on the other sublayer, which supports the active layer. Indeed, as the mass transfer increases sharply at 40bars between 30 and 50°C, i.e., 80% more, the support itself may become an additive resistance, limiting the overall transmembrane flux.

In conclusion, the combined effect of pressure and temperature strongly increased the OSN solvent flux, while the retention of the solute remained constant.

Looking through OSN literature, the determination of Ea has been reported by (Machado, 1999) for acetone with MPF membranes, giving Ea= 1.1kJ at 30bar.

Usually, the relationship between the flux increase and the temperature is explained in terms of a higher polymer chains mobility and a higher diffusion coefficient of the solvent when the permeation occurs through a dense selective layer. In the present case, having a highly swollen membrane due to toluene, it is interesting to compare the Ea of toluene linked to OSN to the energy of activation (Eµ) only linked to the relationship between the solvent viscosity and the temperature, as calculated by Messaâdi [38]. Hence it should be underlined that Eµ (9.2 kJ/mol) is much lower than Ea (26kJ/mol at 40bar) for toluene in PDMS. Once more, this result shows that the transport mechanism through the membrane is far from a viscous flow, even with a highly swollen polymer network. Machado [37] made the same observation in his work with acetone and MPF50 (Eµ= 6.8 vs Ea = 13.2 kJ/mol) [37].

d) Effect of dilution on the retention of diphosphine ligand BINAP in toluene in the range 0.0001-0.2 wt% OSN experiments were carried out both at lower and higher R-BINAP concentrations than the reference concentration of 0.05 wt%. The lower concentrations were easily prepared by dilution with an additional solvent and controlled using an external standard by GC.

Calibration with an external standard was necessary at the very low concentration of 100 ppm. The results are shown in Figure 9. In Figure 10, the influence of varying the concentration of the linear C16 on the OSN flux and the retentions of R-BINAP and C16 is shown. Interestingly, the retention of R-BINAP remained almost constant at 80%, with only a slight decrease (77%) occurring at the highest concentration of C16. A similar observation can be made for C16; its retention slightly decreases. The difference between R-BINAP and C16 can be explained by the higher diffusion coefficient which is in relation with the lower molecular weight of the aliphatic solute (226 g) compared to that of R-BINAP (622 g) and with the correspondingly lower C16 molar volume (Table 2). Another potentially relevant parameter is the lower solubility parameter of C16 compared to that of R-BINAP, which favors its sorption in the active PDMS layer (≈1).

Finally, the results show that the global OSN flux was markedly increased by the presence of the aliphatic solute, up to about 15% at a C16 feed concentration of 10 wt%. Aliphatic solute contributes to increasing the swelling of the active layer of the membrane, which favors, in turn, the increase of the global-flux of the membrane. Clearly, this flux increase was greater than the simple flux contribution of the linear hydrocarbon.

Moreover, from a process point of view, these results indicate that the OSN method allows easy separation of the linear C16 molecule from R-BINAP in a toluene feed mixture. This is a promising result for its application in olefin metathesis.

CONCLUSION

The retentions of the tested solutes, phase transfer catalyst ToABr and diphosphine ligand R-BINAP, were high even at high solute dilutions in toluene, with values of up to 92% and 80%, respectively. Despite the significant swelling of the PDMS active layer in toluene, there was no indication that the mass transfer obeyed a pore flow mechanism. Conversely, all the results obtained indicate that a solution-diffusion mechanism seems to prevail.

In summary, the main findings related to the use of PERVAP4060 in OSN in this work are:

-The stability of the composite membrane was shown to be excellent under the range of pressures tested (10 to 40 bar), regardless of the degree of solvent-induced swelling of the active layer, i.e., with both ethanol and toluene. A linear increase in the OSN flux was recorded over the tested pressure range at temperatures of up to 50 °C without any hysteresis effect.

-The retention of dilute solutes (0.05 wt%), such as ToABr and R-BINAP, which have molecular weights of 546 and 622 g, respectively, were above 80% for the neutral aromatic solute and above 92% for the alkyl ammonium salt. This demonstrates that the retention of the solutes was clearly not related to their molecular weights (or molar volume), but was more likely related to the relative affinity of the solute for the membrane active layer and, perhaps most importantly, to the solute mobility.

-In the range of dilutions studied (100 ppm to 0.2 wt%) in the toluene feed mixtures, the retention of R-BINAP was constant (80%). No coupling effect could be detected.

-The OSN flux followed an Arrhenius law with an increase in feed temperature. The energy of activation at 10 bar was higher than at 40 bar, while the retention remained steady. The effect looks very interesting in terms of application.

-Finally, it was shown that a ternary mixture of the solutes R-BINAP and linear C16 in toluene could easily be fractionated. Most of the C16 alkane was eliminated through the membrane, while the R-BINAP was mainly retained in the feed.

These results highlight the promising OSN potential of PERVAP4060 for the rejection of dilute solutes in metathesis synthesis. All the obtained data were in good agreement with a simple solution-diffusion mechanism through the composite membrane. The high retention level of the R-BINAP solute remained steady even at high dilution. Apparently, the transports of the solute and solvent were not coupled. [24] MPF 60 toluene 3 0.2 to 1.9 (20-25 °C) 48 to 86 [31] MPF 60 MeOH 0.3 0.13 (30 °C) 98 [18] Table 3 Revised Click here to access/download;Table ;Table 3R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 1 :

 1 Figure 1: Characterization of the Sulzer PERVAP composite membrane by SEM and confocal microscopic images: (a) Cross-sectional view of the membrane (total thickness 200-220 µm). (b) High-resolution image of the PDMS surface. (c) The cross-sectional view of the active layer (PDMS, thickness 1-2 µm). (d) Top view of the PAN porous sub-layer (25-30 µm). (e) PET support layer underneath the PAN sub-layer (170-190 µm).

  was used. The setup consisted of a rectangular cross-flow cell (GE Osmonics) able to withstand pressures of up to 70 bar. The cell was used in tangential crossflow mode, in which the pressure, feed flow rate, and temperature of the feed can be controlled well. (Figure 2 a).

Figure 2 :

 2 Figure 2: (a) Scheme of the OSN set-up. (b) Digital pressure control system.



  Column: HP-5 phenyl methyl siloxane. Capillary dimensions: 15 m × 320 µm × 0.25 µm. Oven program: R-BINAP: 325 °C, held for 17 min for R-BINAP using tetratetracontane as the external standard. Retention of R-BINAP at around 13-14 min and retention of the external standard at around 6 min. The calibration and an example chromatogram are provided in the Appendices A, B. ToABr: 200° C, held for 10 min for ToABr using n-tetracosane (C24H50) as the external standard. Retention of ToABr at around 6 min and retention of the external standard at around 8 min. The calibration and an example chromatogram are provided in the Appendices. n-Hexadecane and R-BINAP: 200° C, held for 2 min for n-hexadecane (C16H34), then increased to 325 °C at a rate of 50 °C per minute and held for 17 min to detect R-BINAP. The calibration is given in Appendices B.

Figure 3 :

 3 Figure 3: Schematic representations of diphosphine ligand R-BINAP, Ru-BINAP and phase transfer catalyst ToABr.

Figure 4 :

 4 Figure 4: Pure solvent fluxes of EtOH and toluene through PERVAP6040. Deviation ± 5%

Figure 5 :

 5 Figure 5: OSN performance of PERVAP4060 for the retention of R-BINAP from a toluene feed solution in the range 1-40 bar. R-BINAP: 0.05 mass%. Note that the J & R% values at different TMP correspond to the flux and retention measured after the conditioning procedure. Continuous black line: OSN permeates flux values. Redline: retention values. Deviation ± 5%.

Figure 6

 6 Figure6shows the OSN fluxes and retention values obtained after several hours of continuous OSN operation at transmembrane pressures of 10 and at 20 bar. To maintain a constant feed concentration, the permeate flux was directly recirculated to the feed reservoir. Under these conditions, the retention of diphosphine ligand R-BINAP was almost constant (80%) and independent of the applied pressure. The permeate fluxes were steady with smooth oscillations related to the temperature and pressure regulation. When the experiments were repeated after 15 or 55 hours, the same OSN fluxes were obtained, and the same selectivity was maintained. These experiments showed that the composite membrane was highly stable in the feed mixture, and still gave reproducible results after 4 days.

Figure 6 :

 6 Figure 6: Effect of the applied pressure over time on the OSN flux and R-BINAP retention. Note that the J & R% values at zero correspond to the flux and retention measured after the conditioning procedure (feed crossflow 8 Kg/h ± 20%, 15-20 min steady results at each studied transmembrane pressure in the range of 0-40 bar).

Figure 7 :

 7 Figure 7: Effect of temperature on the pure toluene fluxes in the OSN system. Deviation ± 5%.

Figure 8 :

 8 Figure 8: Arrhenius plot of the OSN flux data obtained for PERVAP4060. NB: as the R-BINAP concentration was very low (<0.05 wt%), the solvent flux has been assimilated to the total OSN flux. Deviation of temperature: ± 2°C. The trends at 10 bar and 40 bar were almost the same in the 30-40 C° range, but a relative flux decline occurred in the 40-50 °C range. Therefore, the regression coefficients (Rc) are below 0.9. In the range 30-40 °C, the observed experimental data exhibit a better linear trend (Rc > 0.97). The calculated Ea values at 10 and 40 bar were 34 kJ/mol and 26 kJ/mol, respectively. As expected, the highest Ea value was observed at 10 bar. It was well controlled that the flux decline recorded at 50 °C was not due to measurement accuracy. Moreover, no hysteresis was observed, and the previously measured values at 30 °C were easily reproduced after the series of experiments at 50 °C. Hence, the decline in the flux at 50 °C was the result of a specific phenomenon that is not yet clearly understood (Appendices D). Two potential explanations can be suggested:

Figure 9 :

 9 Figure 9: Evaluation of the effect of the concentration of the solute in toluene on its retention by PERVAP4060 (10 bar, 30 °C, concentration range: 0.0001-0.2 wt%). Deviation of rejection data: ± 2%.

Figure 10 :

 10 Figure 10: OSN performance of PERVAP4060 for the separation of a model ternary mixture consisting of C16 (1 to 10 wt%) and R-BINAP (0.05 wt%) in toluene (10 bar, 30 °C). Deviation of J: ± 5%.

Appendice C .

 . Calibration of the GC column for R-BINAP and C16 ternary mixture. Arrhenius plot excluding data at 50 °C.

Figure 1 :

 1 Figure 1: Characterization of the Sulzer PERVAP composite membrane by SEM and confocal microscopic images: (a) Cross-sectional view of the membrane (total thickness 200-220 µm). (b) High resolution image of the PDMS surface. (c) Cross-sectional view of the active layer (PDMS, thickness 1-2 µm). (d) Top view of the PAN porous sub-layer (25-30 µm). (e) PET support layer underneath the PAN sub-layer (170-190 µm).

Figure 1

 1 Figure 1 Click here to access/download;Figure;Figure 1_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 2 :

 2 Figure 2: (a) Scheme of the OSN set-up. (b) Digital pressure control system.

Figure 2 Figure 3 :

 23 Figure 2 Click here to access/download;Figure;Figure 2_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 3

 3 Figure 3 Click here to access/download;Figure;Figure 3_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 4 :

 4 Figure 4: Pure solvent fluxes of EtOH and toluene through PERVAP6040 (deviation ± 5%).

Figure 4

 4 Figure 4 Click here to access/download;Figure;Figure 4_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure A2

 A2 Figure A2 Click here to access/download;Figure;Figure A2_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure A3

 A3 Figure A3 Click here to access/download;Figure;Figure A3_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure A4

 A4 Figure A4 Click here to access/download;Figure;Figure A4_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 7 :

 7 Figure 7: Effect of temperature on the pure toluene fluxes in the OSN system. Deviation ± 5%.

Figure 7 Revised

 7 Figure 7 Revised Click here to access/download;Figure;Figure 7R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 8 :

 8 Figure 8: Arrhenius plot of the OSN flux data obtained for PERVAP4060. NB: as the R-BINAP concentration was very low (<0.05 wt%), the solvent flux has been assimilated to the total OSN flux. Deviation of temperature: ± 2°C.

Figure 8 Revised

 8 Figure 8 Revised Click here to access/download;Figure;Figure 8R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 9 :

 9 Figure 9: Evaluation of the effect of the concentration of the solute in toluene on its retention by PERVAP4060 (10 bar, 30 °C, concentration range: 0.0001-0.2 wt%). Deviation of rejection data: ± 2%.

Figure 9 Revised

 9 Figure 9 Revised Click here to access/download;Figure;Figure 9R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 10 :

 10 Figure 10: OSN performance of PERVAP4060 for the separation of a model ternary mixture consisting of C16 (1 to 10 wt%) and R-BINAP (0.05 wt%) in toluene (10 bar, 30 °C). ). Deviation of J: ± 5%.

Figure 9 Revised

 9 Figure 9 Revised Click here to access/download;Figure;Figure 10R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 5 :

 5 Figure 5: OSN performance of PERVAP4060 for the retention of R-BINAP from a toluene feed solution in the range 1-40 bar. R-BINAP: 0.05 mass%. Note that the J & R% values at different TMP correspond to the flux and retention measured after the conditioning procedure. Continuous black line: OSN permeate flux values. Red line: retention values. Deviation ± 5%.

Figure 5 Revised

 5 Figure 5 Revised Click here to access/download;Figure;Figure 5R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Figure 6 :

 6 Figure 6: Effect of the applied pressure over time on the OSN flux and R-BINAP retention. Note that the J & R% values at zero correspond to the flux and retention measured after the conditioning procedure (feed crossflow 8 Kg/h ± 20%, 15-20 min at each TMP in the range of 0-40 bar).

Figure 6 Revised

 6 Figure 6 Revised Click here to access/download;Figure;Figure 6R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Table 1 :

 1 Literature overview of the retention of BINAP and ToABr catalysts by OSN.

	Membrane	Feed	Solutes	Flux	Retention	Reference
	(active layer)	T (°C), pressure (bar)	wt%	Lm -2 h -1	%
	MPF60	MeOH, 30 °C, 15 bar	0.3% Ru-BINAP	~2	98	[18]
	MPF50	MeOH, 30 °C, 16 bar	0.03% Ru-BINAP	NA	70	[20]
	MPF 50	THF, 30 °C, 25 bar	0.04% Pd-BINAP	166	95.6	[19]
	Starmem 122	THF, 30 °C, 25 bar	0.04% Pd-BINAP	93.6	100	[19]
	Starmem 240	EA, 30 °C, 25 bar	0.04% Pd-BINAP	150.9	95.6	[19]
	Starmem 122	MeOH + ionic liquids (0.01-10	0.0008% Ru-	NA	95-99.9	[23]
		wt%), 35 °C, 20 bar	BINAP
	Starmem 122	MeOH, 30 °C, 30 bar	0.005% Ru-BINAP	40	>97.5	[10]
	Graph.Oxide	MeOH, rt, 5 bar	0.001% Ru BINAP	350	98	[27]
	MPF50	Toluene, 30 bar	3% ToABr	19	48	[2]
	Starmem122	Toluene, 30 bar	3% ToABr	14	>99	[28]
	MPF 50	MeOH, 20 °C, 30 bar	0.3% Quats	NA	~95	[29]
	PDMS-PEO	Toluene, 24 °C, 10 bar	8% ToABr	~16	100	[24]
	Starmem 122	Toluene, 30 °C, 30 bar	20% ToABr	~ 33	100	[25]
	Starmem 122	Toluene, 30 °C, 30 bar	20% ToABr	~35	98	[26]
	Desal 5	Toluene 20 °C, 30 bar	3% ToABr	4	62	[30]
	Starmem122	Toluene, 20-23 °C, 30 bar	3-20% ToABr	70	93-97	[31]
	Starmem122	Toluene and MeOH mixtures,	~0.2% ToABr	70	93	[32]
		22 °C, 30 bar

Table 2 :

 2 Despite the fairly good results shown inTable1, Starmem and MPF membranes are no longer commercially available.Table2provides information relevant to the feed solutions used for OSN with the commercial membrane PERVAP4060 in this study: EtOH solutions of ToABr (≈0.05 wt%) and toluene solutions of R-BINAP (≈0.05 wt%). C16 has been used as a simple model of an aliphatic linear product that can be produced by metathesis. Some specifications of the used chemicals

	Material	MW	Molecular	Molar	Diffusion	Diffusion	Solubility
		g/mol	diameter	volume 2	coefficient 3	coefficient 3	parameter 4
			(nm) 1	cm 3 mol -1	(m 2 s -1 ) × 10 +11	(m 2 s -1 ) × 10 +11	MPa 1/2
					in toluene	in PDMS
	R-BINAP 622.7 NA	511	9.18	3.74	21.5
	ToABr	546	NA	761	9.75	4.07	21.9
	C16	226	0.845	294.1	14.9	7.26	15.9
	Toluene 92.1	0.56	106.8	24	13.1	18.2
	EtOH	46	0.52	58.5	26.4	1.7	26.5

Table 3 :

 3 Solvent permeance and retention of ToABr by OSN from dilute toluene and EtOH feeds (10 bar, toluene, EtOH).

	Membrane	Solvent ToABr	Permeance ±5%	ToABr	Reference
			wt%	L m -2 h -1 bar -1	Retention %±0.5
	PERVAP4060 toluene 1	2.2 (30 °C)	93.5
	PERVAP4060 toluene 0.05	2.2 (30 °C)	93
	PERVAP4060 toluene 0.1	2.2 (30 °C)	92.5
	PERVAP4060 toluene 0.001 2.2 (30 °C)	93
	PERVAP4060 EtOH	0.05	0.35 (30 °C)	95	This work
	PERVAP4060 EtOH	0.1	0.35 (30 °C)	95.6
	PDMS-PEO	toluene 8	1.6 (24 °C)	100	[24]

Table 4 :

 4 Effect of temperature on the OSN flux and diphosphine ligand R-BINAP retention at

	10 bar. Feed: 0.05% R-BINAP -PERVAP4060
	Temperature (°C)	Total flux	R-BINAP retention
		J (L m -2 h -1 ) ± 10%	0.05 wt% ±2%
	30	21	80
	35	36	81

Table 1 :

 1 Literature overview of the retention of BINAP and ToABr catalysts by OSN

	Membrane	Feed	Solutes	Flux	Retention	Reference
	(active layer)	T (°C), pressure (bar)	wt%	L m -2 h -1	%
	MPF60	MeOH, 30 °C, 15 bar	0.3% Ru-BINAP	~2	98	[18]
	MPF50	MeOH, 30 °C, 16 bar	0.03% Ru-BINAP	NA	70	[20]
	MPF 50	THF, 30 °C, 25 bar	0.04% Pd-BINAP	166	95.6	[19]
	Starmem 122	THF, 30 °C, 25 bar	0.04% Pd-BINAP	93.6	100	[19]
	Starmem 240	EA, 30 °C, 25 bar	0.04% Pd-BINAP	150.9	95.6	[19]
	Starmem 122	MeOH + ionic liquids (0.01-10	0.0008% Ru-	NA	95-99.9	[23]
		wt%), 35 °C, 20 bar	BINAP
	Starmem 122	MeOH, 30 °C, 30 bar	0.005% Ru-BINAP	40	>97.5	[10]
	Graph.Oxide	MeOH, rt, 5 bar	0.001% Ru BINAP	350	98	[27]
	MPF50	Toluene, 30 bar	3% ToABr	19	48	[2]
	Starmem122	Toluene, 30 bar	3% ToABr	14	>99	[28]
	MPF 50	MeOH, 20 °C, 30 bar	0.3% Quats	NA	~95	[29]
	PDMS-PEO	Toluene, 24 °C, 10 bar	8% ToABr	~16	100	[24]
	Starmem 122	Toluene, 30 °C, 30 bar	20% ToABr	~ 33	100	[25]
	Starmem 122	Toluene, 30 °C, 30 bar	20% ToABr	~35	98	[26]
	Desal 5	Toluene 20 °C, 30 bar	3% ToABr	4	62	[30]
	Starmem122	Toluene, 20-23 °C, 30 bar	3-20% ToABr	70	93-97	[31]
	Starmem122	Toluene and MeOH mixtures,	~0.2% ToABr	70	93	[32]
		22 °C, 30 bar

a) MPF: PDMS active layer; b): STARMEM: polyimide top layer

Table 1

 1 Click here to access/download;Table;Table 1 OSM Morshed.docx

Table 4 :

 4 Effect of temperature on the OSN flux and diphosphine ligand R-BINAP retention at 10 bar (Feed: 0.05% R-BINAP, PERVAP4060)

	Temperature (°C)	Total flux	R-BINAP retention
		J (L m -2 h -1 ) ± 10%	0.05 wt% ± 2%
	30	21	80±2
	35	36	81±1
	40	47	79±2

Table 4 Revised

 4 Click here to access/download;Table;Table4R_M.MORSHED-PDMS-BINAP-OSN-toluene.docx

Table 3 :

 3 Solvent permeance and retention of ToABr by OSN from dilute toluene and EtOH feeds (10 bar, toluene, EtOH)

	Membrane	Solvent ToABr	Permeance ±5%	ToABr	Reference
			wt%	L m -2 h -1 bar -1	Retention
					%±0.5
	PERVAP4060 toluene	1	2.2 (30 °C)	93.5	This work
	PERVAP4060 toluene	0.05	2.2 (30 °C)	93	This work
	PERVAP4060 toluene	0.1	2.2 (30 °C)	92.5
	PERVAP4060 toluene 0.001	2.2 (30 °C)	93	This work
	PERVAP4060 EtOH	0.05	0.35 (30 °C)	95	This work
	PERVAP4060 EtOH	0.1	0.35 (30 °C)	95.6	This work
	PDMS-PEO	toluene	8	1.6 (24 °C)	100

Acknowledgments

This work was achieved in the frame of a collaborative project, ANR-14-CE06-0022, thanks to the financial support of the French National Research Agency and the support of ARKEMA.

Professor S. Abbott is also greatly acknowledged for discussion about the Hansen solubility parameters of R-BINAP and ToABr.

2 Molar volumes calculated using HSPiP [START_REF] Hansen | Hansen Solubility Parameters: A User's Handbook[END_REF] except for that of ToABr [26]. 3 Diffusion co-efficient of toluene and ethanol [14] Other diffusion co-efficient values were calculated using a modified Gierer-Wirtz equation [START_REF] Evans | [END_REF]. 4 Solubility parameters were obtained from HsPiP estimation [START_REF] Hansen | Hansen Solubility Parameters: A User's Handbook[END_REF].