Athanassios K Boudalis

Guillaume Rogez

Benoît Heinrich

Raphael G Raptis

Philippe Turek

Towards ionic liquids with tailored magnetic properties: bmim + salts of ferro-and antiferromagnetic Cu II 3 triangles

Complexes (bmim) 2 [Cu 3 (μ 3 -Cl) 2 (μ-pz) 3 Cl 3 ] (1), (bmim)[Cu 3 (μ 3 -OH)(μ-pz) 3 Cl 3 ] (2) and (bmim) 2 [Cu 3 (μ 3 -OH)(μ-Cl)(μ-pz) 3 Cl 3 ] (3) were synthesized (bmim + = 1-butyl-3-methylimidazolium). Dianionic complexes 1 and 3 were obtained as crystalline solids, whereas the monoanionic complex 2 was obtained as a viscous paste. Magnetic susceptibility and X-band EPR studies revealed intramolecular ferromagnetic interactions for 1 with small magnetoanisotropy in its ground state (D 3/2 ~ 10 -3 cm -1

) and intramolecular antiferromagnetic interactions for 2 and 3 (-285 and -98 cm -1 average J, respectively) with important magnetic anisotropy in their ground states stemming from a combination of low magnetic symmetry and antisymmetric exchange interactions. Thermal studies revealed a clear melting point of 140 °C for 1, which is lower than that of its PPN + and Bu 4 N + analogues (1PPN and 1Bu 4 N, respectively, PPN + = bis(triphenylphosphine)iminium). Upon cooling, 1 remains molten down to 70 °C. Mixtures of the salts 1, 1PPN and 1Bu 4 N, exhibited modified melting behaviours, with the mixtures exhibiting lower melting points than those of either of their pure components. 2 | J. Name., 2012, 00, 1-3 This journal is

Introduction

Ionic liquids (ILs) constitute an exciting class of materials which has attracted wide interest over the past two decades, with applications ranging from reaction media to lubricants and many more. 1 While Al III salts were among the first ILs, 2 metalcontaining ILs (MCILs) constitute a relatively small fraction of those reported to date. Among those, MCILs containing paramagnetic ions constitute an even smaller class; after the initial explosion of this domain in the 1990s, it was only in 2001 that (bmim) [FeCl 4 ] was reported and properly identified as an IL. 3 The discovery that this salt becomes a magnetorheological fluid under weak magnetic fields gave a momentum to the study of magnetic MCILs, 4,5 which was further enhanced by the observation that this behaviour is reproduced by Dy III -based MCILs. 6 Interestingly, studies on paramagnetic MCILs predate those works, but were focused on other aspects of the materials, disregarding their magnetic properties. 7,8 Subsequent to these studies, the magnetic properties of MCILs started attracting more attention, with reports of MCILs containing mononuclear magnetic cations, [9][10][11][12][13][14][15][16] mononuclear magnetic anions [17][18][19][20][21][22][23][24][25] and one report on the magnetic properties of a triferric cationic MCIL. 26 Due to the mononuclear structures of the spin carriers in those magnetic MCILs, the tuning of their magnetic properties, when attempted, focused on modifications of the diamagnetic counterion; e.g., it was demonstrated that changing the countercation charge, two or three [FeCl 3 Br] -anions could be assembled around it, yielding a higher magnetic moment per formula unit. 27 In another approach, modifications to the coordination sphere induced vapochromic transitions from diamagnetic to paramagnetic in a Ni II MCIL. 13 Due to the mononuclear structure of most MCILs, the surest way of achieving significant modifications of their magnetic properties is changing the metal in the spin-carrying ion altogether. 19 Modifications of ligand side-groups may affect certain electronic properties, such as UV-Vis spectra, but not the intrinsic magnetic properties. Moreover, those intrinsic properties concern isolated paramagnetic ions and therefore preclude magnetic behaviours that stem from magnetic exchange interactions (e.g., ferro-or antiferromagnetism). Previous studies with pyrazolate ligands have shown that they exhibit a rich coordination chemistry with Cu II , leading to a series of trinuclear complexes. Furthermore, it has been shown that the structure and intrinsic magnetic properties of these complexes can be systematically modified through pH control; in a series of such complexes containing Cu II 3 cores the magnetic coupling varied systematically from ferromagnetic to weakly-, to strongly antiferromagnetic. 28 These complexes being anionic, the possibility emerged that combining them with bulky countercations might lead to ILs. Since the magnetic properties of the tricopper anions can be

Results and discussion

Synthesis of complexes

The complexes were prepared according to the published procedure for the analogous PPN + [PPN + = bis(triphenylphosphine)iminium] and Bu 4 N + salts (Scheme 1), 28 with the driving factors being the solution pH and the stoichiometric excess of the added countercation salt, in this case bmimCl. In the case of 1 and 2, the reactions led to the same complex anions as in the previously published procedures, however, in the case of 3, instead of the expected {Cu 3 (μ 3 -O)} 4+ , the similar {Cu 3 (μ 3 -OH)(μ-Cl)} 4+ core of the same total charge was isolated in crystalline form.

Scheme 1. The molecular structures of the cations mentioned in the text It is noteworthy that whereas both dianionic complexes 1 and 3 are obtained as crystalline solids, the monoanionic 2 is obtained as a viscous paste, confirmed by powder X-ray diffraction to be amorphous (Figure S1). This is attributed to the fact that the electrostatic forces in the dianionic complexes are stronger, thus stabilizing crystalline solids at ambient temperatures. However, those forces will be weaker in the case of 2, thus leading to a liquid product at room temperature.

Description of structures

Complex 1 consists of a triangular complex anion held together by three μ-pz -ligands approximately coplanar with the Cu 3plane, and two μ 3 -Cl -ions situated above and below the Cu 3 plane (Figure 1). The structure of the anion is essentially that of the PPN and Bu 4 N analogues, 1PPN and 1Bu 4 N, 28 and will not be described in detail. The only salient point is the crystallographic disorder of atom Cl2.

As far as the two bmim + cations are concerned, it is noteworthy that the butyl group of one is in the gauche conformation around bond C4B-C5B, thus adopting a gaucheanti conformation, while that of the other is in the anti-anti conformation (Figure S2). Regarding the bmim + cations, a situation similar to the case of 1 is observed, with one n-butyl chain being in a gauche conformation around bond C4A-C5A, thus adopting a gaucheanti conformation, while the other adopting an anti-anti conformation.

The anions of complex 3 participate in a H-bonded network through the chloro terminal ligand Cl3 and the hydroxo proton H10, forming 1D zig-zag chains (Figure S3).

Melting point determinations

The melting point for complex 1 was visually determined in a glass capillary using a melting point apparatus (Table 1). This was compared to the melting points of previously reported complexes 1PPN and 1Bu 4 N.

Please do not adjust margins

Please do not adjust margins Moreover, the melting points of equimolar binary mixtures of the three salts were determined, with the mixtures being prepared by thorough grinding of the two solids. These studies indicate that the countercation influences the melting point of the salt, resulting in a ~60 °C lower melting point of the bmim + salt (1). Binary mixtures also lead to lowering of the melting point, not only when they contain the bmim + salt, but also in the case of the PPN + /Bu 4 N + mixture, which melts 30-40 °C below its constituent salts.

TGA and DSC studies

The thermal stability and the phase behaviour of the complexes were investigated by TGA, DSC and polarising optical microscopy (POM). Figure 4. DSC traces upon heating (red: first heating; orange: second heating) and cooling (blue) for complex 1. The three traces above were carried on below 100°C and illustrate the irreversibility of the endothermic event at 53°C, attributed to a solid-solid phase transition. The melting transition at 140°C was crossed in the traces below, and the ionic liquid was found to crystallize on cooling.

Complex 1. TGA studies revealed that complex 1 is stable up to 150 °C and rapidly decomposes with weight loss above 160-170°C (Figure 3). DSC and polarizing optical microscopy (POM) revealed an irreversible endothermic process around 53 °C, corresponding to solid-solid phase transition (Figure 4). The complex then melts at 140 °C as indicated by an endothermic process which coincides with the visually observed melting temperature to ionic liquid phase. The crystallization upon cooling was observed around 70 °C, for a rate of 5 °Cmin -1 .

Complexes with the same anion as 1. Since the anion of complex 1 can crystallize with different countercations, we became interested in studying the effect of the countercation on the thermal stability and phase behavior of the salts. TGA studies on the PPN analogue 1PPN showed higher stability, above 170 °C, and a 60 °C increase of the melting temperature. The weight loss is however only displaced by 30-40 °C and now practically coincides with the melting transition, revealed in DSC scans by a steep endothermic process at 205°C agreeing with the transition temperature and states visually determined by POM (Figure 5). Prior to melting, a series of minor peaks are observed in the 80-180°C range of the first heating DSC curve, which originates from structural rearrangements in the crystalline state. The Bu 4 N + analogue of complex 1, 1Bu 4 N, shows a sharp weight loss at 62°C TGA curves (~17 to 26%, depending on the batch) due to the release of co-crystallized solvent (Figure S4). 1Bu 4 N, obtained solvent-free trough preliminary heating to 100°C, showed weight loss due to decomposition above 175°C. DSC experiments were thus not possible above the range of solid-solid transitions (Figure 6), but thermal degradation was sufficiently slow for a rough determination of the melting temperature from POM (ca. 205°C).

Changing the cation from PPN + or Bu 4 N + to bmim + caused a larger drop of the degradation temperature than that of the melting point of the salt. Only the bmim + complex is hence stable in the non-supercooled liquid phase, entered at 140°C instead of above 200°C. This result establishes a milestone in the development of ferromagnetic ILs. A route toward low-melting ferromagnetic ILs might also be the preparation of mixtures, since their melting points are in general lower than the ones of pure constituents. The exploratory experiments performed on equimolar mixtures of 1 and 1PPN effectively revealed a further 10 to 15°C decrease of the melting temperature with respect to neat complex 1 (Table 1). The concept was thus validated, although the system is not adapted due to the high melting temperature of 1PPN, and to the closeness of degradation temperatures. The approach proved however to be promising, once ferromagnetic ILs with thermal properties comparable to 1 will have become available. Complex 2. TGA studies reveal that this complex is relatively stable up to 100 °C (~1% mass loss), before it starts decomposing at higher temperatures (Figure 3). The complex is therefore stable in the fluid ionic liquid phase obtained after progressive liquefying of the pasty sample on heating to 60°C. POM and DSC (Figure 7) confirm that the liquid does not crystallize upon cooling but progressively solidifies through increased viscosity on cooling. These results are particularly interesting since complex 2 remains in the frozen ionic liquid state at room temperature, unlike 1, which needs to be heated above 100°C for melting to occur. Complex 3. TGA studies of complex 3 revealed significant decomposition starting at 110°C, while melting was observed by POM at ~134°C. Since the melting point is above the temperature where significant decomposition occurs, this complex was not studied in detail regarding its thermal properties. DSC performed in the crystalline range only showed a small and broad exothermic event on first heating, presumably due to recrystallization (Figure S5). Thermal properties data for the three bmim complexes and PPN + / Bu 4 N + analogues are summarized in Table 2.

Magnetic properties

Magnetic susceptibility studies of 1. Previous studies have shown that complexes containing the {Cu II 3 (μ-Cl) 2 } 4+ core the Cu II centres are ferromagnetically coupled.

29,30

Magnetic susceptibility studies on pristine complex 1 corroborate this trend; the χ M T product of 1 at 300 K is 1.36 cm 3 mol -1 K, comparable to the value expected for three non-Please do not adjust margins Please do not adjust margins interacting S = 1/2 ions (1.12 cm 3 mol -1 K, g = 2) and it increases upon cooling, reaching a maximum value of 1.87 cm 3 mol -1 K at 18 K, indicative of a S = 3/2 system (Figure 8). It then decreases, reaching 1.10 cm 3 mol -1 K at 2 K. This sudden decrease may be attributed to various factors: saturation effects due to Zeeman splitting, intermolecular interactions, or zero-field splitting (zfs) within the ground state.

The complete spin Hamiltonian of the system, including the isotropic interaction, zfs, Zeeman and mean-field correction terms (intermolecular coupling) can be written as:

(1)

In this context, the zfs term traces the origin of the ground state's zfs to anisotropic exchange and dipolar interactions, since Cu II ions (S = 1/2) cannot give rise to single-ion anisotropy. However, since not all tensors in the above Hamiltonian are diagonal within the same reference system, and due to the large number of terms, the derivation of each term is a non-trivial problem, requiring single-crystal data. 31 However, at a first approximation the giant-spin approach can be useful in quantifying the ground-state axial anisotropy parameter D, in order to decide upon the most suitable model with which to analyse the magnetic susceptibility data. X-band EPR spectroscopy at low temperatures is a very useful tool in analyzing the magnetic properties of the ground states of polynuclear systems. As will be shown (see below), the S = 3/2 ground state of 1 exhibits a negligible zfs, which means that magnetic susceptibility data can be analyzed without that term. Since the anisotropic exchange term induces a zfs in the ground state, this term can be safely excluded from the model. To test the thermal stability of 1, we also carried out magnetic susceptibility studies on a sample that had previously been molten inside a quartz tube at 140 °C, and then allowed to cool. After correcting for the mass of the sample and the diamagnetic corrections of the quartz tube (using the data of pristine 1 as reference), the χ M T vs T and M vs H curves were practically superimposable, corroborating the thermal stability of 1 (Figure S7). Magnetic susceptibility studies of 2. Magnetic studies of 2, in conjunction with microanalytical and IR studies, serve as confirmation of its molecular structure in the absence of structural data. The χ M T product of 2 at 300 K is 0.51 cm 3 mol -1 K (Figure 8), significantly below the value expected for three non-interacting S = 1/2 ions (1.30 cm 3 mol -1 K, g = 2.15) and very close to the expected value for an isolated S = 1/2 spin (0.43 cm 3 mol -1 K, g = 2.15). This suggests very strong antiferromagnetic interactions, which stabilize an S T = 1/2 ground state so strongly that the excited state (S T = 3/2) is weakly populated even at 300 K. This conclusion is corroborated by the χ M T decrease upon cooling. This decrease is moderate down to 50 K, but then it becomes more abrupt, leading to a χ M T value of 0.28 cm 3 mol -1 K at 2 K. This sudden decrease may be attributed to factors such as saturation effects due to Zeeman splitting, intermolecular interactions, or antisymmetric exchange (AE) interactions.

The presence of a shifted g ⊥ resonance in EPR data (see below) in this type of complexes is indicative of the simultaneous presence of a non-equilateral magnetic symmetry and the interplay of AE. 32 At a first approximation we consider an isosceles-symmetry spin Hamiltonian (J 12 = J 13 = J and J 23 = J') with AE contributions. Thus, the complete spin Hamiltonian that may be considered is:

(2)

In this equation, G is the AE vector, assuming G z >> (G x , G y ) ~ 0, while intermolecular interactions are also considered by the last term.

In a preliminary fitting attempt we considered zJ = 0 and J = J'.

The fit was of poor quality, yielding J = -189 cm -1 , |G z | = 1.95 cm -1 and g = 2.11 (R = 2.0 × 10 -3

). We therefore considered an isosceles magnetic model (J ≠ J'). In this type of complexes, fits to magnetic susceptibility data through such Hamiltonians yield two best-fit solutions, one with |J| > |J'| (A) and one with |J| < |J'| (B), since in both cases the resulting spin manifolds are arranged in the same manner and are indistinguishable with respect to their magnetic susceptibilities. Fits considering zJ = 0 afforded an improvement, however they were still of inferior quality (R = 4.8-5.0 × 10 -4 ). It was therefore decided to also consider small intermolecular interactions. Indeed, inclusion of a zJ parameter of the order of -0.3 cm -1 improved the agreement to the data, particularly in the low-T region. Best-fit solutions were J = -298 cm -1 , J' = -257 cm , zJ = -0.37 Magnetic susceptibility studies of 3. The magnetic properties of 3 are qualitatively similar to those of 2. The χ M T product at 300 K is 0.73 cm 3 mol -1 decreasing steadily upon cooling down to 100 K, and subsequently exhibiting a sharper drop down to 0.061 cm 3 mol -1 K at 1.8 K. These similarities suggest the presence of antiferromagnetic interactions, however the higher χ M T value at 300 K suggests weaker couplings. EPR data also suggested the presence of AE interactions (see below), as in the case of 2. The data were accordingly analysed within the framework used to interpret the magnetic behavior of complex 2. Initial fits considering J = J' were carried out, using either AE or zJ to account for the low-T drop in χ M T. Using only AE yielded J = J' = -75 cm -1 and |G z | = 27 cm -1

, but abnormally low g (1.92) and poor agreement with the data at low T (R = 6.6 × 10 -2 ). Using only zJ yielded a much better fit throughout all temperatures, with J = J' = -90 cm -1 , zJ = -3.4 cm -1 and g = 2.05, but still exhibiting poor agreement with the experimental data (R = 3.1 × 10 -3 ). Using both parameters yielded J = J' = -90 cm -1 , |G z | = 0.015 cm -1 , zJ = -7.9 cm -1 and g = 2.09 (R = 7.4 × 10 -4

). This latter result indicates that there are correlations between zJ and G z , with intermolecular interactions being arithmetically favoured during the fitting process. Taking into account the EPR data (see below), it can be concluded that J ≠ J', otherwise the g ⊥ resonance would be forbidden, and that G z ≠ 0, otherwise g eff⊥ would be equal to g 0⊥ , which clearly is not the case. Based on these experimental observations, new fits can be performed including AE and with the constraint J = J' relaxed. Moreover, based on the crystal structure and the connectivity between the Cu atoms, we can additionally propose the assignment J 13 = J 23 = J and J 12 = J'. As in the previous attempts, considering zJ = 0 yielded very poor results. Including this parameter in our model greatly improved results, yielding best fit solutions: J = -117 cm -1 , J' = -62 cm -1 , |G z | = 40 cm -1 , zJ = -7.0 cm -1 , g = 2.17 A salient feature of these fits is the important value of zJ, which we correlate to the intermolecular H-bond-mediated interactions between the anions of 3 (see description of the structure and Figure S3). With z = 2 nearest neighbours the fits allude to interactions of -3.5 cm -1 . Such a significant value can explain the fact that 2 K isothermal magnetization data could not be fitted using this model, as the experimental magnetization values were significantly lower than calculated curves; inclusion of mean-field corrections in the calculation of M requires the consideration of a self-consistent mean field, which is not possible with Phi, and not further pursued in the context of the present work.

In order to corroborate these zJ values, we approximated the 1D chains of Cu 3 complexes by considering closed rings of such complexes. In these calculations we assumed that Cu , |G z | = 51 cm -1 , g = 2.11 (A'), indicating significant intermolecular interactions; solution A' exhibits practically the same J av value as solutions A and B. The simulations to the isothermal magnetisation data were of high quality, greatly improved over models considering mean-field corrections (Figure S6). This is strong evidence that significant intermolecular superexchange interactions are operative. We attribute their strength to the fact that magnetic exchange may occur through the magnetic orbitals of Cu(1) and those of the Cu atoms of an adjacent cluster via the Cl1•••H10''-O10'' pathway. In addition, when analysed within the context of Equation 3 these parameters imply g 0⊥ values of ~2.16, which are much more reasonable for square-planar Cu II . EPR spectroscopic studies of 1. The X-band EPR spectrum of 1 (Figure 9) exhibits a simple axial signal which can be simulated either with an isolated S = 1/2 or with an isolated S = 3/2 spin with a very small D. Given the results from the magnetic susceptibility studies, which reveal ferromagnetic interactions that stabilize an S T = 3/2 ground state, only the latter case is relevant. Fits to the 4 K spectrum yielded g || = 2.261, g ⊥ = 2.081 and |D| = 1.3⋅10 -3 cm -1

.

EPR spectroscopic studies of 2 and 3. The X-band spectra of the complexes (Figure 10) are characterised by broad signals, consisting of a maximum, which we attribute to the g || resonance, and a derivative feature with a broad valley, which we attribute to the g ⊥ resonance. The positions of these resonances correspond to effective g values of: g eff|| = 2.19, g eff⊥ ~ 2.05 (derivative) and 1.85 (valley) for 2; g eff|| = 2.15, g eff⊥ ~ 1.86 (derivative) and 1.65 (valley) for 3.

Please do not adjust margins

Please do not adjust margins In both cases the g ⊥ features are significantly broadened with their tails reaching down to g ~ 1. Such axial lineshapes are common in antiferromagnetic half-integer spin triangles; the ganisotropy is induced by the simultaneous presence of a low magnetic symmetry (J ≠ J') and antisymmetric exchange (Dzialoshinskii-Moriya) interactions. The positions of the g eff|| and g eff⊥ signals have been analysed in detail and have been correlated to the single-ion g-tensor elements, g 0|| and g 0⊥ ; in particular, it can be shown that g eff|| = g 0|| and that:

(

) 3
where hv is the energy of the microwave quantum, δ = 2|J -J'| (for S i = 1/2 and assuming a -2J ij S i S j Hamiltonian formalism), and

Δ = (δ 2 +3G z 2 ) 1/2
. 33 Within that framework, the observed g ⊥ broadening has been attributed to distributions of the J ij isotropic interactions (J-strain). [34][35][36][37][38] The low-temperature spectra of 2 and 3 (Figure 10) were simulated assuming isolated S = 1/2 spins, i.e. corresponding to significant thermal population only of the ground state Kramers doublet. Within this model the g ⊥ broadenings were simulated in a phenomenological manner, assuming distributions of the g eff⊥ parameter. Initial attempts assuming normal distributions were unsuccessful, which was attributed to the possibility that the distributions of the J ij and |G z | values, the fundamental origins of g eff⊥ -strain, are such that they give rise to non-normal g eff⊥ distributions. To account for this, we considered a series of axial species with g eff|| = 2.19 (for 2) and 2.15 (for 3) and with g eff|| ≥ g eff⊥ ≥ 0.7. Then, the experimental spectra were fitted to the relative weights of these sub-spectra and distributions were obtained according to a previously described procedure 34,39 using custom-made routines written for Easyspin. Both distributions are nonnormal, with maxima at g = 2.05 (for 2) and 1.69 (for 3) and weighted averages of 1.70 and 1.47, respectively; we have considered those latter values as representative of g eff⊥ for each complex. Considering that Cu II ions in an approximately square-planar coordination sphere are characterised by a quasi-axial g-tensor with g 0|| ~ 2.15-2.25 and g 0⊥ ~ 2.02-2.08, [40][41][42][43] EPR spectra can help assess the physical meaning of the fits to magnetic susceptibility data. When analysed through this framework, the fits to the magnetic susceptibility data of 2 and 3 implied rather low values for g 0⊥ (see above). For complex 2, magnetic susceptibility fits A and B lead to reasonable g 0⊥ values when considering g ⊥eff = 1.90; this falls between the weighted average (1.70) and the maximum (2.05) of the fitted distribution of the EPR spectrum. We attribute this disagreement to the slight discrepancies of the simulation to the experimental EPR data in the 3-4 kG region, implying that the weighted average of the derived distribution slightly underestimates the average g ⊥eff . This could be related to the physical state of the sample, which is not a crystalline monodisperse solid, but an amorphous frozen liquid. As such, its electronic parameters may exhibit larger distributions, from additional structural strains related to this physical state, and which may be harder to model. For complex 3, the EPR simulation were of higher quality. The underestimation of g ⊥0 based on the parameters of solutions A and B was corrected by considering the parameters of solution A', where intermolecular interactions were no longer considered as perturbations, but were approximated in an Please do not adjust margins Please do not adjust margins exact manner. This improved coherence between magnetic susceptibility and EPR data further corroborates our results.

Conclusions and perspectives

Complexes 44 previously unreported in copper(II) pyrazolate complexes.

Both 1 and 2 are quite similar to their previous analogues with respect to their magnetic properties, however they are remarkably different with respect to their physical form, melting points and thermal properties. This study illustrates that ionic complexes can retain their basic magnetic characteristics, which can be fine-tuned by regular synthetic methods available to coordination chemists, while at the same time their physical form and melting points can be modified by a proper selection of the counterions. In the present case, the selection of bmim, a common cation in ILs caused a decrease in the melting points of those complexes. In the case of 2, this substitution led to a viscous ionic material that could not be isolated in a crystal form. Presumably, one of the factors that led to this marked difference between 1 and 2 is the different charges of the complex anions: complex 1 is dianionic, whereas 2 is monoanionic, therefore bound to experience weaker electrostatic interactions with the bmim + cations and, hence, characterized by a lower melting point.

The metallic core of complex 3 is quite similar to that of 2, with the difference that a μ-chloro ligand provides additional bridging. We attribute the quite different magnetic couplings within the two complexes (-285 vs -98 cm -1 average values, respectively) to the action of this bridge in 3, which presumably increases the pyramidality of the μ 3 -OH -bridge on the opposite side of the Cu 3 plane. This should make the overlap of magnetic orbitals between Cu atoms less effective, thereby decreasing the antiferromagnetic component of their superexchange.

The present findings suggest more extensive further studies in this family of complexes along two directions: First, the testing of different countercations and pyrazolate ligands for the preparation of complex salts with potentially even lower melting points, higher thermal stabilities and lower viscosities;

in particular, such studies will be particularly relevant in the case of complex 2, which showed to be an IL at room temperature, but of a high viscosity and of limited thermal stability. Second, comparison of complex 1 with known derivatives of the same ferromagnetic anion showed that the use of bmim + effectively shifted the melting point to lower temperature with respect to more classical cations and that mixtures of salts with different cations are promising to access to ferromagnetic ILs with even lower melting points and broader thermal stability ranges.

Experimental Syntheses

All reagents and solvents were used as received. Complexes 1PPN and 1Bu 4 N were prepared according to the literature procedures. 28 Indicative IR assignments for 1 were carried out based on bibliographic data for bmim + cations 45,46

X-ray crystallography

X-ray diffraction data for 1 and 3 were collected from single crystals mounted atop glass fibers using graphite monochromated Mo-Ka radiation (λ = 0.71073 Å) on a Bruker D8 QUEST diffractometer equipped with a CMOS detector. The structures were solved by intrinsic phasing methods available with SHELXT, and data were refined by full-matrix leastsquares using SHELXS and SHELXL program packages 48 supplied within the APEX3 suite and ShleXle. 49 Multi-scan absorption correction was performed using SADABS. 50 Relevant details are shown in Table 4. X-ray diffraction data for 2 were collected on a Bruker D8 diffractometer using monochromatic Cu-Ka radiation with a scanning range between 4 and 70° and a scan rate of 2°min -1 .

Physical measurements

IR spectra were collected from the pure powders on a Bruker Alpha FTIR spectrometer and on a Perkin-Elmer Spectrum 100 FT-IR spectrometer using the Attenuated Total Reflectance (ATR) accessory. The elemental analyses (C, H, N) were performed at Galbraith Laboratories, Inc., Knoxville, Tennessee and at the Service d'analyses, de mesures physiques et de spectroscopie optique of the University of Strasbourg. Melting points were determined on a Start SMP10 digital melting point apparatus. SQUID data were collected on a Quantum Design MPMS3 magnetometer. Magnetization measurements at different fields at a given temperature confirmed the absence of ferromagnetic impurities. Data were corrected for the sample holder and TIP contributions, and diamagnetism was estimated by using Pascal constants. The magnetic susceptibilities were computed by exact calculation of the energy levels associated with the spin Hamiltonian through diagonalisation of the full matrix using Phi 2.1.6. 51 The error-factor R is defined as:

where N is the number of experimental points. TGA studies were performed using a TA instrument SDTQ 600 (heating rates of 5 °Cmin -1 under air stream, using Pt crucibles), and DSC studies under a nitrogen stream were carried on a DSC Q1000 apparatus from TA Instruments. EPR spectra were recorded on a Bruker ESP300 spectrometer using a Bruker 4102ST rectangular cavity operating in the TE 102 mode. For variable-temperature experiments the cavity was fitted in an ESR900 dynamic continuous flow cryostat and the temperature was regulated with an Oxford ITC4 servocontrol controlled by the Oxford Objectbench software application. To properly load a sample of complex 2 without risk of contamination of the EPR cryostat, a quantity of the viscous paste was pushed into a quartz capillary (Figure S8), which was then loaded into a regular EPR tube.

Complex 3

 3 consists of an anion exhibiting a {Cu 3 (μ 3 -OH)(μ-Cl)} 4+ metal core, in which an additional chloro bridge occupies the axial positions of Cu(1) and Cu(2) through two elongated bonds (2.659 and 2.799 Å, respectively, Figure2). The hydroxo O(1) atom is quite pyramidal, situated 0.599 Å from the Cu 3 plane, with the sum of the Cu-O-Cu angles being equal to 334.16°. The three pyrazolate ring mean planes exhibit marked deviations from the Cu 3 plane, with dihedral angles of 27.26, 14.61 and 10.85° between the Cu 3 plane and the pyrazolates containing atoms N(1), N(3) and N(5), respectively.

Figure 1 .

 1 Figure 1. POV-Ray plot of the anion of 1. Hydrogen atoms have been omitted for clarity. Carbon atoms are shown in grey.

Figure 2 .

 2 Figure 2. POV-Ray plot of the anion of 3. Hydrogen atoms, except for the μ 3 -OH -one, have been omitted for clarity.

Figure 3 .

 3 Figure 3. TGA traces for complexes 1, 2, 3, 1PPN and 1Bu 4 N, the latter complex having first been heated to 100°C to remove the co-crystallized solvent (see ESI).

Figure 5 .

 5 Figure 5. DSC traces for complex 1PPN. The successive heating cycles (red, orange, magenta and olive curves, and corresponding expanded ranges above) revealed the crossing of several irreversible solid-solid transitions, until the final melting at 206°C, temperature around which the decomposition process had just started. Crystallization was not observed on cooling (blue curve), but freezing of supercooled ionic liquid occurred on crossing the glass transition at 70°C.

Figure 6 .

 6 Figure 6. DSC traces of co-crystallized solvent-free 1Bu 4 N complex, showing two phase transitions in solid state, located at 20 and 63°C (red: first heating; orange: second heating) and slightly delayed on cooling (blue). Experiment was stopped below the melting transition, observed with POM around 205°C, because of the weight loss associated with the onset of decomposition.

Figure 7 .

 7 Figure 7. DSC traces for complex 2 (red: first heating; orange: second heating, blue: cooling) showing a broad low-temperature glass transition range, corresponding to the progressive liquefying of the frozen ionic liquid.

Table 2 .

 2 Summary of thermal property data for bmim + complexes 1, 2, 3, and analogue complexes 1PPN and 1Bu 4 free 1Bu 4 N. **T m determined with optical polarizing microscopy. T dec : temperature above which decomposition is detected in TGA traces; T 95% : 5% weight loss temperatures; Cr: crystal; F. li.: frozen liquid; T recr : transition temperatures between crystalline solid states on first heating; ΔH: enthalpy change associated to transitions; T m : melting temperature; T G : glass transition ranges on heating and on cooling (differences between step onset and end).

1 , 1 . 1 . 30 Figure 8 .

 111308 Figure 8. Magnetic susceptibility data of complexes 1-3 and fits according to the models described in the text.

- 1 ,

 1 |G z | = 18.2 cm -1

6 | 1 , 5 , 1 ,

 6151 J. Name., 2012, 00, 1-3 This journal is © The Royal Society of Chemistry 20xx Please do not adjust margins Please do not adjust margins cm g = 2.12 (R = 4.9 × 10 -A) and J = -271 cm -1 , J' = -315 cm -|G z | = 19.0 cm -1 , zJ = -0.38 cm -1 , g = 2.12 (R = 5.0 × 10 -5 , B). In both these solutions, J av (defined as (2J + J')/3) is -285 cm -1 , and all other parameters are practically the same. EPR spectroscopic data allow us to independently evaluate the coherence between the determined values of J, J' and G z . In particular, considering an average g eff⊥ of 1.70 (see below), in the framework of Equation 3 solutions A and B imply g 0⊥ ~ 1.82, which falls significantly below the values usually known for square-planar Cu II . Attempts to constrain |J -J'| to lower values and/or G z to higher values, in order to attain more reasonable g 0⊥ values were unsuccessful. As discussed (see below), reasonable values are obtained when we consider g eff⊥ ~ 1.90, which falls between the weighted average (1.70) and the maximum (2.05) of the fitted distribution.

g = 2 . 1 ,

 21 17 (R = 2.4 × 10 -4 , B). In both these solutions, J av ~ -98 cm and all other parameters are practically the same. Following the previous procedure, and considering an average g eff⊥ ~ 1.47 (see below), in the framework of Equation 3 solutions A and B imply g 0⊥ values of ~1.73, which underestimate usual values for square-planar Cu II .

( 1 ) 1 ,

 11 couples to all three spins of the adjacent molecule through the H-bond Cl(1)•••H(10')-O(1') by an additional exchange interaction, J'' (= J 11' = J 12' = J 13' ). The smallest possible ring of three Cu 3 complexes was fitted for its magnetic susceptibility and the best-fit parameters were used to simulate the isothermal magnetization data. Best-fit parameters based on solution A were J = -111 cm -J' = -70 cm -1 , J'' = -5.6 cm -1

Figure 9 .

 9 Figure 9. X-band EPR spectrum of 1 at 11 K and fit according to the model described in the text. Experimental conditions: f EPR = 9.42 GHz, microwave power: 0.5 mW, mod. amplitude: 1 G pp . The inset shows the weight distributions of the species with varying g ⊥ parameters.

Figure 10 .

 10 Figure 10. X-band EPR spectrum of 2 and 3 at 4 K and simulations according to the model described in the text. The inset shows the distributions of the axial species used to reproduce the g ⊥ features of the two complexes. Experimental conditions: f EPR = 9.42 GHz, microwave power: 2 mW; , mod. amplitude: 5 G pp (2), 1 G pp (3).

  This journal is © The Royal Society of Chemistry 20xx

a w = 1 /[σ 2 (F 0 2 ) 2 )/ 3 ,

 1223 + (aP)2 + bP], where P = (F 0 2 + 2F c and (a, b) = (0.0694, 1.0569) for 1 and (0.0442, 2.8327) for 3. This journal is © The Royal Society of Chemistry 20xxPlease do not adjust margins Please do not adjust marginsNotes and references

Table

Table 3 .

 3 Summary of magnetic properties of complexes 1, 2, 3, and 1Bu 4 N. Energies are given in cm -1 and the -2J ij S i S j spin Hamiltonian formalism is used.

				1		2	3	1PPN	1Bu 4 N
	J av (cm -1 )	15.6		-285	-98	-	14.3
	|G z | (cm	-1 )	-		18	51	-	-
	|D| (cm	-1 )	1.3×10	-3	-	-	-	0.088
	g ||			2.261	2.19	2.15	-	2.245
	g ⊥			2.081	1.70-1.90	~1.47	-	2.064
	S			3/2		1/2	1/2	-	3/2
	Ref.			TW		TW	TW	-	30
	TW: This work.

  1 and 2 have previously been reported in the form of PPN + and Bu 4 N + salts and are herein reported as bmim

		+
	salts. Complex 3 consists of a new structural core, reminiscent
	of the ones found in complexes [Et 3 NH][Cu 3 (μ 3 -OH)(μ-
	pz) 3 Cl 3 (pzH)]	28 and [Cu 3 (μ 3 -OH)(μ-pz) 3 (py) 2 (μ-Cl)Cl]•py (py =
	pyridine)

  was stirred overnight, and turned dark blue. NaCl was removed by filtration through celite and the filtrate was exposed to slow Et 2 O vapour diffusion in a closed system. A blue-grey oily solid was obtained after three days. The supernatant solution was decanted, and allowed to slowly evaporate, while the blue-grey material was redissolved in THF and allowed to slowly evaporate. Both solutions yielded crystalline 3 after slow evaporation (0.45 g, 52%). Elemental analysis found C, 35.16; H, 4.59; N., 17.07. Calc. for C 25 H 40 Cl 4 Cu 3 N 10 O: C, 36.22; H, 4.86; N, 16.89%. IR (ATR):

	ν max /cm -1 3309br, 3145s, 3115s, 3076s, 2959s, 3021s, 2958s,
	2933s, 2873s, 1567s, 1488m, 1423m, 1376s, 1277s, 1176vs,
	1168vs, 1050vs, 753vs, 644w, 627s, 618s.
	and
	pyrazolato complexes. 47
	Complex 1. In 10 mL of THF were added 0.511 g CuCl 2 •2H 2 O
	(3.00 mmol), 0.204 g Hpz (3.00 mmol), 0.120 g NaOH (3.00
	mmol) and 0.349 g bmimCl (2.00 mmol). The dark green
	solution was stirred overnight, and turned bright green. The
	solution was filtered through celite (to remove NaCl as a white
	solid) and the filtrate was exposed to slow Et 2 O vapour
	diffusion in a closed system. A green crystalline solid resulted
	after three days, was collected by decantation, washed with
	Et 2 O and dried under reduced pressure (0.200 g, 24%).
	Elemental analysis found C, 34.90; H, 4.54; N., 16.20. Calc. for
	C 25 H 39 Cl 5 Cu 3 N 10 : C, 35.43; H, 4.64; N, 16.53%. Mp 130-140 °C.
	IR (ATR): ν max /cm -1 3306br, 3148s (v S HC(2)C(3)H bmim ), 3111s &
	3090vs (v a HC(2)C(3)H bmim + v C(1)H bmim ), 2959s (v a
	CH3 bmim/butyl ), 2934s (v FR CH 3 bmim/butyl ), 2873s (v s CH 3 bmim/butyl ) ,
	1570 & 1561 (v a ring bmim + v CH 2 (N) bmim + v CH 3 (N) bmim + v
	CN) bmim , 1488m, 1420 & 1376 (v ring pz ), 1273 (δ s HCH butyl + δ a
	ring bmim + δ CCCC butyl ), 1175vs & 1165vs (γ ring pz + δ CH pz ),
	1052vs (δ CH pz ), 759vs (γ CH pz ), 648w & 629m & 620s (γ ring pz ).
	Complex 2. In 10 mL of THF were added 0.511 g CuCl 2 •2H 2 O
	(3.00 mmol), 0.204 g Hpz (3.00 mmol), 0.160 g NaOH (4.00
	mmol) and 0.175 g bmimCl (1.00 mmol). The dark green
	solution was stirred overnight, and turned dark blue-green.
	NaCl was removed by filtration through celite and the filtrate
	was exposed to slow Et 2 O vapour diffusion in a closed system.
	A dark blue oil was obtained after three days. The supernatant
	solution was decanted, the oil was redissolved in a small
	amount of THF and allowed to slowly evaporate until a dark
	blue viscous paste was obtained (0.500 g, 70%). Elemental
	analysis found C, 31.02; H, 3.91; N, 16.00. Calc. for
	C 17 H 24 Cl 3 Cu 3 N 8 O⋅0.25THF⋅H 2 O: C, 31,36; H, 4.09; N, 16.25%. IR
	(ATR): ν max /cm -1 3281br, 3139m, 3108m, 2956m, 2932m,
	2872m, 1570m, 1561m, 1487, 1465, 1459, 1428, 1420, 1377s,
	1277, 1252, 1177s, 1162s, 1077w, 1049vs, 887m, 835m, 750vs,
	649w, 620vs.

Complex 3. In 10 mL of THF were added 0.511 g CuCl 2 •2H 2 O (3.00 mmol), 0.204 g Hpz (3.00 mmol), 0.200 g NaOH (5.00 mmol) and 0.349 g bmimCl (2.00 mmol). The dark green Please do not adjust margins Please do not adjust margins

solution

Table 4 .

 4 Data collection and refinement details for complexes 1 and 3.

			1	3
	Empirical formula		C 25 H 39 Cl 5 Cu 3 N 10	C 25 H 40 Cl 4 Cu 3 N 10 O
	Formula weight		847.53	829.09
	Temperature/K		298	298
	Crystal system		Triclinic	Orthorhombic
	Space group		P1	P2 1 2 1 2 1
	a/Å		11.209(1)	11.5442(6)
	b/Å		13.137(1)	15.6305(9)
	c/Å		13.352(1)	19.9973(11)
	α/°		93.015(2)	90
	β/°		108.718(2)	90
	γ/°		108.591(2)	90
	V / Å 3		1738.4(3)	3608.3(3)
	Z		2	4
	ρ calc / g cm -3		1.619	1.526
	μ / mm -1		2.236	2.083
	F(000)		862	1692
	Crystal size / mm 3		0.26 × 0.18 × 0.15	0.31 × 0.11 × 0.06
	2Θ range for data collection/°	5.894 to 56.784	5.988 to 56.79
	Index ranges
	Reflections collected		37960	163883
	Independent reflections		8688 [R int = 0.0756,	9003 [R int = 0.1184,
			R sigma = 0.0510]	R sigma = 0.0391]
	Data/restraints/parameters	37960/0/398	163883/46/393
	Goodness-of-fit on F 2		1.026	1.042
	R 1 , wR 2 [I > 2σ(I)]		0.0450, 0.1195	0.0451, 0.0977
	R 1 , wR 2 (all data)		0.0578, 0.1300	0.0711, 0.1106
	Largest diff. peak/hole / eÅ	-3	0.78/-0.57	0.58/-0.33
	Flack parameter			0.15(2)

-14 ≤ h ≤ 14, -17 ≤ k ≤ 17, -17 ≤ l ≤ 17 -15 ≤ h ≤ 15, -20 ≤ k ≤ 20, -26 ≤ l ≤ 26

This journal is © The Royal Society of Chemistry 20xx J. Name., 2013, 00, 1-3 | 9

Acknowledgements

We thank Dr. Logesh Mathivatanan (FIU) for helpful discussions on the preparations of the complexes, Dr Nathalie Gruber (Université de Strasbourg) for the collection of XRD data of complex 2 and Dr. Éric Rivière (ICMMO, Orsay) for the collection of SQUID data of complex 3. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 746060. Work at FIU was partially supported by the National Science Foundation (CHE-1213683).

Conflicts of interest

There are no conflicts of interest to declare.


Lyes Bayou

David Espes

Nora Cuppens-Boulahia

Frédéric Cuppens

wIDS: a multilayer IDS for Wireless-based SCADA Systems

The increasing use of wireless sensors networks in Supervisory Control and Data Acquisition systems (SCADA) raises the need of enforcing the security of this promising technology. Indeed, SCADA systems are used to manage critical installations that have hard security, reliability and real-time requirements. Consequently, in order to ensure Wireless Industrial Sensor Networks (WISN) security, Intrusion Detection Systems should be used as a second line of defense, in addition to sensor's embedded security mechanisms. In this paper, we present wIDS a multilayer specification-based Intrusion Detection System specially tailored for WISN. It has a two-level detection architecture and is based on a formal description of node's normal behavior.

Introduction

Wireless Industrial Sensor Network (WISN) are now established as a widely used technology in industrial environments. Indeed, comparing to wired technologies, they allow significant decreases in deployment and maintenance costs. In the same time, they increase the system sensing capabilities as wireless sensors can be deployed in hardly reachable and adversarial environments.

In industrial environments, Supervisory Control and Data Acquisition systems (SCADA) are used for monitoring and managing complex installations such as power plants, refineries, railways, etc. These systems rely on sensors deployed over large area to gather in real time information about the industrial process. These informations are sent to a controller that processes them and sent back commands to field devices such as actuators or valves.

Security is an important issue in SCADA systems. Indeed, the disruption of these systems can cause significant damages to critical infrastructures such as electric power distribution, oil and natural gas distribution, water and wastewater treatment, and transportation systems. This can have a serious impact on public health, safety and can lead to large economical losses.

On the other hand, ensuring security in WISN is a challenging task. Indeed, WISN are subject to the same attacks as other wireless networks. Mainly, attackers use wireless communication as a vector to launch their attacks. Furthermore, sensor's limited capabilities in terms of processing power, memory space and energy make hard the implementation of strong security mechanisms.

Thus, in addition to sensor's embedded mechanisms that ensure authentication, confidentiality and availability, Intrusion Detection Systems can be used as a second line of defense for enforcing the overall system security and in particular for detecting unknown attacks.

The exchanged traffic in a SCADA system is highly predictable in terms of amount and frequency. Indeed, it involves limited human interaction and is mainly composed of automated devices that execute defined actions at defined times. Therefore, by modeling the normal expected behavior of wireless nodes, we can detect malicious action as being actions deviating from the established model.

In this paper, we present wIDS, a multilayer specification-based Intrusion Detection System specially tailored for Wireless Industrial Sensor Networks. The proposed IDS checks the compliance of each action performed by a wireless node towards the formal model of the expected normal behavior. To do that, access control rules are used for modeling authorized actions that a wireless node can perform. These rules are mainly built on the base of the specifications of each layer of the communication protocol, node's localization and the industrial process configuration. They also take into consideration the capabilities and limitations of the wireless nodes . Thus, by specifying security policy at an abstract level, we are able to define and manage more accurate and efficient security rules independently from nodes and network characteristics such as sensor natures and density or the network topology. Then, these characteristics are used later when deriving concrete security rules. Also, in addition to alerts that are raised by actions deviating from the normal model, we define additional intrusion rules that aim to detect basic attacker actions such as injecting, deleting, modifying and delaying packets.

The rest of the paper is organized as follows. Section 2 presents previous works done in this field and emphasis their limits. In Section 3, we present briefly the protocol WirelessHART that is the use case of this study. We present in Section 4, the proposed IDS for Wireless Industrial Sensor Networks. We describe its two-level detection architecture and present the formalism used to build node's normal behavior. Section 5 details security rules defined on the base of WirelessHART specifications. In Section 6, we present how detection rules are defined to detect suspicious actions. The performances of the proposed wIDS are presented and discussed in Section 7. Finally, Section 8 presents the conclusion and future works.

Related Work

In the literature, there are only few studies on the security of Wireless Sensor Networks used in industrial environments. Mainly, proposed solutions for SCADA systems focus on applying IDS techniques to wired-based networks [START_REF] Huitsing | Attack taxonomies for the modbus protocols[END_REF][START_REF] Fovino | Modbus/dnp3 state-based intrusion detection system[END_REF][START_REF] Mitchell | A survey of intrusion detection techniques for cyber-physical systems[END_REF] and neglect those using wireless communications.

More generally, several IDS are proposed for generic WSN [START_REF] Mitchell | A survey of intrusion detection in wireless network applications[END_REF]. However, proposed solutions are not suitable for WISN. Firstly, WISN have more hard requirements than generic WSN such as real-time and reliable communications. Indeed, dropped or delayed data may lead to physical losses. Secondly, these proposed IDS are mainly restricted to detect specific kinds of attack while WISN must be secured towards a broad spectrum of known and unknown attacks. Nevertheless, these works should be considered in order to propose a solution designed for WISN. Thus, in [START_REF] Silva | Decentralized intrusion detection in wireless sensor networks[END_REF], Da Sila et al. propose one of the first intrusion detection systems for WSN. They designed a decentralized system in which a set of nodes is designated as monitor and is responsible of monitoring their neighbors. The proposed IDS is based on the statistical inference of the network behavior. It only monitors data messages and ignores other kinds of exchanged messages. It includes seven types of rules that aim to detect common attacks.

For its part, Roosta et al. propose in [START_REF] Roosta | An intrusion detection system for wireless process control systems[END_REF] an intrusion detection system for wireless process control systems. The system consists of two components: a central IDS and multiple field IDS that passively monitor communications in their neighborhood. They periodically send collected data to the central IDS that checks their conformity with the security policy. This IDS models normal behavior of the different wireless devices on the base of some network specifications and traffic characteristics inferred statistically. Attacks are detected when there is a deviation from the model. However, it defines a few numbers of rules (8 rules) that do not cover all well-known attacks. Furthermore, as the detection logic is centralized, this solution requires continuous communications with field IDS which can add a significant network overload.

In [START_REF] Coppolino | An intrusion detection system for critical information infrastructures using wireless sensor network technologies[END_REF], Coppolino et al. propose an architecture for an intrusion detection system for critical information infrastructures using wireless sensor network. Their solution is a hybrid approach combining misuse and anomaly based techniques. It is composed of a Central Agent and several IDS Local Agents that monitors exchanged messages in their neighborhood. They calculate a statistical model of exchanged traffic and raise a temporary alert when nodes actions deviate from this model. The central agent combines these alerts and confirms them on the base of misuse rules. This IDS focuses on attacks against routing protocols and detects only two kinds of attacks i.e., sinkhole and sleep deprivation attacks.

Shin et al. [START_REF] Shin | An experimental study of hierarchical intrusion detection for wireless industrial sensor networks[END_REF] propose a hierarchical framework for intrusion detection for WISN. It is based on two-level clustering; multihop clusters for data aggregation and one-hop clusters for intrusion detection. This results in a four layer hierarchy: member nodes (MN) are the leaves, cluster heads (CH) manage MNs, gateways (GW) bundle clusters and a base station (BS) is the root of the hierarchy. These different levels implement the same detection logic, however they respond differently. Thus, MN only report to CH while other roles have the ability to react to attacks.

In our study, we aim to propose a solution that is able to detect either known and unknown attacks. Furthermore, such solution should have a multilevel detection architecture to monitor both local and end-to-end communications (gener-ally encrypted) and also in order to provide global coordination. Low detection level should have full detection capabilities in order to avoid overloading the network by additional exchanges and to have quick and accurate detections.

Backgrounds on WirelessHART

In our work, we choose to apply our approach to WISN that implements Wire-lessHART and we will use it as a common thread all along this paper. Indeed, WirelessHART [9] is the first standardized wireless communication protocol specially developed for industrial process management. It is included in version 7 of the HART standard, released in 2007, and was approved as an international standard in 2010 (IEC 62591).

A WirelessHART network, illustrated in Figure 1, has the following characteristics: -A Gateway that connects the wireless network to the plant automation network, allowing data to flow between the two networks. It can also be used to convert data and commands from one protocol to another one; -A Network Manager that is responsible for the overall management, scheduling, and optimization of the wireless network. It generates and maintains all of the routing information and also allocates communication resources; -A Security Manager that is responsible for the generation, storage, and management of cryptographic keys; -Access Points that connect the Gateway to the wireless network through a wired connection;

-Field devices deployed in the plant field and which can be sensors or actuators; -Routers used for forwarding packets from one network device to another; -Handheld devices that are portable equipments operated by the plant personnel used in the installation and during the maintenance of network devices.

WirelessHART implements several mechanisms to ensure security in both hop-by-hop and end-to-end communication. In hop-by-hop transmission, security is provided by the Data Link Layer (DLL) using a cryptographic key called "Network Key" shared by all devices composing the wireless network. Each packet is authenticated using a keyed Message Integrity Code (MIC).

The end-to-end security is provided by the Network Layer (NL) using a cryptographic key called "Session Key" known only by the two communicant devices. Packets are both authenticated by a MIC and their payload is also encrypted.

Multilayer specification-based IDS

In this Section, we present wIDS a multilayer specification based IDS for securing Wireless Industrial Sensors Networks. We describe its architecture, its components and its analyzing process.

Specification-based intrusion detection approaches formally define the model of legitimate behavior and raise intrusion alerts when user's actions deviate from the model [3] [4]. WISN are composed of nodes that have a predictable behavior and involves few human interactions. Consequently, on the base of the communication protocol specifications, the process configuration and wireless nodes capabilities, we can build an accurate model of the expected nodes's behavior.

We should also note that specification-based intrusion detection system do not require any training step. Therefore, they can be applied and used directly.

In this study, we assume that the aim of the attacker is to disturb the industrial process. This goal can be achieved by dropping some packets, injecting into the network false packets or modifying packets during their transmission. Furthermore, the attacker can also choose to delay the transmission of some important packets (alarms, sensing data, etc) in order to lead the process to an uncertain state or to hide its malicious actions. Therefore, we consider an attacker that can intercept, modify, forge or delay packets. It can be an insider or an outsider attacker.

wirelessOrBAC

We propose in this work wirelessOrBAC, an OrBAC [START_REF] Kalam | Policies for Distributed Systems and Networks[END_REF] extension that we develop in order to efficiently model Wireless Sensor Networks specifications. OrBAC has already been used to specify network security policy, especially in firewall management [START_REF] Cuppens | A formal approach to specify and deploy a network security policy[END_REF], intrusion detection (IDS) and intrusion prevention systems (IPS) [START_REF] Debar | Enabling automated threat response through the use of a dynamic security policy[END_REF]. It allows the definition of a conflict-free security policy and by using the concept of context, it makes it possible to define dynamic rules that fit the system's changes. This extension allows using access control rules, modeling authorized actions and the expected behavior of wireless nodes. Then, using this model, we can detect malicious actions by checking the compliance of each node action toward the defined security policy.

Furthermore, wirelessOrBAC allows the definition of both access control rules and intrusion detection rules using the same formalism.

To define a security policy, wirelessOrBAC defines the following concepts:

-wNetwork: It is an abstraction of the considered WSN.

-

where:

-

wIDS architecture

As indicated in Fig. 2, wIDS has a two-level architecture consisting in a central-IDS agent and several IDS-agents.

-The central-IDS agent: It is implemented in the Network Manager (resp. in the sink) in the case of wirelessHART (resp. in the case of a WISN). In addition of playing the role of an IDS-agent in its neighborhood, it monitors end-to-end communications after they are decrypted. It may check routing tables and transmission scheduling consistency; and performs global coordination between IDS-agents. -IDS-agents: They are implemented in selected sensor nodes. They are responsible for monitoring local communications of sensor nodes inside their neighborhood. They listen in promiscuous mode to all packets exchanged in their neighborhood. Then, they extract from them, relevant informations in order to check their compliance with the security policy.

The abstract security policy is defined at the central-IDS agent using the wirelessOrBAC formalism. It is also provided with several inputs such as node localizations, industrial process parameters and nodes configuration. The central-IDS agent provisions IDS-agents with security rules and several inputs related to nodes available in their neighborhood (i.e., the list of monitored nodes). It also updates if necessary all these information. Each IDS-agent is in charge of the application of the security policy in its area and alerts the central-IDS agent when policy violation occurs.

IDS-agents deployment scheme

The scheme used for the deployment of IDS-agents, is an important issue. Indeed, as WSN are decentralized systems, the localization of monitoring devices must be chosen carefully otherwise a part of exchanged traffic will not be monitored.

The deployment of IDS-agents is out of the scope of this paper. However, in our study, we use the scheme proposed in [START_REF] Bayou | Towards a CDS-based Intrusion Detection Deployment Scheme for Securing Industrial Wireless Sensor Networks[END_REF]. This scheme uses the graph theory concept of Connected Dominated Set to ensure the gathering of the whole exchanged traffic. Also, it presents the following characteristics: a) each IDS-agent is able to detect basic attacks occurring in its neighborhood without any cooperation with other IDS-agents; b) it creates a secure and reliable communication channel between each IDS-agent and the central-IDS; c) it requires an acceptable IDS-agents number to ensure an efficient network monitoring and coverage.

In wIDS, IDS-agents are implemented in sensors with enhanced capabilities. These nodes, called Super-Nodes, will act as classical sensor nodes by fulfilling sensing tasks and implements in the same time the detection logic. By using the aforementioned deployment scheme, selected Super-Nodes represents between 20%-25% of the total network nodes number. In this Section, based on WirelessHART specification [9], we define using wire-lessOrBAC rules the expected node's normal behavior. These rules express authorized actions at each protocol layer. We gather them in several categories and present hereafter, examples of each of them.

Meshed wireless network rules

In a wirelessHART network, all devices have the capability to forward packets of devices that are located several hops away from the Network Manager. That means that a device can send packets to any of its neighbors:

wRule(perm, wnet, wDevice, sending, packets, neighbors)

where neighbors is a wContext indicating that s1 performs action sending object packet to node s2 that is in its neighborhood:

Hold(W SN, s1, sending, packet, neighbors) ← is_dstAddr(packet, s2) ∧ is_neighbor(s1, s2) (4)

Packets construction rules

The WirelessHART specifications give guidelines on how packets should be built and the possible values of each field. Thus, the length and value of each field must be checked. Also, fields of the same packet must be consistent with each other. wRule(perm, wnet, wDevice, sending, packet, _) ← is_V alidP acket(packet)

where is_V alidP acket(packet) is a predicate indicating if packet fulfills wire-lessHART construction rules. The symbol "_" indicates that this rule is valid for any wContext.

Communication level

WirelessHART defines 5 packet types: Ack, Advertise, Keep-Alive, Disconnect and Data packets. The first 4 types are generated and processed in the Data Link Layer and are not propagated to the Network Layer or forwarded through the network. This means that these packets are only used in local communication between neighbors.

wRule(perm, wnet, wDevice, sending, packet, neighbors) ← is_packetT ype(packet, Ack|Advertise|keepAlive|Disconnect|Data)

The Data packet type is the only kind of packet that is transmitted in an end-to-end communication. This means that only data packets can be forwarded throughout the network: wRule(perm, wnet, wDevice, f orwarding, packet, _)

← is_packetT ype(packet, Data)

On the other hand, data packets are only exchanged between the Network Manager (wSink ) and wireless sensors (wSensor ) in both sens. This means that a data packet is never send from a wireless sensor to another wireless sensor. Thus: wRule(perm, wnet, wSensor, sending, packet, _)

← is_packetT ype(packet, Data) ∧is_dstN LAddr(packet, s2.addr) ∧ empower(wnet, s2, wSink) [START_REF] Shin | An experimental study of hierarchical intrusion detection for wireless industrial sensor networks[END_REF] and wRule(perm, wnet, wSink, sending, packet, _)

← is_packetT ype(packet, Data) ∧is_dstN LAddr(packet, s2.addr) ∧ empower(wnet, s2, wSensor) (9)

Communication scheduling rules

WirelessHART uses Time Division Multiple Access (TDMA) and Channel hopping to control the access to the wireless medium. The time is divided in consecutive periods of the same duration called slots. Each communication between two devices occurs in one slot of 10 ms.

Typically, two devices are assigned to one time slot (one as the sender and a second as the receiver). Only one packet is transmitted in one slot from the sender to the receiver which has to reply with an acknowledgment packet in the same slot.

In addition, WirelessHART uses channel hopping to provide frequency diversity and avoid interferences. Thus, the 2.4 GHz band is divided into 16 channels numbered from 11 to 26 which provide up to 15 communications in the same slot (Channel 26 is not used). Thus, we have the following rules: wRule(perm, wnet, wDevice, sending, packets, startSlot ∧ assignedF q) [START_REF] Deji | WirelessHART : Real-Time Mesh Network for Industrial Automation[END_REF] where startSlot is a wContext indicating that s performs action sending object packet when a slot time assigned to s starts:

Hold(W SN, s, sending, packet, startSlot) ← is_slotStartT ime(s, packet) (11)
and assignedFq is a wContext indicating that s uses its assigned frequency when performing action sending object packet :

Hold(W SN, s, sending, packet, assignedF q) ← is_assignedF q(s, packet)

For the acknowledgment, we have the following rule:

wRule(perm, wnet, wDevice, sending, packet, sendingAck)

where sendingAck is a wContext indicating that s1 performs action sending object packet when s1 received packet from s (at time t), and packet is destined to s and of type ack and s1 uses the slot and frequency assigned to s:

Hold(W SN, s1, sending, packet , sendingAck) ← packet_received(s1, packet, t) ∧ is_srcAddr(packet, s) ∧is_packetT ype(packet , Ack) ∧ is_dstAddr(packet , s) ∧is_assignedF q(s, packet) ∧ is_slotStartT ime(s, packet) [START_REF] Bayou | Towards a CDS-based Intrusion Detection Deployment Scheme for Securing Industrial Wireless Sensor Networks[END_REF] We should note that the Network Manager is responsible of building, managing and updating slots and frequencies planning.

Packets transmission rules

Sensor nodes are configured to send different kind of packets (i.e., sensing data, keep-alive, advertisement) at a defined time. Thus, sensing data must be sent periodically to the Network Manager.

wRule(perm, wnet, wDevice, sending, packet, packetP eriodicity)

← is_packetT ype(packet, Data)

where packetPeriodicity is a temporal context indicating that s performs action sending object packet in the planned sending time:

Hold(W SN, s, sending, packet, packetP eriodicity) ← is_packetP eriodicity(s, packet) (16)

Packets forwarding rules

A wirelessHART network has a meshed topology. Thus, wireless devices that are located several hops from the Network Manager, relay on their neighbors for forwarding their packets to their final destination.

wRule(perm, wnet, wDevice, f orwarding, packet, F orwardP acket)

where ForwardPacket is a provisional context (i.e., based on previous device actions) indicating that subject s received object packet (at time t) and s must forward this object:

Hold(W SN, s, f orwarding, packet, F orwardP acket) ← packet_received(s, packet, t) ∧ is_toBeF orwarded(packet)
∧empower(org, s, f orwarder)

Routing rules

WirelessHART uses graphs as routing method. A graph consists in a set of directed paths that connect network devices. It is build by the Network manager based on its knowledge of the network topology and connectivity. Every graph has a unique graph identifier that is inserted in the network packet header. Each device receiving this packet, forwards it to the next hop belonging to that graph.

wRule(perm, wnet, wDevice, sending, packets, graphN extHop)

where graphNextHop is a spatial context indicating that s performs sending object packet to s2 that is the next hop of s following graph g: Hold(W SN, s, sending, packet, graphN extHop) ← is_dstAddr(packet, s2.addr)∧ is_usedGraph(packet, g) ∧ is_N extHop(s.addr, g, s2.addr)

(20)
In graph routing there are two kinds of graphs: an upstream graph directed from all devices to the Network Manager and several downstream graphs directed from the Network Manager to each device. Thus, sensor nodes use the upstream graph for sending packets to the Network Manager: wRule(perm, wnet, wSensor, sending, packet, _)

← is_packetT ype(packet, Data) ∧is_usedGraph(packet, g) ∧ is_upStream(g) (21) and the Network Manager uses downstream graphs for sending packets to sensors:

wRule(perm, wnet, wSink, sending, packet, _)

← is_packetT ype(packet, Data) ∧is_usedGraph(packet, g) ∧ is_downStream(g) (22)

Cross layer consistency rules

As indicated in Section 5.2, packet's fields must complain with the protocol specifications and also be consistent between them. This verification is done according to each layer rules. However, an attacker can bypass this verification by giving contradictory information that fulfills each layer rules. Therefore, for some fields a cross layer verification must be applied. For example, in the case of routing information, DLL and NL fields must be consistent: wRule(perm, wnet, wSensor, sending, packet, _) ← is_dstAddr(packet, s1.addr) ∧ is_dstN LAddr(packet, s2.addr) ∧is_usedGraph(packet, g) ∧ is_N extHop(s1.addr, g, s2.addr)

wIDS detection rules

In order to detect malicious actions, wIDS apply a close policy requirement. This means that each action initiated by wireless nodes is compared to the defined security policy and a security alert is raised if the verification failed. Thus, all node's actions must:

1. be explicitly allowed by the security policy; 2. and is compliant with all rules that match the action.

Thus each IDS-agent implements Algo. 1 in order to check the compliance of actions performed by wireless nodes.

Thus, each time a node s performs an action a on object o, we first build M the set of security rules that matches the tuple {s,a,o}. If the set M is empty this indicates that there is not a security rule that explicitly permits that s performs an action a on object o. Otherwise, the tuple {s,a,o} is compared towards each rule m ∈ M to check if it is compliant with that rule (see Rule 2). If the tuple {s,a,o} is not compliant with a security rule m, it is considered as a malicious action and an intrusion rule is raised. Else, if the tuple {s,a,o} is compliant with all security rules m ∈ M , it is considered as a legitimate action. return validAction 13: end procedure

Algorithm 1 Conformity checking algorithm

Default IDS alert

We chose to model IDS alert as wContexts. This permits not only the accurate identification of the malicious action but also can allow an automatic reaction by for example the activation or deactivation of some security rules. It also allows the global coordination of alerts in the central-IDS.

To do that, we define idsAlertCtx a default context that is activated when an action performed by a wireless node violates a security rule defined in Section 5:

Basic malicious action IDS alert

In order to enforce wIDS detection capabilities, we define additional security rules that aim to detect basic actions that an attacker can perform such as intercepting, deleting, modifying, forging or delaying packets. 7 Implementation and Evaluations

Implementation

To evaluate wIDS performances, we use WirelessHART NetSIM [START_REF] Bayou | Wirelesshart netsim: A wirelesshart scada-based wireless sensor networks simulator[END_REF], a Wire-lessHART SCADA-based systems simulator. The simulated network is composed of a network manager and 9 wireless sensors. We implement IDS-agents into 3 of them and launched randomly attacks.

WSN attacks implementation

We test the proposed wIDS towards the following well-known attacks on WSN [START_REF] Karlof | Secure routing in wireless sensor networks: attacks and countermeasures[END_REF]:

-Jamming attack: A malicious node disturbs transmissions of nearby nodes by emitting packets periodically or continuously. -Denial of Service (DoS) attack: A malicious node overwhelms the targeted node by sending a great amount of packets that will not be able to receive legitimate packets. -Sinkhole and blackhole attacks: A malicious node misleads routing algorithm by transmitting false information to the base station. Consequently, a part of the traffic will be redirected to the malicious node which can drop the packets partially (wormhole) or totally (blackhole). -Hello Flood attack: A malicious node with a large transmission range can flood a large part of the network with this kind of packets. Nodes receiving these packets, will assume that the malicious node is in their transmission range and exhaust their battery life by trying to communicate with it. -Selective forwarding attack: A malicious node chooses selectively to drop some packets and to not forward them to their final destination. -Forced delay attack: A malicious node delays the forwarding of some packets which can have harmful consequences in WISN where processes are time sensitive.

Furthermore, we test it towards 2 attacks targeting wirelessHART networks:

-Sybil attack [START_REF] Bayou | Security issue of wirelesshart based SCADA systems[END_REF]: In this attack, a malicious insider node forges a fake Disconnect packet (Used by nodes to inform their neighbors that they are leaving the network), puts the targeted node as the packet source address and then authenticates it using the Network Key (Shared by all legitimate nodes).

As results, receiving nodes erase the target node from their communication planning. -Broadcast attacks [START_REF] Bayou | Security analysis of wirelesshart communication scheme[END_REF]: In this attack, a malicious insider node uses its knowledge of the Broadcast Session (A Key used to encipher end-to-end packets broadcasted by the Network Manager to all nodes) for injecting into false commands. This attack is more harmful than the previous one as the attacker pretends to be the Network Manager and can change nodes configuration parameters.

Experimental results

As indicated in Table 1, wIDS detects all tested well-known attacks. Each of these attacks, is not compliant with one or several security rules. Performed tests report 100% correct identification of malicious actions and less than 2% of false positives. Depending on which security rule is violated, false positives is about 0% for sybil or broadcast attacks and about 5% for jamming, DoS or forced delay attacks. Indeed, first cited attacks are composed of actions that are clearly identified as malicious while the second cited attacks can be assimilated to transitory transmission perturbations such as interferences. This rate may be reduced by the use of a threshold.

Attacks

Detection Rules Jamming Rule (5), Rule [START_REF] Deji | WirelessHART : Real-Time Mesh Network for Industrial Automation[END_REF]

Discussion

Previous results confirm the correctness of wIDS conception. They show that the normal behavior of wireless nodes can be modelized. As expected, the detection rate is 100% and depends highly of the accuracy of node normal behavior. By combining local and central detection, wIDS can be applied to networks of several sizes both in terms of nodes number and geographical area. Indeed, IDS-agents have the capabilities to detect basic malicious actions without any cooperation between them.

Also, by focusing on the detection of basic malicious actions, wIDS is able to detect known attacks as well as unknown ones and this without requiring any training phase.

Conclusion and Future Works

In this paper, we present wIDS an efficient intrusion detection system specially designed for enforcing wireless-based SCADA systems. It builds the normal behavior model of wireless nodes on the base of used protocol specification. Conducted tests confirm that wIDS is able to detect a large number of attacks with a low false-positive rate. These performances rely mainly on the quality of the nodes normal behavior model that depends on expert knowledges.

On the other hand, as tests were conducted in a simulated environments, some physical phenomenons were not considered. Indeed, WISN are expected to be deployed in industrial harsh environment characterized by wide temperature range, vibrations, reflections due to metallic structures, etc. Such an environment can impact communication reliability which can increase the false-positive rate.

Fig. 1 .

 1 Fig.1. Example of a WirelessHART network[START_REF] Deji | WirelessHART : Real-Time Mesh Network for Industrial Automation[END_REF]

Fig. 2 .

 2 Fig. 2. The Central-IDS and IDS-Agents Architecture

Fig. 3 .

 3 Fig. 3. IDS-agents deployment

  ∀s ∈ S, o ∈ O, a ∈ A, Hold(wnet, s, a, o, idsAlertCtx) ← Action(s, a, o) ∧ ¬actionV alidation(s, a, o) (24) where Action(s,a,o) indicates that subject s performed action a on object o and ¬actionV alidation(s, a, o) (See Algo. 1) indicates that Action(s, a, o) do not match any defined security rules.

  wRole: It is an abstraction of predefined roles used in WSN such as: wSensor, wSink, wForwarder, wCluster_head. -wDevice: It is an abstraction of wireless devices. It is composed of one or several wRole. -wActivity: It is an abstraction of wireless actions that a wDevice can perform such as: sending, receiving, forwarding and aggregating. -wView: It is an abstraction of messages sent from a wDevice to another one. -wContext: It is used to model extra conditions that a subject, an action and an object must satisfy to activate a security rule.

Thus, a security rule is defined as follows:

wRule(security_rule, wnet, d, a, v, c)

(1)

that means that in wNetwork wnet, wDevice d is granted security_rule to perform wActivity a on wView v within wContext c and where security_rule belongs to {perm, prohib, obl} (Corresponding to: permission, prohibition and obligation). Finally, concrete security rules are derived as follows:

wRule(perm, wnet, wRole, wActivity, wV iew, c) ∧empower(wnet, s, wRole) ∧ consider(wnet, a, wActivity) ∧use(wnet, o, wV iew) ∧ hold(wnet, s, a, o, c) → Is_P ermitted(s, a, o)

  empower(wnet, s, wRole): means that in wNetwork wnet, subject s is empowered in wRole. consider(wnet, a, wActivity): means that in wNetwork wnet, action a is considered an implementation of wActivity. use(wnet, o, wView): means that in wNetwork wnet, object o is used in wView. hold(wnet, s, a, o, c): means that in wNetwork wnet, wContext c is active for s, a and o.

1 .

 1 Packets and fields specification: According to the communication protocol used by the WSN, exchanged packets must follows some rules in terms of packets size and fields value. Indeed, a malicious node can inject into the network malformed packets in order to lead receiving nodes to unstable state. Forging a fake packet: In this attack, the subject s forwards a packet o however the context forwardingPacket is not active. This means that the packet o is a packet forged by s that pretends forwarding a received packet. In this attack, the subject s forwards a received packet o after that the maximum forwarding time has expired. Deleting a packet: In this attack, the subject s does not forward a received packet o within the defined time δ . Thus, a packet is considered as deleted if it has not been forwarded within the time δ (with δ < δ ). Between δ and δ a packet not forwarded is considered as delayed. 5. Modifying a packet: In this attack, the subject s forwards a modified version of a received packet o that does not complain with the used communication protocol.

	2. Hold(wnet, s, a, o, f orged_packet) ←
	empower(wnet, s, wF orwarder) ∧ consider(wnet, a, sending) ∧use(wnet, o, packets)	(26)
	∧¬hold(s, a, o, f orwardP acket)
	3. Delaying a packet: Hold(wnet, s, a, o, delayed_packet) ←
	empower(wnet, s, wF orwarder)
	∧consider(wnet, a, sending) ∧ use(wnet, o, packets) ∧packet_received(s, o, t) ∧ packet_sent(s, o , t )	(27)
	∧is_f orwadedV ersion(o, o )
	∧hold(wnet, s, a, o, F orwardP acket) ∧ (t + δ) < t
	where δ represents the maximal time a packet must be forwarded within
	since it is received.
	4. Hold(wnet, s, a, o, deleting_packet) ←
	empower(wnet, s, wF orwarder)
	∧consider(wnet, a, sending) ∧ use(wnet, o, packets) ∧packet_received(s, o, t) ∧ ¬packet_sent(s, o, t )	(28)
	∧is_f orwadedV ersion(o, o )
	∧hold(s, a, o, F orwardP acket) ∧ (t < t + δ )
	Hold(wnet, s, a, o, modif ied_packet) ←
	empower(wnet, s, f orwarder) ∧ consider(wnet, a, sending)
	∧use(wnet, o, packets) ∧packet_received(s, o, t) ∧ packet_sent(s, o , t )	(29)
	∧is_f orwadedV ersion(o, o )
	∧hold(wnet, s, a, o, f orwardP acket) ∧ is_V alidP acket(o )
	Hold(wnet, s, sending, packet, not_valid_packet) ← ¬is_V alidP acket(packet)	(25)

Table 1 .

 1 Well-known Attacks Detection

	, Rule (15)


Edward Richmond

Vuk Vukovic

Joseph Moran

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Nucleophilic Ring Opening of Donor-Acceptor Cyclopropanes Catalyzed by a Brønsted Acid in Hexafluoroisopropanol

published or not. The documents may come   L'archive ouverte pluridisciplinaire

Nucleophilic Ring-Opening of Donor-Acceptor Cyclopropanes Catalyzed by Brønsted acid in Hexafluoroisopropanol

Edward Richmond, Vuk D. Vuković, Joseph Moran* University of Strasbourg, CNRS, ISIS UMR 7006, 67000 Strasbourg, France Supporting Information Placeholder ABSTRACT: A general, Brønsted acid catalyzed method for the room temperature, nucleophilic-ring opening of donor-acceptor cyclopropanes in fluorinated alcohol solvent, HFIP, is described. Salient features of this method include an expanded cyclopropane scope; including those bearing single keto-acceptor-groups, and those bearing electron deficient aryl-groups. Notably, the catalytic system proved amenable to a wide range of nucleophiles including arenes, indoles, azides, diketones and alcohols. Donor-acceptor (DA) cyclopropanes serve as 'springloaded' synthetic intermediates owing to the inherent C-C bond polarization afforded by the synergistic combination of donor-and acceptor substituents. 1 Consequently, they have found widespread application in modern synthetic organic chemistry, and a range of catalytic methodologies have been developed that engage DA-cyclopropanes in cycloaddition, [START_REF] Pohlhaus | For selected examples of D-A cyclopropanes engaging in catalytic [3+2]-cycloadditions[END_REF] 1,3-difunctionalization 3 and homo-conjugate addition-type reactions 4 with a variety of nucleophiles including amines, alcohols, thiols, carboxylic acids and azides. [START_REF] Braun | For the use of thiols as nucleophiles[END_REF] Outside of reactions with heteroatomic nucleophiles, a handful of catalytic arylation reactions of DA-cyclopropanes have been developed, however currently developed systems are typically limited to a single class of nucleophiles such as indole derivatives, 6 anilines, 7 electronically-activated anisole derivatives 8 and 2naphthols. 9 Typically, all of the aforementioned catalytic systems employ high (10-20 mol%) loadings of Lewis acidic catalysts, 10 namely rare-earth triflates, with the reactions typically operating at elevated temperatures. As these Lewis acidic catalyst systems seek to take advantage of dual-coordination to geminal diester-bearing cyclopropanes, a striking limitation in terms of cyclopropane substitution becomes apparent. Likewise, the activation of such donor-acceptor cyclopropanes relies on polarization of the C-C bond by the synergistic interaction of the donor and acceptor groupings. Consequently, in almost all conjugate addition-type ring-openings the tolerated donor-substitution is limited to electron-donating or electronneutral aryl-substituents (Figure 1, Top).

Given our recent investigations into aggregation phenomena in acid catalysis 11 we recognized an opportunity to develop an alternative Brønsted acid-catalyzed protocol for the activation of DA-cyclopropanes. We hypothesized that a strong Brønsted acid catalyst system would provide a dual-advantage in the activation of donor-acceptor cyclopropanes; allowing both a wider nucleophile scope, and the employment of a wider range of cyclopropane scaffolds above and beyond the typical structural limitations. Herein, we report the successful realization of such a scenario, whereby trifluoromethanesulfonic acid (TfOH) in hexafluoroisopropanol (HFIP) [START_REF] Saito | For examples of other HFIP-enabled strong Brønsted acid catalyzed reactions[END_REF][START_REF] Berkessel | For studies pertaining to the properties of HFIP in the context of organic reactivity[END_REF] acts as a highly active and general catalyst system for the nucleophilic ring-opening of donor-acceptor cyclopropanes. A wide array of nucleophiles (C-, O-, N-) can be employed in the protocol, and typical limitations of the donor-acceptor cyclopropane architecture have also been surpassed, allowing chalcone derived cyclopropanes bearing a single keto-acceptor motif to engage in catalytic nucleophilic ring-opening (Figure 1 -This work). The devel-oped method is also highly user-friendly providing numerous practical advantages; the reactions operate at ambient temperature, under open-flask conditions with most reactions typically complete within 3 hours.

Synthetic investigations began with a benchmark reactionthe arylative ring-opening of donor acceptor cyclopropane 1a 14 in combination with 1,3,5-trimethoxybenzene; a reaction known to proceed at 80 ºC in the presence of 20 mol% of Yb(OTf) 3 . 8c It was rapidly established that by slight modification of catalytic conditions already established within the group, 11d the arylative ring-opening of such cyclopropanes could be initiated at room temperature by TfOH when employing HFIP as solvent. Further slight tweaking established 10 mol% of TfOH in HFIP as a reliable system for this transformation leading to complete conversion in just 3 hours and a 95% yield of the desired arylated material 2a after simple column chromatography (Scheme 1).

Scheme 1. Scope of Brønsted Acid catalyzed Arylative

Ring-Opening of Donor-Acceptor Cyclopropanes bearing a geminal diester motif a a Isolated yields after column chromatography. b Isolated as a mixture of regioisomers, see SI for further details. c Reaction performed at 40 ºC for 4 h. d Reaction performed at 50 ºC for 24 h.

Application of these catalytic reaction conditions across a range of donor-acceptor cyclopropane substrates was then undertaken. 1,2,4-Trimethoxybenzene also proved an excellent nucleophile furnishing the desired product 2b in 85% yield. Reaction of various cyclopropane substrates bearing electron donating or neutral aryl-substituents with a range of di-and tri-methoxybenzene derivatives provided the desired arylated products in moderate to good yields (2c-2h) including arylated diethylester 2f. 2,6-Dimethylphenol also proved an excellent nucleophile in this system generating arylated product 2i in 97% yield. A donor-acceptor cyclopropane bearing a 2fluorophenyl substituent was also well tolerated in this catalytic system, delivering arylated products 2j, 2k, and 2l with 1,3,5-trimethoxybenzene, mesitylene and 2,6-dimethylphenol respectively. As a further demonstration of the generality of the developed catalytic system, donor acceptor cyclopropanes bearing a 4-nitrophenyl group and a 4-benzonitrile aryl substituent were also smoothly engaged in arylation with 1,3,5trimethoxybenzene and mesitylene (2m-2o) in good to excellent yields.

Scheme 2. Scope of Brønsted Acid catalyzed Arylative

Ring-Opening of Donor-Acceptor Cyclopropanes bearing a keto-acceptor group a a Isolated yields after column chromatography. b Reaction performed with 5 mol % TfOH. c Isolated as a mixture of regioisomers, see the supporting information for further details. d Reaction performed at 80 ºC.

Attention next turned to donor-acceptor cyclopropanes bearing a single ketone substituent as the 'acceptor' motif. To the best of our knowledge, such scaffolds have yet to find widespread uptake as substrates in catalytic cyclopropane methodology development owing to the prior focus on Lewis acid catalyzed methods believed to require a geminal diester cyclopropane substitution pattern. Nevertheless, upon reaction with 1,3,5-trimethoxybenzene, chalcone derived cyclopropane 1k delivered the desired arylated product 2p in 98% yield (Scheme 2). Furthermore, this reaction was successfully scaled up to 2.5 mmol, catalyzed by only 5 mol% TfOH, and duly delivered 0.971 g of the arylated product in 99% yield. Variation of the nucleophilic component in this reaction system proved unproblematic (2q-2s), as did variation of the chalcone-derived cyclopropane scaffold to include electron-rich aryl groups (2t and 2u) and halogenated aryls (2v and 2w). Notably, mesitylene (2r), naphthalene derivatives (2s and 2w), 2,6-dimethylphenol (2t), and anisole (2u) were all tolerated in the reaction system in excellent yield. Once again, donoracceptor cyclopropanes bearing electron deficient arylsubstituents (4-NO 2 and 4-CF 3 ) were successfully engaged in arylative ring-opening (2x, 2y and 2z) with only moderate heating required in the case of the reactions employing the 4nitro substituted starting material. Additionally, cyclopropanes bearing heterocyclic motifs were also successfully engaged in arylative ring-opening with 1,3,5-trimethoxybenzene under slightly modified conditions; 15 thiophene-bearing products 3a and 3b were isolated in 60% and 93% yield respectively, yet methyl-furan bearing product 3c proved sensitive to decomposition during purification and was only isolated in trace amounts (Scheme 3). Further investigation of this reaction system revealed that the same catalytic conditions were able to promote cyclopropane ring-opening with nucleophiles other than activated arenes. Reaction with diketones proceeded smoothly to yield highly functionalized products 4a and 4b in 78% and 50% yield respectively. Investigation of the reactions of donor-acceptor cyclopropanes with indoles revealed HFIP to be an inefficient solvent for such reactions, most likely owing to its ability to hydrogen bond to basic groups, thus attenuating the nucleophilicity of these species. Rather, N-methylindole proved a competent reaction partner with donor-acceptor cyclopropanes when employing B(C 6 F 5 )•H 2 O as a catalyst in nitromethane, a catalytic duo previously investigated in our research group. 11a Under these conditions, products 4c and 4d were delivered in 85 and 68% yield respectively. Ring opening with TMS-N 3 also proved facile with the developed catalytic protocol, with products 4e-4h isolated in good to excellent yield. Additionally, primary alcohols could be employed as nucleophiles with no change in reaction conditions required and products 4g-4i were delivered as expected in up to 90% yield (Scheme 4).

In a system designed to shed light on the mechanistic course of such cyclopropane opening reactions, treatment of enantiopure cyclopropane (S)-1a with 1,3,5-trimethoxybenzene under standard conditions delivered (R)-2a in high yield. 16 This observation is in line with prior Lewis acid catalyzed protocols 8c and suggests that under Brønsted acid catalyzed conditions, cyclopropane ring-opening occurs via a predominantly S N 2-like mechanistic pathway. This allows the following mechanistic rationale to be proposed (Scheme 5). Initial protonation of the cyclopropane 'acceptor-motif" by Brønsted acid catalyst, 17 leads to an increase in cyclopropane C-C bond polarization, thus activating the benzylic carbon to nucleophilic attack by the nucleophilic species in a mechanism analogous to an S N 2-like displacement. Subsequent enoltautomerization or protonation, together with proton abstraction, regenerates Brønsted acid to enable turnover of the cycle and in the process delivers the desired ring-opened product.

Scheme 5. A plausible mechanistic scenario.

In conclusion, a unified Brønsted acid catalyzed nucelophilic ring-opening of donor-acceptor cyclopropanes has been developed. The salient features of this system are the operatorfriendly reaction procedure, and the wide scope with respect to both the cyclopropane scaffold and nucleophile. The combination of TfOH and HFIP provide a simple yet highly active Brønsted acid system allowing novel classes of cyclopropane, including those bearing electron-deficient aryl groups and those derived from chalcones, to engage in nucleophilic ringopening reactions for the first time. Initial observations suggest that ring-opening occurs via an S N 2-like mechanistic pathway, however comprehensive mechanistic studies into the Brønsted acid catalyzed activation of a range of small-ring cycloalkyl-species are currently ongoing within our laboratory, and will be reported in due course.

ASSOCIATED CONTENT Supporting Information

H

The Supporting Information is available free of charge on the ACS Publications website.

Optimization data, experimental procedures, characterization of new compounds, and spectral data (PDF)

Figure 1 .

 1 Figure 1. Existing Lewis acid catalyzed methodologies for the nucleophilic ring-opening of diester-bearing D-A cyclopropanes. This work: Brønsted acid catalyzed nucleophilic ringopening of a wide range of donor-acceptor cyclopropanes.

Scheme 3 .Scheme 4 .

 34 Scheme 3. Brønsted Acid catalyzed Arylative Ring-Opening of Donor-Acceptor Cyclopropanes bearing heterocyclic donor-groups a a Isolated yields after column chromatography.

ACKNOWLEDGMENT

This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement n° 639170) and by grants from LabEx "Chemistry of Complex Systems". V.D.V. thanks the French government for an MRT fellowship. We thank Dr Helmut Muenster of MasCom and Dr Jean-Louis Schmitt (ISIS, CNRS, UMR7006) for their assistance with HRMS analysis.

AUTHOR INFORMATION Corresponding Author

*moran@unistra.fr

Author Contributions

The manuscript was written through contributions of all authors. / All authors have given approval to the final version of the manuscript.