D Frindel

H Rositi

V Hubert

L Weber

E Ong

L.-P Berner

C Frindel

D Rousseau

C Olivier

M Langer

T.-H Cho

N Nighoghossian

Y Berthezène

F Peyrin

F Chauveau
email: chauveau@cermep.fr

M Wiart

Abstract submitted for contribution to the User-dedicated Microsymposium (UDM2): "Quantitative coherent X-ray diffraction imaging" High throughput three-dimensional imaging of myelin fibers in the whole mouse brain

High throughput three-dimensional imaging of myelin fibers in the whole mouse brain

Introduction. Injury to the white matter (WM) leads to severe functional loss in many neurological diseases such as stroke and multiple sclerosis. In-vivo neuroimaging techniques such as diffusion tensor imaging are becoming important tools for the diagnosis of WM abnormalities. However, these tools still present limitations and there is a crucial need for whole-brain ex-vivo complementary approaches to overcome them [1]. We propose a novel three dimensional (3D) imaging method to map the myelin fibers in the whole mouse brain with high throughput using in-line phase contrast X-ray tomography. Methods. Twelve C57Bl6 mice were included in the present study (stroke: N=3, focal demyelination: N=2, healthy&sham: N=7). The impact of fixation was examined in 5 of the healthy brains fixed either by paraformaldehyde (PFA) 4% or ethanol (range [25%-96%]). All subsequent brains were fixed with ethanol 96%. Imaging was performed on beamline ID19 at ESRF at 19keV as described in [2]. An indirect detection-based detector with a LuAg scintillator, standard microscope optics and a 2048x2048 pixel CCD camera was positioned 1-m from the sample to obtain phase contrast. The whole-brain data set was acquired at an isotropic pixel size of 7.5-µm. Acquisition time was 14 minutes per brain. 3D images were reconstructed by Filtered Backprojection after phase retrieval based on [3]. Results. In contrast to PFA fixation, ethanol >50% led to hyperintense WM fibers, allowing accurate 3D representation of main fiber tracts (Fig 1). Our imaging approach revealed the complexity of fiber orientations and intrication, and distinguished individual axons in the fiber bundle (see st in

Conclusion.

The proposed set-up permits brain-wide studies of fiber tracts and of their structural changes in diseases, using conventional animal models, minimal sample preparation, and with the potential to scan 30 brains in an 8-hours shift.

  Fig 1A). Focal WM lesions were clearly depicted both at the macroscopic (Fig 1: CPu and int demyelination, plain arrow; other lesions, arrow heads) and microscopic (Fig 1: st demyelination, thin arrow) levels.

Figure 1 :

 1 Figure 1: MIP in an animal model of demyelination: axial (A), coronal (B), contralateral sagittal (D) and ipsilateral sagittal (E) views. Focal demyelination of caudate putamen is clearly seen (plain arrow in A, C et E). Other focal lesions are shown in the ipsilateral (left) side with an arrow head: disorganization of the bed nuclei of the st (A), demyelination of the aco (B) and lateral ventricle collapse (C). Demyelination of stria terminalis is also detected despite the small size of this fiber tract (thin arrow in A, B and C). Abbreviations: aco anterior commissure, olfactory limb; act anterior commissure, temporal limb; alv alveus; cc corpus callosum; cg cingulum; chpl choroid plexus; cpd cerebral peduncle; CPu caudate putamen; df dorsal fornix; fi fimbria; fr fasciculus retroflexus; fx columns of the fornix; int internal capsule; mtt mammillothalmic tract; opt optical tract; pc posterior commissure; sm stria medularis; st stria terminalis..

Acknowledgments. LABEX PRIMES (ANR-11-LABX-0063) -ESRF (project LS-2292)


Sooyeon Shin

Seungyeon Kim

Taekyoung Kwon
email: taekyoung@yonsei.ac.kr

Identification of Corrupted Cloud Storage in Batch Auditing for Multi-Cloud Environments

Keywords: Cloud computing, Provable data possession, Public auditing, Batch auditing, Identification for the corrupted clouds

In cloud storage services, users can store their data in remote cloud servers. Due to new and challenging security threats toward outsourced data, remote data integrity checking has become a crucial technology in cloud storage services. Recently, many integrity checking protocols have been proposed. Several protocols support batch auditing, but they do not support efficient identification when batch auditing fails. In this paper, we propose a new identification method for the corrupted cloud in multi-cloud environments without requiring any repeated auditing processes.

Introduction

In cloud storage service, users' outsourced data can be lost or corrupted due to outside and inside threats [START_REF] Claycomb | Guest Editorial: Emerging Trends in Research for Insider Threat Detection[END_REF], [START_REF] Lindauer | Generating Test Data for Insider Threat Detectors[END_REF] but cloud servers might hide data loss incidents by claiming that the data are still correctly in the cloud in order to maintain their reputation. Thus, users need to be able to verify that their outsourced data are correctly stored in the cloud. Recently, many remote integrity checking protocols have been proposed to support public auditability that allows a third party auditor to verify the correctness of outsourced data on demand without retrieving a copy of the whole data [START_REF] Ateniece | Provable data possession at untrusted stores[END_REF], [START_REF] Shacham | Compact proofs of retrievability[END_REF], [START_REF] Wang | Enabling public verifiability and data dynamics for storage security in cloud computing[END_REF] [START_REF] Wang | Privacy-preserving public auditing for data storage security in cloud computing[END_REF], [START_REF] Zhu | Dynamic audit services for integrity verification of outsourced storages in clouds[END_REF], [START_REF] Zhu | Cooperative provable data possession for integrity verification in multicloud storage[END_REF], [START_REF] Yang | An efficient and secure dynamic auditing protocol for data storage in cloud computing[END_REF], [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF], [START_REF] Kai | An efficient public batch auditing protocol for data security in multi-cloud storage[END_REF]. As cloud computing has been widely adopted, a third party auditor may take charge of multiple auditing delegations from different users. To improve auditor efficiency, several protocols support batch auditing, which allows the auditor to simultaneously handle multiple auditing delegations from a large number of different users [START_REF] Wang | Privacy-preserving public auditing for data storage security in cloud computing[END_REF], [START_REF] Zhu | Cooperative provable data possession for integrity verification in multicloud storage[END_REF], [START_REF] Yang | An efficient and secure dynamic auditing protocol for data storage in cloud computing[END_REF], [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF], [START_REF] Kai | An efficient public batch auditing protocol for data security in multi-cloud storage[END_REF]. For batch auditing, multiple proofs on distinct data of different users are aggregated into a single proof. If a single data block or authenticator has been corrupted or discarded, batch auditing will fail and the benefits of batch auditing could be canceled out. Wang et al. suggested a divideand-conquer approach (e.g., binary search) in order to identify the corrupted data [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF] and Kai et al. recommended an encoding and decoding approach to reduce communication overhead when batch auditing fails [START_REF] Kai | An efficient public batch auditing protocol for data security in multi-cloud storage[END_REF]. However, both approaches are inefficient because repeated auditing processes are needed.

To address these problems, in this paper, we propose a new identification method for the corrupted cloud based via two batch auditing schemes [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF], [START_REF] Yang | An efficient and secure dynamic auditing protocol for data storage in cloud computing[END_REF] in multi-users and multi-cloud environments. When the data of users on the single cloud are corrupted, our protocol can identify the corrupted cloud without requiring any repeated auditing processes by utilizing an unique indexing value assigned to each cloud server.

We briefly introduce batch auditing and describe our identification method for the corrupted cloud server in Section 2 and Section 3, respectively. In Section 4, we conclude this paper.

Users

1 ? = L Y l=1 ( A l D l • H l ) [Eq. 1]
Fig. 1. System model of batch auditing.

Batch Auditing

We consider batch auditing for multi-cloud data storage systems involving multiusers and L multi-cloud servers, and the third-party auditor (TPA), as illustrated in Fig. 1. The users store their data in the remote cloud and rely on them for data maintenance. Each cloud server CS l (1 ≤ l ≤ L) provides powerful storage, computational resources, and the data access to users. The TPA has the expertise and capability to audit data storage on behalf of the user upon request.

For batch auditing, we take two batch auditing schemes into consideration: Wang et al's privacy-preserving public auditing scheme (hearafter, W-BA) [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF] and Yang & Jia's efficient and secure dynamic auditing scheme. The original W-BA provides batch auditing for multi-users of single cloud server but it is possible to extend W-BA to support batch auditing for multi-users of multi-cloud servers. Batch auditing consists of three phases: system initialization, setup, and audit. system initialization phase involves a ParaGen step to generate system parameters and the setup phase involves KeyGen and AuthGen steps. In KeyGen step, a user generates a key pair (public key and secret key) used for computing authenticators of data. In AuthGen step, the user computes authenticators used for further auditing then stores them with the data in the remote cloud servers. When multi-users of multi-cloud servers request auditing to the TPA, the TPA performs an audit phase through Challenge, Prove, and Verify steps. In Challenge, the TPA randomly selects the number of data blocks for each user and sends a challenge message C to each cloud server involved in batch auditing. In Prove, upon receiving a challenge message, each cloud server sends a response message P as a proof of possession to the TPA. The proof P includes the data proof D and the authenticator proof A. In Verify, upon receiving the proofs from the challenged servers, the TPA performs batch verification to check the correctness of all proofs at the same time. The TPA firstly computes the challenged hash H l for each cloud server in the challenged servers and simultaneously verifies all proofs via [Eq. 1] in Fig. 1. If the batch verification holds, it means that all challenged servers correctly maintain the data of users.

Identification for Single Corrupted Cloud

Batch verification only holds when all of the proofs are valid and fails when there is even one invalid proof of single user in batch auditing. In many situations, a proof collection may contain invalid proofs caused by malicious cloud server or accidental data corruption. If the batch verification equation ([Eq. 1]) fails, it means that a proof of single cloud server is invalid. In this case, the TPA runs Identify step to determine which server's proof is invalid.

1. The TPA sequentially allocates an index I l (I l = 1, • • • , π) to each CS l , where π is the number of challenged cloud servers. For example, the second server in the challenged servers has 2 as the index. 2. Let T is the right side of [Eq. 1]. By exponentiation of the corresponding index I l for each cloud server CS l , the TPA computes T as

T = L l=1 ( A l H l • D l ) I l [Eq. 2].
3. When the data of a single server CS o are corrupted, T will be ∆o, the difference between the original data and the corrupted data . Similarly, T will be ∆o Io , the I o -th power of ∆o. The TPA can identify the corrupted server by multiplying T by T until the result equals to T where T ? = I l i=1 T . Consequentially, M -1 will be the index for the corrupted server CS o , where M is the number of multiplications.

There can be several cases of corruption as follows: only data blocks are corrupted or discarded, only authenticators are corrupted or discarded, and both data blocks and authenticators are corrupted or discarded. To hide those corruptions and to deceive the TPA, the malicious cloud server may generate the proof using the user's another valid and uncorrupted pairs (data block and the corresponding authenticator), another user's pairs, random data blocks, or the previous proof. ∆o can have several forms according to the above cases. However, it is possible for the proposed method to identify the corrupted server regardless of the forms of ∆o.

Conclusion and Future Work

In this paper, we proposed a new identification method for the corrupted cloud in multi-users and multi-cloud environments. When the data of users on the single cloud are corrupted and thus batch auditing fails, our method can identify the corrupted cloud without requiring any repeated auditing processes by utilizing an unique index for each cloud server.

As part of future work, we would analyze the performance of the proposed identification method and compare it with the divide-and-conquer approach [START_REF] Wang | Privacy-preserving public auditing for secure cloud storage[END_REF] and sequential re-verification for each server one by one.

  This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2015-H8501-15-1008) supervised by the IITP(Institute for Information & communications Technology Promotion). T. Kwon is the corresponding author.

  Prove P = (D, A)


Olivier Gerber

Sylvie Bégin-Colin

Benoit P Pichon

Elodie Barraud

Sébastien Lemonnier

Cuong Pham-Huu
email: cuong.pham-huu@unistra.fr

Barbara Daffos

Patrice Simon

Jérémy Come

Dominique Bégin
email: dominique.begin@unistra.fr

Jeremy Come
email: jeremy0come@gmail.com

Design of Fe3-xO4 raspberry decorated graphene nanocomposites with high performances in lithium-ion battery

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

Introduction

Lithium-ion batteries (LIBs) are widely used in portable electronic devices, and show increasing interest for powering electric vehicles [1] . To date, most of commercial LIBs use graphite as negative electrode thanks to its low discharge plateau and cycling stability [1][2][3][4] . However, graphite specific capacity is limited to 372 mAh/g upon Li + intercalation, and exhibits poor rate performance associated with the risk of metallic Li deposition at high charging regimes [1,5] . To meet the demand in high energy and high power electrochemical storage devices, alternative anode materials have been investigated [6,7] , including alloying reaction metals [8] , or conversion reaction oxides [9][10][11] . Among them, spinel iron oxide Fe 3 O 4 has been considered as a promising oxide ✩ This work was supported by the funding from the European Research Council (ERC, Advanced Grant, ERC-2011-AdG, Project 291543-IONACES). The authors also acknowledge the funding from the Materials Institute Carnot Alsace (MICA) and from the Direction Générale de l'Armement (DGA) and French-German Research Institute of Saint-Louis (ISL). thanks to its high theoretical capacity of 924 mAh/g, its environmental benign, large abundance and low cost [5,6,9,[12][13][14][15][16] . Moreover, Fe 3 O 4 shows a potential around 1 V versus Li + /Li, which provides better safety versus metallic Li deposition at high rate. However these applications are limited by poor cycling performance arising from the structure breakdown linked with volume change during the electrochemical reaction with Li, as well as important polarization during the charge/discharge processes [5,15,17,18] . To increase the number of cycles, various approaches have been proposed such as carbon based coating [15,19] , electrodes nanostructuring [11,16,17,20] , or nanocomposites [5,18,21] . Taberna et al. proposed to attach Fe 3 O 4 nanoparticules onto nanostructured copper foil by electrodeposition [11] but the best performances were obtained using carbon-based composites such as carbon shells, carbon nanotubes, or graphene [16,[22][23][24] . Besides, Fe 3 -x O 4 nanostructures, consisting of aggregates of nanocrystals, have shown interesting performances as electrode material [25,26] but the low electronic conductivity of iron oxide leads to poor rate performance and they require thus the addition of non-electroactive material such as acetylene black.

Graphene and few-layer graphene (FLG) materials have received an ever increasing scientific interest during the last decades thanks http://dx.doi.org/10.1016/j.jechem.2016.01.021 to their exceptional physical properties [27][28][29][30] . These 2D materials can be synthesized by different methods such as micromechanical alleviation of graphite, liquid-phase exfoliation, mechanical ablation, high-temperature treatment of silicon carbide, catalytic or chemical unzipping of carbon nanotubes as well as chemical vapor deposition (CVD) or by reduction of graphene oxide (GO) [31][32][33][34][35][36] . In the LIB application, it is expected that graphene and FLG could play a significant role to stabilize deposited transition metal oxides, improving the electrical conductivity of the composite and voids for accommodating volume change during the charge/discharge cycles.

We recently synthesized nanohybrid materials combining metal oxide nanoparticles ( M = Co or Fe) with an extremely narrow size distribution and carbon nanotubes [37,38] or few-layer graphene (FLG) [39] with a metal oxide content up to 50%. Iron oxide nanoparticles with mean diameter ranged from 5 to 50 nm (depending on the synthesis conditions) were well dispersed on both side of the FLG surface, according to the recent TEM tomography analysis [40] . These nanoparticles further act as spacers to prevent the complete restacking of the FLG through van der Walls forces.

Using a similar approach, porous Fe 3 -x O 4 hollow nanostructures with a raspberry shape, narrow size distribution, well-defined chemical composition and crystalline structure [30] were successfully grown onto few-layer graphene sheets with highly controlled covering density. These nanostructures consist of oriented aggregates of magnetite nanocrystals (nanocrystals with common crystallographic orientations directly combined together to form larger ones) which ensure a nanostructuration, porosity and a low oxidation state of Fe 3 O 4 nanocrystals [41] . The structure of such a composite presents several interests for electrode material such as (i) a high porosity that provides both high electrode/electrolyte interface area and fast Li + diffusion path toward active reaction sites, (ii) a preservation of the magnetite composition at low nanocrystal sizes (as described in ref. [30] ) that improves the capacity performance, and (iii) a highly conductive graphene matrix that provides an excellent interface with the Fe 3 -x O 4 nanostructures and ensures high electronic percolation without the need of conducting additives, and (iv) the strong interaction between the iron oxide and the graphene surface which significantly reduces the problem of deactivation linked with the excessive sintering of the iron oxide compounds upon LIB experiments. The 2D morphology of the FLG also contributes to the flexibility of the composite as a function of charge/discharge cycle and to prevent the breaking of the composite structure for long-term operation.

In this work, we report on the use of these Fe 3 -x O 4 raspberry shaped nanostructures deposited on graphene sheets (synthesized by an "ultimate" exfoliation of expanded graphite), as anode material for LIB application. The composite demonstrates specific capacity values as high as 660 mAh/g at 8 C with excellent cycling stability. The samples, before and after LIB tests, were also characterized by different techniques in order to get more insight about the possible structural modification during the charge/discharge cycling and also for subsequence optimization process.

Experimental

Graphene and few-layer graphene synthesis

Few-layer graphene (FLG) powders were obtained using a technique derived from the synthesis developed by Janowska et al. based on an "ultimate" exfoliation of graphite-based material or expanded graphite [42,43] . The expanded graphite powder Carbon Lorraine was dispersed in ethanol by an ultrasonic treatment (finger) during 30 min: ultrasonic finger is a "Branson" instrument (Digital sonifier 450) with a maximal power of 400 W (in reality 20% to 40% of the maximal power was used). After the solution containing the powder was decanted for 1 h, the supernatant solution containing the smaller particles was collected and the operation was repeated two times to obtain the few-layer graphene powder.

Synthesis of Fe 3 -x O 4 @graphene hybrid nanostructure

The Fe 3 -x O 4 @graphene was synthesized by a one-step mixed polyol-solvothermal method. In a typical synthesis, iron chloride hexahydrate (1.00 mmol), succinic acid (0.33 mmol), urea (10.0 mmol) and a given amount of graphene (10.0 mg, 20.0 mg and 100.0 mg) were dispersed in ethylene glycol (10.0 mL) by vigorous mechanical stirring and ultrasonication. The solution was subsequently sealed in a Teflon lined stainless steel autoclave (20 mL volume), slowly heated at 200 °C for 4 h and maintained at this temperature for 10 h. After cooling down to room temperature, the precipitated powder was separated by centrifugation and was then washed several times using deionized water and ethanol. Finally, the powder was freeze dried before characterizations. Samples were named NC-10, NC-20 and NC-100 accordingly to the amount of graphene used.

Structural characterizations

Scanning electron microscopy (SEM) analysis was carried out on a JEOL 6700F microscope working at 10 kV accelerated voltage. Transmission electron microscopy (TEM) was carried out using a JEOL 2100F (voltage 200 kV) microscope with a point resolution of 0.2 nm. The sample was dispersed in ethanol by ultrasonication during 5 min and a drop of the solution was then deposited on a copper grid (covered with a carbon membrane). X-ray diffraction (XRD) was carried out using a Bruker D8 Advance in the 27 °-75 °(2 θ ) range with a scan step of 0.03 °. The detector was a three degrees wide analysis detector ("Lynx Eye"). Thermal gravimetric analyses were carried out with a TA Instrument (Q-50 0 0 model). They were performed under an air flow (20 mL/min) up to 10 0 0 °C with a heating rate of 5 °C/min. The specific surface area was determined with a Micromeritics sorptometer (Tristar). The sample was outgassed at 250 °C under vacuum for 12 h in order to desorb moisture and adsorbed species on its surface. The measurements were carried out using N 2 as adsorbent at liquid N 2 temperature.

Electrochemical characterizations

2-electrode Swagelok cells were assembled in an argon-filled glove box using the nanocomposite powder as the positive electrode and the Li metal as the negative electrode. A Whatman GF/B borosilicate glass-fiber (520 µm-thick) saturated with 1 M LiPF 6 electrolyte solution (in EC : DMC = 1 : 1 in volume ratio) was used as the separator. Powders were used without any conducting additives. The electrode loading was between 2 and 2.5 mg/cm 2 . All measurements were carried out using a Bio-Logic WMP 3 potentiostat, between 0.05 and 3 V (versus Li/Li + ). The rate performance was obtained by the so-called "signature" experiment as described in details in the reference [11] .

Results and discussions

Fig. 1 (a-d) shows SEM images of the graphene/Fe 3-x O 4 nanocomposites with three different weight ratios raspberry Fe 3 -x O 4 nanostructures/graphene (1 for NC-100, 5 for NC-20 and 10 for NC-10). The mean Fe 3 -x O 4 nanostructure size is centered to 250 nm and is very similar for all three samples meaning that the amount of graphene does not affect the formation of iron oxide nanostructures. They consist of original orientated aggregates of Fe 3 -x O 4 nanocrystals ( Fig. 1 e) with a mean size of 25 nm, mainly constituted of the magnetite phase (Fe 2.90 O 4, 70% of magnetite) and exhibiting a porous and hollow structure with a BET specific surface area of 27 m 2 /g [41] . The spatial distribution of nanostructures onto the graphene sheets is relatively homogeneous for all nanocomposites, with higher volumetric mass density for the sample with low amount of graphene ( Fig. 1 a-d). Such strong interactions may be attributed to the nucleation-growth of nanostructures from defects and/or steps onto graphene sheets ( Fig. 1 b) [39] . It is also worthy to note that the synthesis is extremely selective for preparing Fe 3 -x O 4 aggregated nanostructures with controlled size as high-resolution SEM micrograph ( Fig. 1 e) clearly shows.

The strong interaction between nanostructures and graphene sheets, especially the graphene sheet border, is clearly visible on the edges where nanostructures "marry" the shape of the sheet ( Fig. 2 a). According to these results, one can state that the iron oxide nucleation also started at the defect sites localized on the border of the graphene sheets where sites with high reactivity are present. The high reactivity of the border sites on the FLG has already been reported by other research groups in the literature showing the decoration of the graphene border with subnanometer platinum clusters [44,45] . High resolution SEM micrograph also evidences the formation of iron oxide aggregates with different morphology on the FLG surface ( Fig. 2 b). Indeed, despite a large part of the iron oxide aggregates are in a round-shaped form, the SEM micrograph also reveals the presence of some other iron oxide aggregates with a hemi-sphere shape on the edge sites of the FLG (indicated by arrows) which strongly confirms the high interaction between the deposited iron oxide aggregates and the FLG surface.

The microstructure of the Fe 3 -x O 4 aggregates, well dispersed on a high surface area alumina support in order to avoid the overlapping, was also analyzed by TEM and the representative TEM micrographs are presented in Fig. 3 . The TEM results confirm the ho-mogeneous size of the iron oxide aggregates ( Fig. 3 a) while highresolution TEM clearly evidences the presence of Fe 3 -x O 4 nanoparticles within the aggregate ( Fig. 3 b). It is expected that such iron oxide nanoparticle assembly will provide an "easy access" for the lithium ion insertion while the hollow structure of the aggregate allows the composite to resist to the expansion consecutive to the lithium insertion.

TGA curves ( Fig. 4 a) have shown that theoretical and experimental carbon/Fe 3 -x O 4 weight ratios are very close which confirms the high efficiency of the synthesis method for decorating the FLG surface with controlled size of iron oxide nanostructures. Its variation between 2 and 0.1 is perfectly correlated to the amount of carbon added in the reaction medium. X-ray diffraction pattern ( Fig. 4 b) confirms that the iron oxide aggregated nanostructures are constituted of the spinel iron oxide with a composition very close to that of the magnetite phase (JCPDS 19-0629).

Electrochemical characterizations of nanocomposites in Li-ion cells

The NC-100 nanocomposite has been found to be the most efficient as anode material in Li-ion device. Fig. 5 shows the Cyclic Voltammograms (CVs) of NC-100 in 1 M LiPF 6 in EC : DMC (1 : 1 in volume ratio) electrolyte at 0.2 mV/s. Starting from the Open Circuit Voltage (OCV) at 2.9 V versus Li down to 0.1 V versus Li, the first cycle shows a slight reduction peak at 1.5 V versus Li and an important redox peak at 0.55 V versus Li. The small peak at 1.5 V is associated with the structure transition caused by Li insertion into Fe 3 O 4 (Fe 3 O 4 + x Li + + x e -→ Li x Fe 3 O 4 ). The peak at 0.55 V versus Li corresponds to the further transformation of Li x Fe 3 O 4 into metallic Fe through the conversion reaction (Li x Fe 3 O 4 + (8-x )Li + + (8x )e -→ 4Li 2 O + 3Fe), together with the formation of the SEI layer on the graphene/Fe 3 O 4 electrode [33] . From 0.2 V down to 0.1 V versus Li, the reversible intercalation of Li ions into graphene layer scan be seen, according to 2C + Li + + e -→ LiC 2 [34] .

During positive scan (oxidation), the Li de-insertion is visible at 0.2 V versus Li. The peaks at 1.68 V and 1.89 V versus Li correspond to the reverse of the reduction reaction that is the oxidation of metallic Fe into Fe 2 + and Fe 3 + , respectively. The shift in the peak potentials between the first and subsequent cycles originates from the thermodynamics of the conversion reaction [11] . x )e -→ 4Li 2 O + 3Fe) observed at 0.8 V; the end of the plateau and the slopping zone correspond to the SEI formation. Upon cycling, the well-known hysteresis associated with the conversion reaction is observed, that leads to an important polarization between charge and discharge.

The graphene/iron oxide nanocomposite shows a stable capacity behavior with cycles (inset Fig. 6 ). The capacity reaches 330 mAh/g on the composite basis weight which is accounted to 660 mAh/g for Fe 3 O 4 (the capacity of graphene alone was measured and is negligible). Such a value is slightly below previous ones reported in the literature for magnetite or graphene/iron oxide composite materials [11,46,47] . However, the weight loading used here (2.5 mg/cm ²) allows reaching a real capacity of 0.8 mAh/cm ² that compares favorably to previous work. At this time, the values measured in the case of NC-10 and NC-20 are lower: the metal oxide/graphene weight ratio must be optimized to obtain a good electrical contact between the nanostructures and the graphene sheets. The electrodes synthesized from NC-100 were able to discharge up to 8 C still keeping 90% of the capacity ( Fig. 7 ), which evidence the high power performance of the electrodes, originating from the combination of the high conductivity of the graphene substrates and the Fe 3 -x O 4 raspberry nanostructure constituted of iron oxide nanoparticles with smaller diameter (25 nm). The strong interaction between the iron oxide nanostructures and the FLG surface also prevents leaching and excessive sintering (see below) of iron oxide during the charge/discharge experiments. Such electrodes can be interesting in designing high power systems, while the energy density can be fine-tuned by controlling the Fe 3 O 4 content in the composite.

Finally, after 50 charge/discharge cycles, the morphology of the raspberry nanostructures remains very similar according to the SEM analysis ( Fig. 8 ). Such a high stability could be attributed to the strong interaction between the iron oxide aggregated nanostructures and the graphene surface which prevents excessive sintering during the LIB experiments. However, some local sintering can be observed in the SEM micrograph ( Fig. 8 b). It is expected that such sintering was somehow significantly reduced thanks to the strong interaction between the iron oxide aggregates and the graphene surface which prevent excessive motion of the iron oxide aggregates during the charge/discharge experiments.

Conclusions

Fe 3 -x O 4 raspberry nanostructures/graphene nanocomposites have been synthesized by a one-step polyol-solvothermal method with Fe/C molar ratios varying from 1 to 10. Iron oxide nanostructures are distributed homogeneously on both side of the graphene sheets and acting as spacer to prevent the re-stacking of the graphene sheets through van der Walls attractions. The iron oxide nanostructures are strongly anchored on the graphene surface, through defect, vacancies and border/edge sites, and are present both in a round-shaped and hemispheres forms. The nanocomposite with the highest density on iron oxide nanostructures has been tested as anodes in Li-ion batteries and displays a reversible capacity, as high as 660 mAh/g, which makes this type of nanocomposite materials very promising for Li-ion battery applications. The relatively high and extremely stable charge/discharge of the Fe 3 O 4 -x /FLG could be attributed to several facts: the strong anchorage of the iron oxide aggregated nanostructures on the FLG which prevents the sintering during the LIB experiments, a porosity providing an easy path for lithium ion insertion and the high electrical conductivity of the graphene layer. The interconnected graphene structure in the composite also provides extra space to the volume change of the iron oxide nanostructures during the charge/discharge process. Work is underway to optimize the performance of such hybrid materials by introducing doping or by alloying the as-synthesized iron oxide with other oxides. It is also expected that the composite studied in the present work could be also useful for other applications in the field of heterogeneous catalysis, i.e. direct dehydrogenation or selective oxidation processes, where high mass transfer is key issue for the catalyst stability with improving selectivity.

Fig. 1 .

 1 Fig. 1. SEM images of Fe 3 -x O 4 /graphene sheets nanocomposites with different weight ratios Fe 3 -x O 4 /graphene: NC-100 (a,b), NC-20 (c) and NC-10 (d) and of isolated nanostructures showing Fe 3 -x O 4 aggregates constituted by assembly of several nanocrystals (e).

Fig. 2 .

 2 Fig. 2. High resolution SEM micrographs of the nanostructure/FLG composite showing the anchorage of the iron oxide aggregates on both side of the graphene sheet and also the presence of strong oxide/support interaction leading to the formation of iron oxide hemispheres aggregates (indicated by arrows).

Fig. 3 .

 3 Fig. 3. TEM analysis of the Fe 3 -x O 4 nanostructures showing the presence of Fe 3 -x O 4 nanoparticles with diameter ranged between 30 mm and 70 nm within the aggregate.

Fig. 5 .

 5 Fig. 5. Cyclic voltammograms of the Fe 3 O 4 raspberry/graphene sheets in 1 M LiPF 6 in EC: DMC (1: 1 in volume ratio) electrolyte, at 0.2 mV/s.

Fig. 6

 6 Fig. 6 shows the galvanostatic charge/discharge plots obtained for the NC-100 containing 50 wt% of Fe 3 -x O 4 at 1 C rate. The first cycle starts with the Li insertion into Fe 3 O 4 (Fe 3 O 4 + x Li + + x e -→ Li x Fe 3 O 4 ) at 1.5 V, before reaching the conversion

Fig. 4 .

 4 Fig. 4. (a) TG-DTA curves of NC-100, NC-20 and NC-10 and (b) XRD pattern of NC-10 (This XRD pattern is characteristic of those of all composites).

Fig. 6 .

 6 Fig. 6. Galvanostatic charge/discharge plots for the Fe 3 -x O 4 nanostructures/graphene sheets containing 50 wt% of Fe 3 -x O 4 , at 1 C rate.

Fig. 7 .

 7 Fig. 7. Power plot for the Fe 3 O 4 raspberry/graphene sheets containing 50 wt% of Fe 3 O 4 ; details of the power plot construction is given in experimental section.

Fig. 8 .

 8 Fig. 8. SEM images of the raspberry nanostructures after 50 charge/discharge cycles showing the high stability of the iron oxide aggregates after charge/discharge cycles. Some sintering is observed as indicated by arrows.

Acknowledgments

The authors would like to thank Cedric Leuvrey (IPCMS, UMR 7504) and Walid Baaziz (ICPEES, UMR 7515) for SEM and TEM experiments.


A Loh

S Corbel

G Dubus

J Rodriguez

I Grenier

T Hovatta

T Pearson

A Readhead

R Fender

K Mooley

High-energy gamma-ray observations of the accreting black hole V404 Cygni during its June 2015 outburst

Keywords: black hole physics -stars, individual, V404 Cygni -gamma-rays, stars -radio continuum, stars -X-rays, binaries

We report on Fermi/Large Area Telescope observations of the accreting black hole low-mass X-ray binary V404 Cygni during its outburst in June-July 2015. Detailed analyses reveal a possible excess of γ-ray emission on 26 June 2015, with a very soft spectrum above 100 MeV, at a position consistent with the direction of V404 Cyg (within the 95% confidence region and a chance probability of 4×10 -4 ). This emission cannot be associated with any previously-known Fermi source. Its temporal coincidence with the brightest radio and hard X-ray flare in the lightcurve of V404 Cyg, at the end of the main active phase of its outburst, strengthens the association with V404 Cyg. If the γ-ray emission is associated with V404 Cyg, the simultaneous detection of 511 keV annihilation emission by INTEGRAL requires that the high-energy γ rays originate away from the corona, possibly in a Blandford-Znajek jet. The data give support to models involving a magnetically-arrested disk where a bright γ-ray jet can re-form after the occurrence of a major transient ejection seen in the radio.

INTRODUCTION

The microquasars consist of an accreting black hole or neutron star in a binary system with transient or persistent relativistic jets (Mirabel & Rodríguez 1999). They display a wide range of behaviour at all wavelengths (e. g Fender 2006), but they have rarely been detected at high-energy γ rays, despite the high-energy particles produced in their jets (Corbel et al. 2002). Relativistic particles in the jet could emit γ rays, either by Compton up-scattering the low-energy photons from the accretion disc/stellar field (e.g. Georganopoulos et al. 2002;Bosch-Ramon et al. 2006) or by pion decays from inelastic collisions between jet particles and stellar wind protons (Romero et al. 2003). Gamma-ray photons could also be produced at the shock regions where the jets encounter the interstellar medium (Bosch-Ramon et al. 2011) or within the jet itself (Atoyan & Aharonian 1999).

E-mail: alan.loh@cea.fr Despite their recurrent outbursts, only the microquasar Cyg X-3 (and perhaps Cyg X-1, Bodaghee et al. 2013;Malyshev et al. 2013) behaves like a clearly identified transient high-energy emitter (Fermi LAT Collaboration et al. 2009;Tavani et al. 2009). The latter's γ-ray flares are strongly correlated to the radio emission originating from the relativistic jets (Corbel et al. 2012). With a donor star of mass >10 M , they are consistent with being high-mass X-ray binaries.

The low-mass X-ray binary (LMXB) V404 Cygni (also known as GS 2023+338) underwent an exceptional outburst phase in June 2015. V404 Cyg is a nearby system (2.39 ± 0.14 kpc, Miller-Jones et al. 2009) harbouring a ∼9 M black hole and a ∼1 M companion star (Khargharia et al. 2010;[START_REF] Wagner | [END_REF]) with a 6.5-day orbital period (Casares et al. 1992). After a 26 year long quiescent period (e.g. Rana et al. 2016), renewed activity was detected with the Swift/BAT [START_REF] Barthelmy | GRB Coordinates Network[END_REF] and Fermi/GBM [START_REF] Younes | GRB Coordinates Network[END_REF]Jenke et al. 2016, up to 300 keV) monitoring campaign from radio [START_REF] Mooley | The Astronomer's Telegram[END_REF] to hard X-rays (Rodriguez et al. 2015a) until V404 Cyg faded towards its quiescent accretion level in August 2015 [START_REF] Sivakoff | The Astronomer's Telegram[END_REF]. The source has since undergone a fainter rebrightening, in December 2015 (e.g. [START_REF] Beardmore | The Astronomer's Telegram[END_REF].

We took advantage of the intense activity and monitoring of V404 Cyg to probe its high-energy emission with the Large Area Telescope (LAT, Atwood et al. 2009) on board Fermi. The γ-ray analysis leading to the marginal detection of a flare is described in §2. Its origin is discussed in §3.

OBSERVATIONS AND DATA ANALYSIS

We have analysed the Pass 8 Fermi/LAT data covering the period 4 August 2008 to 17 July 2015. We used the Fermi Science Tools (version v10r1p1) with the Instrument Response Functions set P8R2_SOURCE_V6. A 15 • acceptance cone centered on the infrared position of V404 Cyg has been considered. LAT photons labelled as SOURCE (evclass=128) were selected in the energy range from 100 MeV to 100 GeV. Events were also filtered based on the quality of the PSF, choosing the 3 best partitions (PSF 1 to 3: evtype=56) and standard filters on the data quality were applied. To minimise the contamination by Earth limb photons, γ-ray events with reconstructed directions pointing above a 90 • zenith angle have been excluded.

In order to first constrain the emission of the whole region (nearby point-like sources and diffuse sky components), we performed a binned maximum-likelihood spectral analysis using the NewMinuit optimization algorithm implemented in gtlike. In the modelling of the region of interest (RoI), we have included the standard templates for the Galactic and isotropic backgrounds (gll_iem_v06.fits and iso_P8R2_SOURCE_V6_v06.txt1 ) and we used the spectral models listed in the 4-year Fermi catalogue (Acero et al. 2015, hereafter 3FGL) for all the sources within a 25 • radius. The normalisation parameters were left free to vary for the diffuse components and for the sources either within 5 • from the RoI center or labelled as variable (i.e. a variability index greater than 72.44, 3FGL). The results of the binned likelihood analysis using 7 years of LAT data, without including V404 Cyg which is not detected over this time scale, are fully consistent with those of the 3FGL catalogue. For instance, the flux normalisation for the blazar B2023+336 (3FGL J2025.2+3340, Kara et al. 2012), which is only ∼0. • 32 away from V404 Cyg, differs by only ∼3% from the catalogue value. In addition, the residual maps do not show any noticeable structures, especially around the Galactic plane.

Gamma-ray variability

To study the shortest time-scale variations, we have fixed every source model parameter at their fitted values from the binned analysis and added a point-source at the location of V404 Cyg, modelled as a power-law with free normalisation and index. Unbinned analyses over 12 or 6-h bins were performed, with each bin shifted by 6 or 1-h from the previous one respectively (see Fig. 1 and2). Whenever the derived Test Statistic (TS2 ) value was lower than 9 (corresponding to 3σ detection significance, Mattox et al. 1996), we computed 95 per cent upper limits on the high-energy flux using the method of Helene (1991) as implemented in the pyLikelihood module of the Science Tools. Otherwise, integrated γ-ray fluxes along with 1σ statistical error bars are provided. The LAT exposure (averaged on 12 h) ranges between 1 and 4 × 10 7 cm 2 s during the considered period, anti-correlated with the flux upper limits in Fig. 1, and is ∼2.5 × 10 7 cm 2 s during the γ-ray excess on MJD 57199.2.

Our variability analysis (performed between MJD 57140 and 57225) encompassing the June outburst period of V404 Cyg reveals the presence of a weak γ-ray excess at a location close to the LMXB around MJD 57199 (26 June 2015). The date of the γ-ray excess maximum statistical significance is estimated at MJD 57199.2 ± 0.1 (based on our 6-hour bins, see Fig. 2), although we caution that the measurements are not independent since the bins overlap in exposure. At the position of V404 Cyg, we measure a peak photon flux Fγ = (2.3 ± 0.8) × 10 -6 ph cm -2 s -1 , using the 6-hour bins (quoted errors are statistical and dominate the systematic uncertainties), for a corresponding TS value of 15.3 (the maximum on 12-hour bins is Fγ = (1.4 ± 0.5) × 10 -6 ph cm -2 s -1 for TS = 15.2, see Fig. 3). The spectrum is very soft and scales as Fγ ∝ E -3.5±0.8 . As a verification procedure, we have computed the 12h bin lightcurve (LC) of the closest Fermi source: 3FGL J2025.2+3340, with the normalisation of its spectral component let free to vary and excluding V404 Cyg from the model. This blazar underwent one flaring episode in July 2009 which lasted tens of days (Fermi All-sky Variability Analysis, Ackermann et al. 2013) and is labelled as variable in the 3FGL catalogue (with a variability index of 278.7, Kara et al. 2012;Ackermann et al. 2015). Its LC shows no significant detection over the 30 days encompassing the outburst period of the LMXB. The highest value (TS∼8.1) occurs on MJD 57199.25, which is consistent with the observed γ-ray excess since some of the photons are attributed to the blazar's emission if V404 Cyg is not taken into account. Furthermore, we note that no multi-wavelength activity has been reported from this source despite intense monitoring of this field at all wavelengths in June 2015, including its use as a phase calibrator for V404 Cyg radio observations.

Test Statistic maps and localisation

We constructed TS maps during the outburst of V404 Cyg to test whether the detection could be due to a nearby source. We show in Fig. 3 the TS map built from a 12-h integration around the date of the highest flux in the 0.1-2 GeV energy range and excluding V404 Cyg from the source model. The residual TS map shows a transient excess close to the location of V404 Cyg with a peak TS value of about 20 (∼4.5σ). The TS value drops to ∼6 if photons below 200 MeV are not considered, in agreement with the computed soft spectrum.

We used the tool gtfindsrc to localize the point source at the origin of the γ-ray excess emission. The best-fit location is at RA(J2000) = 305. • 31, Dec. = 33. • 63 with a TS of 17.6/19.5 on 6/12 h and a similar flux than reported in §2.1. The 68 and 95 per cent confidence radii are r68 = 0. • 43 and r95 = 0. • 69 (including corrections, 3FGL), represented as concentric circles in Fig. 3. The excess lies 0. • 63 from V404 Cyg's position, 0. • 84 away from the blazar B2023+336 and 1. • 48 away from the next closest source, the pulsar PSR J2028+3332 (3FGL J2028.3+3332, Pletsch et al. 2012). The latter is not known to vary (variability index of 51.2, 3FGL). The position of the excess γ-ray emission thus excludes the two closest known sources. However, V404 Cyg is within the 95 per cent confidence region of the excess. The localization cannot be better constrained due to the softness of the photons, implying a larger PSF, and the short integration time, limiting the number of photons.

Hard X-ray and radio observations

In Fig. 2 we plot the V404 Cyg LCs obtained from observations with the IBIS/ISGRI imager on board the INTEGRAL satellite (data reduction similar to Rodriguez et al. 2015a). 100-s binned LCs and hardness ratios are presented in the bands 20-40 and 80-150 keV along with mean Crab levels over the year 2015 (respectively 152.9 and 33.2 ct s -1 ).

The 15 GHz observations were obtained using the Owens Valley Radio Observatory (OVRO) 40-m telescope. Calibration is achieved using a temperature-stable diode noise source to remove receiver gain drifts and the flux density scale is derived from observations of 3C 286 (Baars et al. 1977). Details of the reduction and calibration procedure are found in Richards et al. (2011). V404 Cyg was observed with the Arcminute Microkelvin Imager (AMI-LA, 13-17 GHz), operating as part of the University of Oxford's 4 PI SKY transients programme (Fender et al., in prep.). J2025+3343 was used as phase calibrator and the absolute flux calibration was done using 3C 286 (Baars et al. 1977). The calibration and RFI excision were done using AMI-REDUCE (Davies et al. 2009). LCs centered at 13.9 GHz were extracted from the calibrated data via vector-averaging of the UV data.

DISCUSSION

We have found transient excess γ-ray emission at a position consistent with that of V404 Cyg, which we could not associate with a previously-known Fermi/LAT source. Formally, the TS of this excess is not sufficiently high to claim a detection, once the number of trials associated with constructing the LC is taken into account. The probability of measuring a TS (distributed as a χ 2 2 ) value ≥ 15.3 over the 10 days of the outburst, given 320, 6 h-long, independent trials is ∼2%.

The integrated PSF of the LAT for the soft excess seen toward V404 Cyg, in the 0.1-2 GeV band, has a 1. • 5 HWHM. By comparing to 12-hour-long all-sky maps averaged before and after the time interval of the X-ray outburst, we estimate the chance probability of having a transient or fluctuation as bright as the excess at ∼2%. So, the ∼4 × 10 -4 probability of having a random, point-source, γ-ray excess at the time of the X-ray outburst, toward V404 Cyg supports the detection of an associated γ-ray flare. Its temporal coincidence with the brightest daily averaged Swift/BAT flare, associated with a marked change in the multi-wavelength properties of the source, provides a compelling reason to posit a detection of transient γ-ray emission from V404 Cyg.

Multi-wavelength behaviour

V404 Cyg showed strong flaring activity from radio to hard X-rays over a period of about 10 days following the initial detection of the outburst on MJD 57188. The brightest flares occurred at the end of this period, close in time to the detection of the γ-ray excess we report. As shown by the AMI 13.9 GHz LC (Fig. 2), a giant radio flare with a peak above 3.4 Jy occurred ∼6 h before the γ-ray flare peak. Our 15 GHz OVRO data (Fig. 2), as well as VLA and VLBA (J. Miller-Jones, priv. com.) and RATAN [START_REF] Trushkin | The Astronomer's Telegram[END_REF] observations conducted around MJD 57198 and 57200 do not indicate the presence of other major radio flares. At hard X-rays, the brightest flare reaches about 57 Crab at 20-40 keV and occurs ∼14 h after the radio flare (i.e. starting on MJD 57199.5). This is preceded by another hard Xray flare around MJD 57199.2 that is coincident with the Fermi/LAT γ-ray excess. Although its 20-40 keV intensity is lower than the MJD 57199.5 flare, its 80-150 keV flux is higher (and corresponds to the maximum at ∼29 Crab over the whole outburst period, see Fig. 2). The activity on MJD 57198-57200 in radio and hard X-rays is also accompanied by the third (and last) detection of e -e + pair annihilation (Siegert et al. 2016). The annihilation flux LC follows the 100-200 keV flux over these two days, including the dip at MJD 57199.4. The X-ray spectral fits suggest annihilation occurs in two zones with, respectively, kT ∼2 keV and ∼500 keV. Siegert et al. (2016) performed a LAT study during the largest positron flare (MJD 57199.616-57200.261) and derived a 8 × 10 -7 ph cm -2 s -1 upper limit that is consistent with our upper limit of 8.7 × 10 -7 ph cm -2 s -1 on the same time interval, above 100 MeV. The activity and emission levels decrease markedly at all wavelengths after MJD 57200. The γ-ray excess thus appears related to the last spur of activity of the source, preceding the brightest enhancement of 511 keV emission, before it started to fade.

Gamma-ray emission from the jet?

The association of the γ-ray excess with major radio activity and marked transition to a softer X-ray state (Fig. 2) are reminiscent of Cyg X-3, where γ-ray emission is detected when the radio flux is above ∼0.2 Jy and when X-ray emission is soft -but not too much so (Corbel et al. 2012). The γ-ray luminosity from V404 Cyg is ∼2 × 10 35 (d/2.4 kpc) 2 erg s -1 , a factor ∼5 fainter than the typ- ical >100 MeV luminosity from Cyg X-3. This is a minor fraction of the overall luminosity output, which reached ∼2×10 38 erg s -1 (Rodriguez et al. 2015a). Gamma-ray emission may thus be much fainter in V404 Cyg than in Cyg X-3, either intrinsically or because of the boosting depending on the Lorentz factor and orientation of the emission in the relativistic jet (Grenier et al. 2005). Radio VLBI imaging of the jet should be able to narrow down such a possibility. In both cases, it is likely that we have detected only the brightest flaring episode during the outburst. V404 Cyg appeared to stay in a hard or intermediate state during this outburst (Rodriguez et al. 2015a;Jenke et al. 2016;Radhika et al. 2016;Kimura et al. 2016). The tentative high-energy γ-ray detections of the microquasar Cyg X-1 are also associated with this spectral state (and/or at the transition to the soft state, Sabatini et al. 2013). Bodaghee et al. (2013) found 21 daily measurements for which TS > 9 at the position of the source, mostly when it was in a hard or intermediate state. Malyshev et al. (2013) obtained a total TS∼15 by integrating all the hard state data and no detection in the soft state. The γ-ray emission from Cyg X-1 is not a simple extrapolation of the >100 keV power-law emission detected in X-rays, associated with nonthermal emission from the corona and/or the jet (Rodriguez et al. 2015b). Models suggest that the high-energy γ-ray emission is located elsewhere, most likely associated with non-thermal emission from the jet (Malyshev et al. 2013). The association in V404 Cyg of high-energy γ-ray emission contemporaneous with annihilating e + e -pairs further supports this picture. Radiative models of coronal plasmas show significant 511 keV line emission when the pair energy input is primarily non-thermal and when the corona is very dense i.e. a large opacity to pair production on >100 MeV photons (e.g. [START_REF] Svensson | [END_REF]). The high-energy γ-ray emission must thus originate away from the corona.

70 • 72 • 74 • 76 • Galactic longitude l ( • ) -6 • -4 • -2 • +0 • +2 • Galactic latitude b ( •
An intriguing possibility is that the ejection during the radio flare is associated with the disruption of a jet extracting energy from the black hole through the Blandford-Znajek process [START_REF] Blandford | [END_REF]. Numerical simulations indicate this process to be efficient when magnetic flux dragged in by a thick accretion flow piles up to create a 'magnetically-arrested disk' (MAD) close to the black hole (Tchekhovskoy et al. 2011;McKinney et al. 2012). O' [START_REF] O' Riordan | [END_REF] show that such a configuration leads to high-energy γ-ray emission in the hard state, due to Compton upscattering of jet or disk synchrotron photons. In contrast, the γ-ray emission is very weak when the built-up magnetic flux is insufficient to suppress standard accretion. In this scenario, a transient ejection occurs when the MAD configuration is disrupted (reconnects) due to incoming magnetic flux of opposite polarity (Dexter et al. 2014). O' [START_REF] O' Riordan | [END_REF] indicate that the re-formed jet is brighter in γ-rays than prior to the major ejection. Hence, the brief γ-ray emission from V404 Cyg following a major radio flare might be associated with the temporary re-formation of a powerful Blandford-Znajek jet.

The present observations support the presence of γ-ray emission associated with ejections in microquasars, and for the first time from an accreting black hole with a low-mass donor companion. This emission is weak and variable, with a low statistical significance. Some perseverance will be required to clarify the multi-wavelength context in which it appears in this and other microquasars, thus fulfilling its potential as a diagnostic of the accretion-ejection process.

Figure 1

 1 Figure 1. γ-ray flux and 95% upper limits >100 MeV and corresponding TS at the position of V404 Cyg in 12-h bins, shifted by 6 hours in time. The upper panels display the optical (extracted from the AAVSO database), hard X-ray Swift/BAT (Krimm et al. 2013), INTEGRAL/ISGRI count rate in the 80-150 keV band and the photon flux in the annihilation line (Siegert et al. 2016) LCs.

Figure 2 .

 2 Figure 2. Multi-wavelength LC of V404 Cyg around the time of the γ-ray peak (vertical blue shaded area). From top to bottom panel: AMI and OVRO flux density evolutions; LAT flux and 95% upper limits in 6-h bins, with 1-h shifts in exposure between each measurement; corresponding TS; INTEGRAL/ISGRI (LC and hardness ratio).

Figure 3 .

 3 Figure3. 12-h residual TS map on MJD 57199.25 (0.1-2 GeV, 0. • 1 pixel -1 ). 3FGL sources are marked as black crosses. 68% and 95% confidence regions on the best fit position are represented.

http://fermi.gsfc.nasa.gov/ssc/data/analysis/

TS = 2 ln(L 1 /L 0 ), L 1 and L 0 are the likelihood maxima with or without including the target source into the model. MNRAS 000, 1-5(2016)

MNRAS 000, 1-5 (2016)

ACKNOWLEDGEMENTS

We thank J. Miller-Jones, J. Ballet and J. Perkins for useful discussions and T. Siegert for providing the annihilation LC. AL, SC and JR acknowledge funding support from the French Research National Agency: CHAOS project ANR-12-BS05-0009 and the UnivEarthS Labex program of Sorbonne Paris Cité (ANR-10-LABX-0023 and ANR-11-IDEX-0005-02). KM acknowledges funding support from the Hintze Foundation. The Fermi-LAT Collaboration acknowledges support for LAT development, operation and data analysis from NASA and DOE (United States), CEA/Irfu and IN2P3/CNRS (France), ASI and INFN (Italy), MEXT, KEK, and JAXA (Japan), and the K.A. Wallenberg Foundation, the Swedish Research Council and the National Space Board (Sweden). Science analysis support in the operations phase from INAF (Italy) and CNES (France) is also gratefully acknowledged. The OVRO 40-m monitoring program is supported in part by NASA grants NNX08AW31G and NNX11A043G, and NSF grants AST-0808050 and AST-1109911. We acknowledge with thanks the variable star observations from the AAVSO.