Rafael Henrique Avanço
email: avancorafael@gmail.com

Danilo Antonio Zanella
email: daniloazll@gmail.com

Americo Cunha
email: americo.cunha@uerj.br

Angelo M Tusset
email: tusset@utfpr.edu.br

José Manoel Balthazar

Angelo Marcelo

A tutorial on the simplification of electromechanical dynamic models

Keywords:

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

Introduction

This chapter focuses on a pedagogical discussion on a relatively classic theme in dynamical systems, the modeling of nonlinear dynamics of electromechanical systems involving DC motors [START_REF] Cveticanin | Dynamics of Mechanical Systems with Non-Ideal Excitation[END_REF][START_REF] Chapman | Electric Machinery Fundamentals[END_REF][START_REF] Toliyat | Handbook of Electric Motors[END_REF][START_REF] Nayfeh | Nonlinear Oscillations[END_REF][START_REF] Kononenko | Vibrating Systems with a Limited Power Supply[END_REF]. In addition to contributing to the formation of new researchers on the subject, the text also aims to clarify some points that still confuse the literature. In this sense, the text presents a discussion of the most important aspects of modeling a system where a cart is coupled to a DC motor via a scotch yoke mechanism.

A DC motor is an electric machine that converts direct current electrical energy into mechanical energy. These motors have a permanent magnet stator with the poles N and S, where the electromagnetic forces arise from the current subject to the magnetic field of the stator [START_REF] Chapman | Electric Machinery Fundamentals[END_REF]. The main goal of this analysis is to understand the influence of the inductance in the dynamics of the DC motors. The inductance may be defined as a tendency of an electrical conductor to oppose a change in the electric current flowing through it. In DC motors, the current flows in coils, what causes a higher effect in the magnetic field. Therefore, the consequence is that in some cases the inductance interferes in the dynamics, but in others, it could be neglected. A DC motor is governed by a set of differential equations. An electric equation considering current and voltage. The other is a mechanic differential equation based on the equilibrium of torque. In literature, a useful approach does not consider the inductance of the motor after the transient condition [START_REF] Kononenko | Vibrating Systems with a Limited Power Supply[END_REF] and [START_REF] Avanço | [END_REF]. However, recent analysis claimed that this approach is not reasonable in all cases. An analysis with a motor with a mass and scotch yoke was performed in [7], neglecting the inductance in this case caused a discrepancy when compared with a complete model which considers the inductance. In the present text, some simulations are worked out where is possible to verify that under some conditions there is a divergence in results when the inductance is considered or not. On the other hand, in some situations, the inductance does not interfere significantly in the dynamics, and the act of disregarding it does not have great losses, with the advantage of simplifying the mathematical model.

Electromechanical system

The mechanism comprehends a cart moved to left and right through a scotch yoke mechanism. This mechanism is powered by a DC motor and it is illustrated in Fig( 1). This type of motor has its electric equation written in as

+ + Θ = V, (1)
while the Newton Laws of rotation applied over the rotor in the motor results in the mechanical equation

Θ + Θ - = T . (2)
DC motor cart electric circuit -+ Fig. 1 Illustration of the electromechanical system, which consists of a cart coupled to a DC motor by a scotch yoke mechanism.

In the last two equations we have = ( ) and Θ = Θ( ) respectively denote the electrical current and angular displacement of rotor in time ; the upper prime is an abbreviations for physical time derivative, i.e., = / ; represents an electrical inductance of the motor armature; stands for the internal electrical resistance of the motor; the rotational inertia of the rotor; describes a damping coefficient related to a viscous friction; while is an electromechanical coupling coefficient, it is equal to the torque constant and speed constant. The voltage source V = V ( ) and the external torque T = T ( ) acting over the motor correspond to (possibly) time-dependent external excitations. The torque may also be a function of the electromechanical system coordinates and their derivatives, i.e., T = T (Θ, Θ , Θ , ).

In the present problem the external torque T is a consequence of the cart reaction and is written as

T = sin Θ. (3)
The position of the cart is represented in Eq.( 4), where the cart depends on the angular position of the rotor = cos Θ.

The force of the motor acting over the cart is

= , (5)
and the resultant torque over the motor is given by

T = - 2 sin Θ sin Θ Θ + cos Θ Θ 2 . (6)
The initial conditions for the dynamic system are represented by

(0) = 0 , Θ (0) = Θ 0 , and
Θ(0) = Θ 0 , (7)
The dynamic system described by Eqs.( 1) and ( 2) is considered the full-order dynamic model. In the next section we will introduce and comment the reduced model.

Reduced-order dynamic system

The electrical characteristic time of the problem is defined by

= , (8)
which in a Resistor-Inductor circuit means 63.2 % of the time necessary to reach a steady-state current. Additionally, the mechanical time constant

Θ = 2 , (9)
represents 63.2 % of the time used to reach the maximum speed without external loads on the DC motor.

In literature, it is common authors [START_REF] Avanço | [END_REF][START_REF] Kononenko | Vibrating Systems with a Limited Power Supply[END_REF]8,9,10,11,12,13,14] affirm the inductance could be neglected when the electrical characteristic time is much smaller than the Θ mechanical characteristic time. Although this approach is very useful, [7,15] demonstrated an example where the models highly diverge in results. The reduced-order dynamic model considers the inductance multiplied by the derivative of the current is irrelevant in steady-state conditions. Therefore, a set of equations may be resumed in a single equation.

When inductance is neglected the Eq.( 1) turns into

= V -, Θ (10)
which, after isolating the term and substituting in the mechanical equation Eq.( 2) we obtain the reduced-order equation including both electrical and mechanical aspects

Θ + Θ - V V + 2 Θ = T . (11)
The initial conditions now do not consider the current. The electrical part depends on the voltage set. Therefore the initial conditions are simply

Θ (0) = Θ 0 , and Θ(0) = Θ 0 . ( 12
)

Dimensionless formulation

In this sections the dimensionless parameters are introduced. A method commonly applied is the Buckingham Π theorem. The theorem states one can combine parameters from a physical problem and find dimensionless parameters. Some of the most known are the Reynolds number and Mach number in fluid dynamics. In the present problem the dimensionless parameters considered are

= / 2 , = Θ , = Θ 2 / , = 3 / 2 , ℓ = 2 / 2 , = V 3 / , = 2 / , = / . ( 13
)
Here the lower case letters represent the dimensionless parameters and the upper case letters are physical parameters previously mentioned. The electric equation of the DC motor represented in Eq.( 1) turns into the dimensionless electric equation

ℓ + + = , (14)
while the mechanical equation in Eq.( 2) become the dimensionless equation

+ -= , (15)
which the right-hand-side is given by the dimensionless external torque

= -2 sin sin + cos 2 . ( 16
)
The dimensionless initial conditions are (0) = 0 , (0) = 0 , and (0) = 0 .

In the reduced model we consider the dimensionless electric equations as

+ = , (18)
so that when the dimensionless current is replaced in Eq.( 15), results in the reduced dimensionless mechanical equation

+ ( + 1) -= . (19)
In consequence, the initial conditions for the reduced model does not contain the electric current (0) = 0 , and (0) = 0 .

(20)

Results and discussion

In figures from Figure 2 to Figure 9 we have in each one the graphics of electric current versus angular velocity , the time history of the motor angular speed and the time history of the motor angular position . The intention is to vary some parameters and find some conclusion about the influence of the different parameters.

There are many parameters in the present problem and all of them may have its own relevance. However, for practical purposes we considered that three of them are more important. A dimensionless parameter for inductance represented through the parameter ℓ which is varied from Figure 2 to Figure 4, while the others parameters are maintained constant. In Figure 2, the value of ℓ is 0.02, a relatively small inductance where the results demonstrated low divergence when the full and reduced model are compared. An intermediate condition of divergence may be found in Figure 3 when the value of ℓ is 0.2. Finally, in Figure 4 which the highest value of inductance with ℓ equal to 2, the diverge appears clearly. This comparisons among these three figures evidence the relevance of the inductance on the present eletromechanical system. Larger values for the inductance have more impact in the divergence between the two models. Another parameter that is took into account is the . According the Eq. 13, the term depends on the mass displaced, the moment of inertia of the rotor and the crank radius. From Figures 5 to 7 the parameter is varied while the inductance is fixed with ℓ equal to 0.05.The results show good accordance between reduced and full model in Figure 5. Differences begin to rise in Figure 6, specially in the graphics for the angular velocity time histories. Lastly, in Figure 7 the difference are obvious in the three graphics.

The third parameter analyzed is the . Higher values for the voltage will exhibit divergence for the two models. In the Figure 8 where equal to 0.5 the two models have good accordance in the results of motion, while in Figure 9 with equal to 5 the reduced and the full models demonstrate a relevant divergence.

Conclusion

The conclusion begins pointing the importance to express the system in dimensionless terms. The common reason for this advice is the purpose to obtain a more generic result, suitable for diverse range of conditions. However, in this eletromechanical system when you turn the differential equations into dimensionless differential equations you avoid very small coefficients that oblige the usage of tiny step for integration. In other words, very small values in the coefficients cause difficulties for the computer calculus. The effect of high inductance is easier to understand. It follows the derivative of the current, the consequence is that higher the inductance, higher is the effect to the dynamics of the eletromechanical system. Not so obvious is the influence of the parameter . This parameter is not composed by eletric parts. The parameter is essentially mechanical and it is responsible for the external loads acting on the motor. A higher value of means high external forces alternating during time. It is similar to a motor in the transient regime, while it is accelerating. The voltage Fig. 7 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: = 100, ℓ = 0.05, = 1, = 1. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 ) Fig. 8 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: = 0.5, = 10, ℓ = 0.05, = 1. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 ) represented by the parameter also provokes divergences between the two models. The explanation is that high voltage causes a higher current and also contributes for a greater forces involved in the mechanism. A mathematical note is that in Eq.1 and Eq.14 when the speed of motor is reduced near to stall, the eletric part of the equation will have higher influence. It means a higher influence for inductance and electric resistance. Therefore, the main advice for electromechanical systems with DC motor is to test different models including and disregarding the inductance. Operating in high speeds and with constant load are the best conditions to neglect the influence Fig. 9 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: = 5, = 10, ℓ = 0.05, = 1. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 ) of the inductance in DC motors. For more details on the discussed in this chapter the reader is invited to see reference [16].

Fig. 2

 2 Fig. 2 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: ℓ = 0.02, = 1, = 1, = 10. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 ).

Fig. 3 Fig. 4

 34 Fig. 3 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: ℓ = 0.2, = 1, = 1, = 10. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 )

Fig. 5 Fig. 6

 56 Fig. 5 Phase-space of electric current versus angular velocity , angular velocity versus t and angular displacement versus . Dimensionless parameters: = 1, ℓ = 0.05, = 1, = 1. Initial conditions: ( 0 , 0 , 0 ) = (0, 0, 3 )

Acknowledgements This research received financial support from the Brazilian agencies Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance Code 001, the Brazilian National Council for Scientific and Technological Development (CNPq), grants 306525/2015-1 and 307371/2017-4, and the Carlos Chagas Filho Research Foundation of Rio de Janeiro State (FAPERJ) under the following grants: 211.304/2015, 210.021/2018, 210.167/2019, 211.037/2019 and 201.294/2021.

Code availability

The simulations of this chapter used a Matlab code dubbed ElectroM -ElectroMechanical Dynamic Code. To facilitate the reproduction of the results, this code is available for free on GitHub [START_REF] Cunha | ElectroM -ElectroMechanical Dynamic Code[END_REF]. Other animations of electromechanical dynamics are available on a YouTube playlist [START_REF] Cunha | Electromechanical dynamics[END_REF].


Vincent Bailly-Comte

Eglantine Husson

Elisabeth Legoff

Coline Hubert Camus

Coline Ariagno

Yannick Manche

Claudine Lamotte

A karstogenetic model to understand the karstic functioning of the Causse Méjean, France

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

A karstogenetic model to understand the karstic functioning of the Causse Méjean, France

Vincent BAILLY-COMTE (1,2), Eglantine HUSSON (3), Elisabeth LEGOFF (4), Hubert CAMUS (5), Coline Ariagno (6), Yannick MANCHE (7), Claudine LAMOTTE (4)

(1) BRGM, Univ Montpellier, Montpellier, France (2) G-eau, UMR 183, INRAE, CIRAD, IRD, AgroParisTech, Supagro, BRGM, Montpellier, France (3) BRGM, Orléans, France (4) BRGM, DAT Occitanie, Montpellier, France (5) PROTEE research group, CENOTE, Nîmes, France (6) Univ.Grenoble Alpes, INRAE,UR ETNA, Grenoble, France (7) Etablissement Public Parc National des Cévennes, Florac, France

The Cevennes national Park (PnC) and the French Geological survey (BRGM) have worked together to study the karst groundwater resources of the Causse Méjean, France. This karstic plateau is made up of Jurassic carbonate sediments (Lias, Dogger, Malm). ). Except the liasic marls (Toarcian and the Domerian), it is made of limestones and dolomites that gives a typical karst landscape all over the Causse and its adjacent valleys.

The Causse Méjean has undergone a long period of weathering under cover, producing deep corridors that are mostly still filled with alterites (dolomitic sands). In the western part of the Causse , discharge monitoring shows that this ghost rocks karstification controls the highly inertial hydrodynamic behavior of the phreatic zone. However, the current karstic functioning exports these alterites, which allows the rapid development of a limited number but well-developed karstic networks. This explains the predominance of convective transport revealed by tracer tests within these pseudo-endokarsts. To the East, the karstification was enhanced thanks to allochthonous recharge from surface stream draining the Cevennes mountains. Associated with the dip of the layers towards the West, this configuration explains the paleo-direction of the karst drainage revealed by tracer tests that reach the Tarn River. This major direction of flows was then modified due to the deepening of the Tarn, the Jonte and finally the Tarnon rivers. The deepening of the Tarn River allows the emergence of karst springs that reorganize the karst drainage to the North (i.e. Castelbouc Sp). The deepening of the Jonte River explains the relatively limited karstic drainage of the Causse Méjean towards the Douzes sp., which is mostly recharged by swallow holes in the Jonte riverbed. Finally, the deepening of the Tarnon river through all the Jurassic sedimentary sequence explains the emergence of the Pêcher Sp. in contact with the substratum. Results of 22 tracer tests conducted during the project validate this karstogenetic evolution. In addition, the deepening of the Tarnon river has also hydraulically disconnected fluviokarst streams and polje systems from their Cevennes watershed. Materials of Cevennes origin still remain in karst depressions and filled the vadose and phreatic zone of the karst systems. Geochemical water-rock interactions with these materials explain radiogenic anomalies of Sr isotopes. This interpretation has been used to better understand the origin of the water flowing to the Pêcher spring, and to assess the relative contribution of the Jonte River to the discharge of the Douze Sp.

This study shows how knowledge of the geological and geomorphological evolution of the Causse Mejean can be used to build a karstogenetic model to be challenged by other hydrogeological tools and methods. This end up with a consistent representation of the structure and the hydrological functioning of the karst systems at the scale of the Causse Méjean.


Deliang Yi

Yuanyuan Min

Beatrice Muzzi

Audrey Marty

Idaline Romana

Pier- Francesco Fazzini

Thomas Blon

Guillaume Viau

Philippe Serp

Katerina Soulantica

Epsilon Cobalt Nanoparticles as Highly Performant Catalysts in Cinnamaldehyde Selective Hydrogenation

Keywords: hcp-cobalt, epsilon-cobalt, nanoparticles, selective hydrogenation, ligands

Epsilon cobalt nanoparticles are under-explored in catalysis due to the fact that they are accessible only through wet-chemical approaches which employ ligands as stabilizing agents.

Ligands may play a significant role in determining the structure and the catalytic performances of nanoparticles, which complicates their comparison in catalysis. Here we present the catalytic performances in cinnamaldehyde hydrogenation, of freestanding and few-layer graphenesupported ε-Co nanoparticles and hcp-Co nanorods which are stabilized by the same ligands.

We show that while hcp-Co nanorods exposing a majority of {11-20} type facets are the most active, the supported spherical ε-Co nanoparticles combine high activity and excellent selectivity for the selective hydrogenation of cinnamaldehyde to cinnamyl alcohol. The concentration dependent ligand conformation on the surface of the nanostructures influences their catalytic performances with higher concentrations favoring both activity and selectivity to cinnamyl alcohol. These results should incite the interest in the implementation of ε-Co nanoparticles in other catalytic reactions where the cobalt crystal structure may play an important role.

Introduction

Cobalt nanoparticles (CoNP) present physical and chemical properties exploitable in many applications. [START_REF] Soulantica | Magnetism of Single-Crystalline Co Nanorods[END_REF][START_REF] Anagnostopoulou | Dense Arrays of Cobalt Nanorods as Rare-Earth Free Permanent Magnets[END_REF][START_REF] Braik | Introducing Cobalt as a Potential Plasmonic Candidate Combining Optical and Magnetic Functionalities within the Same Nanostructure[END_REF][START_REF] Khodakov | Advances in the Development of Novel Cobalt Fischer-Tropsch Catalysts for Synthesis of Long-Chain Hydrocarbons and Clean Fuels[END_REF] These properties critically depend on NP structural features such as size and shape. The type of facets exposed by the nanocrystals depends on their morphology, which is highly dependent on the crystal structure. CoNP can adopt three crystallographic structures: hexagonal close packed (hcp), face centered cubic (fcc) and epsilon (ε). [START_REF] De La Peña O'shea | Electronic and Magnetic Structure of Bulk Cobalt: The α, β, and ε-Phases from Density Functional Theory Calculations[END_REF] The ε-phase has been unambiguously identified and fully characterized only recently for CoNP prepared by liquid phase synthesis. [START_REF] Dinega | A Solution-Phase Chemical Approach to a New Crystal Structure of Cobalt[END_REF][START_REF] Sun | Synthesis of Monodisperse Cobalt Nanocrystals and Their Assembly into Magnetic Superlattices[END_REF] Crystal structure dependent catalytic performances have been demonstrated in several cases where allotropes were available for comparison. [START_REF] Liu | Theoretical Study of Crystal Phase Effect in Heterogeneous Catalysis[END_REF][START_REF] Fan | Template Synthesis of Noble Metal Nanocrystals with Unusual Crystal Structures and Their Catalytic Applications[END_REF] For instance, hcp and fcc Ru nanostructures show different performances in catalytic reactions such as the hydrogenation of arenes and substituted arenes. [START_REF] Yao | Modulating Fcc and Hcp Ruthenium on the Surface of Palladium-Copper Alloy through Tunable Lattice Mismatch[END_REF][START_REF] Ghosh | Effect of the Crystallographic Phase of Ruthenium Nanosponges on Arene and Substituted-Arene Hydrogenation Activity[END_REF] In another example of rarer nanoalloy allotropes, PdCu nanoalloys of fcc and body centered cubic (bcc) structures have shown different selectivities in the hydrodeoxygenation of 5-hydroxymethylfurfural. [START_REF] Li | Crystal-Phase Engineering of PdCu Nanoalloys Facilitates Selective Hydrodeoxygenation at Room Temperature[END_REF] For the case of Co it has been shown that the Co crystal phase (hcp or fcc) impacts the catalytic performances in Fischer-Tropsch Synthesis (FTS), [START_REF] Liu | Crystallographic Dependence of CO Activation on Cobalt Catalysts: HCP versus FCC[END_REF][START_REF] Liu | Particle Size and Crystal Phase Effects in Fischer-Tropsch Catalysts[END_REF] On the other hand, the ε-Co phase is practically absent from dedicated studies. [START_REF] Van Deelen | Assembly and Activation of Supported Cobalt Nanocrystal Catalysts for the Fischer-Tropsch Synthesis[END_REF] This is in part due to the fact that ε-Co is metastable, [START_REF] De La Peña O'shea | Electronic and Magnetic Structure of Bulk Cobalt: The α, β, and ε-Phases from Density Functional Theory Calculations[END_REF] and can be converted to the other two phases upon thermal treatments prior to catalyst use, or under the catalytic reaction conditions. Furthermore, ε-Co can only be obtained by colloidal syntheses, which are rarely employed in heterogeneous catalyst preparation methods. While conventional elaboration of supported catalysts allows only a limited degree of control over size, shape and crystal structure of the active phase, colloidal methods are well adapted for the synthesis of nanocrystals of well-controlled features that can be advantageously exploited in several catalytic reactions. [START_REF] Somorjai | Selective Nanocatalysis of Organic Transformation by Metals: Concepts, Model Systems, and Instruments[END_REF][START_REF] Dai | Metallic Nanocatalysis: An Accelerating Seamless Integration with Nanotechnology[END_REF] For structure-sensitive catalytic reactions, and provided that the reaction conditions do not induce significant structural modifications of the catalytically active phase, colloidal NPs can contribute to a better rationalization of catalytic processes, and to the development of efficient catalytic systems. [START_REF] Witte | NanoSelect TM Technology: Innovative Supported Pd-and Pt-Based Catalysts for Selective Hydrogenation Reactions[END_REF] Nevertheless, colloidal NPs invariably comprise capping agents (ligands), which not only stabilize them, but they also play a determinant role in controlling NP nucleation and growth steps, thus dictating their structure (size, shape, crystal structure). NPs of the same material but adopting different structures (phase, shape) are generally stabilized by different ligands, and ligand elimination is in general accompanied by modification of the NPs features. Ligand influence on the performances of NP-based catalysts is multifaceted and controversial. [START_REF] Liu | Insights into the Interfacial Effects in Heterogeneous Metal Nanocatalysts toward Selective Hydrogenation[END_REF][START_REF] Albani | Ligand Ordering Determines the Catalytic Response of Hybrid Palladium Nanoparticles in Hydrogenation[END_REF][START_REF] Chen | Interfacial Electronic Effects Control the Reaction Selectivity of Platinum Catalysts[END_REF][START_REF] Wu | Surface Molecular Imprinting over Supported Metal Catalysts for Size-Dependent Selective Hydrogenation Reactions[END_REF][START_REF] Zhang | Boosting CO2 Conversion with Terminal Alkynes by Molecular Architecture of Graphene Oxide-Supported Ag Nanoparticles[END_REF] Thus, the study of the influence of the structural characteristics of colloidal NPs on their catalytic properties is always hampered by the presence of ligands.

The chemoselective reduction of ketones/aldehydes is a widely used, fundamental reaction in organic chemistry. [START_REF] Liu | Insights into the Interfacial Effects in Heterogeneous Metal Nanocatalysts toward Selective Hydrogenation[END_REF] In particular, the selective hydrogenation of -unsaturated aldehydes, among which cinnamaldehyde (CAL), is an industrially relevant reaction for producing high added value chemicals through hydrogenation of either the C=O or the C=C bond. CAL can be hydrogenated via two parallel reactions to (i) hydrocinnamaldehyde (HCAL) through C=C hydrogenation, and (ii) cinnamyl alcohol (COL) through C=O hydrogenation.

Further hydrogenation yields the fully hydrogenated 3-phenyl-1-propanol (HCOL) (insert in Table 1). The easier hydrogenation of the C=C bond by the most widespread hydrogenation catalysts (Pt, Pd, Ru, Ni) has incited the development of COL-selective catalysts, through introduction of elements that can appropriately modify the properties of the basic metal. [START_REF] Lan | Highly Selective Catalysts for the Hydrogenation of Unsaturated Aldehydes: A Review[END_REF][START_REF] Luneau | Guidelines to Achieving High Selectivity for the Hydrogenation of α,β-Unsaturated Aldehydes with Bimetallic and Dilute Alloy Catalysts: A Review[END_REF] However, the high price and the scarcity of the most active hydrogenation metals (Pd, Pt) urges for more sustainable alternatives. Among the cost-effective metals, cobalt has been used as a COL selectivity promoter of Pt based-catalysts. [START_REF] Tsang | Engineering Preformed Cobalt-Doped Platinum Nanocatalysts For Ultraselective Hydrogenation[END_REF][START_REF] Zheng | An Effective Co-Promoted Platinum of Co-Pt/SBA-15 Catalyst for Selective Hydrogenation of Cinnamaldehyde to Cinnamyl Alcohol[END_REF][START_REF] Su | Probing the Performance of Structurally Controlled Platinum-Cobalt Bimetallic Catalysts for Selective Hydrogenation of Cinnamaldehyde[END_REF][START_REF] Winterbottom | Pt and Pt-Alloy Catalysts and Their Properties for the Liquid-Phase Hydrogenation of Cinnamaldehyde[END_REF] Nevertheless, when employed alone, while more selective, it is not a viable catalyst because of its low activity. Thus, examples of cobaltbased catalysts for the selective hydrogenation of  -unsaturated alcohols are rather scarce and among them, only very few concern pure Co. [START_REF] Nitta | Effects of Preparation Variables of Supported-Cobalt Catalysts on the Selective Hydrogenation of -Unsaturated Aldehydes[END_REF][START_REF] Antony | Selective Hydrogenation of Cinnamaldehyde over Cobalt Supported on Alumina, Silica and Titania[END_REF][START_REF] Wu | Synthesis of a Stable and Porous Co-B Nanoparticle Catalyst for Selective Hydrogenation of Cinnamaldehyde to Cinnamic Alcohol[END_REF][START_REF] Bailie | IR Study of Acrolein Hydrogenation over Co/SiO2 catalysts[END_REF][START_REF] Li | Selective Hydrogenation of Cinnamaldehyde to Cinnamyl Alcohol over an Ultrafine Co-B Amorphous Alloy Catalyst[END_REF][START_REF] Li | Highly Active Co-B Amorphous Alloy Catalyst with Uniform Nanoparticles Prepared in Oil-in-Water Microemulsion[END_REF][START_REF] Rodrigues | Co/SiO2 Catalysts for Selective Hydrogenation of Crotonaldehyde II: Influence of the Co Surface Structure on Selectivity[END_REF][START_REF] Ando | Selective Hydrogenation of Aldehyde Groups in Various -Unsaturated Aldehydes over Alumina-Supported Cobalt (0) Catalyst[END_REF][START_REF] Zhang | Efficient Selective Hydrogenation of Cinnamaldehyde over Zeolite Supported Cobalt Catalysts in Water[END_REF][START_REF] Zhang | Cobalt Silicides Nanoparticles Embedded in N-Doped Carbon as Highly Efficient Catalyst in Selective Hydrogenation of Cinnamaldehyde[END_REF][START_REF] Bustamante | Cobalt SiO2 Core-Shell Catalysts for Chemoselective Hydrogenation of Cinnamaldehyde[END_REF][START_REF] Lv | Fe-Co Alloyed Nanoparticles Catalyzing Efficient Hydrogenation of Cinnamaldehyde to Cinnamyl Alcohol in Water[END_REF] The development of a stable, active and COL-selective pure cobalt catalyst would thus, be a major breakthrough in the field. Size-, shape-and crystal structure-controlled cobalt nanostructures have been synthesized by some of us by the reduction by H2 of [Co{N(SiMe3)2}2(thf)] in the presence of lauric acid (LA) and hexadecylamine (HDA). [START_REF] Liakakos | The Big Impact of a Small Detail: Cobalt Nanocrystal Polymorphism as a Result of Precursor Addition Rate during Stock Solution Preparation[END_REF][START_REF] Cormary | Concerted Growth and Ordering of Cobalt Nanorod Arrays as Revealed by Tandem in Situ SAXS-XAS Studies[END_REF] The as-prepared Co nano-objects are purely metallic, thus, no reductive post-treatments prone to modify their structural characteristics are needed prior to their implementation, as recently shown in the case of FTS [START_REF] Harmel | A Seed-Mediated Approach for the Preparation of Modified Heterogeneous Catalysts[END_REF][START_REF] Harmel | Hcp -Co Nanowires Grown on Metallic Foams as Catalysts for Fischer-Tropsch Synthesis[END_REF] and in the acceptorless dehydrogenation of 2-octanol. [START_REF] Kaźmierczak | Influence of Capping Ligands on the Catalytic Performances of Cobalt Nanoparticles Prepared with the Organometallic Route[END_REF] Here, we present the performances in the chemoselective hydrogenation of CAL of two types of nano-objects, formed simultaneously in the same synthesis: hcp Co nanorods (hcp-CoNR) exposing mainly {112 ̅ 0} type facets and isotropic ε-CoNP. We show that while hcp-CoNR are more active, ε-CoNP supported on functionalized few-layer graphene are also active and by far the most selective cobalt catalysts for COL production, reported so far.

Experimental Section

Materials

Due to the air-sensitivity of the cobalt precursor and the cobalt nanocrystals, all manipulations have been performed under inert conditions, either by using standard Schlenk techniques or in a glove box. Hexadecylamine (HDA, 98%, Aldrich) and lauric acid (LA, 99 %, Acros) were transferred in the glovebox and used without further purification. Toluene (99 %, Fisher) was purified by a solvent purifier (Innovative Technology Purification System) and stocked in the glovebox. 1,4-dioxane (100 %, VWR Chemicals), cinnamaldehyde (97 %, Aldrich), nonane (99 %, Sigma-Aldrich), ethanol (dried, 99.9 %, Seccosolv), methanol (100 %, VWR Chemicals) were degassed by Ar bubbling and stocked in the glove-box. The Co precursor [Co{N(SiMe3)2}2(thf)] was purchased from NanoMeps. The few-layer graphene (avanGRP 40) was purchased from Avanzare.

Synthesis of hcp-CoNR and ε-CoNP

In a Fisher-Porter bottle, HDA (819.3 mg, 3.4 mmol) dissolved in 16 mL toluene, was mixed with a solution of LA (420.1 mg, 2.1 mmol) in toluene (16 mL) and the mixture was stirred for 3 min. A green solution of [Co{N(SiMe3)2}2(thf)], (902.3 mg, 2.0 mmol) in 8 mL toluene was then added under vigorous stirring to the LA-HDA mixture, giving rise to a dark blue solution. The Fischer-Porter bottle was sealed, removed from the glove box, pressurized with 3 bar of hydrogen and kept under stirring for 48 h in an oil bath preheated to 110°C. After this period of time, the excess of hydrogen was eliminated, the Fisher-Porter bottle was introduced in a glove box and the dark suspension was let to decant overnight. The black precipitate containing the hcp-CoNR was washed several times with 10 mL toluene, until the supernatant became colorless and then with 10 mL pentane, and dried. The resulting powder was stored in the glove-box (ICP-OES: hcp-CoNR: Co = 73.4 w%, elemental analysis: N = 0.18 w%). The brown supernatant containing the ε-CoNP and ligand excess was collected and dried under vacuum. The as-obtained solid was then kept in the glove-box. (ICP-OES ε-CoNP: Co = 0.64 w%, elemental analysis: N = 4.91 w%).

Purification of ε-CoNP by repeated centrifugation steps of 15 min at 50000 rpm yielded ε-Co*NP samples (ICP-OES ε-Co*NP: Co = 57.2 w%, elemental analysis: N = 0.48 w%).

Catalyst preparation

The freestanding nanostructures were supported on oxidized commercially available few layer graphene.

Few layer graphene support functionalization 2 g of few-layer graphene (G) in 120 mL of HNO3 (65%, VWR Chemicals) were heated at 100 °C for 3h. The mixture was then filtered and washed with deionized water until pH = 7.

The final product (Gox) was collected and dried at 80 °C overnight. It was then stored in the glove box.

Co immobilization on functionalized graphene

In a typical elaboration of a supported hcp-CoNR/Gox catalyst, 14 mg of powder containing hcp-CoNR dispersed in 15 mL toluene were mixed with 200 mg of Gox and sonicated for 10 min. After decantation the colorless supernatant was removed, the black solid washed three times with 20 mL toluene and dried, giving a powder which was stored in the glove-box.

(ICP-OES: Co = 3.67 w%, elemental analysis: N < 0.01 w%).

In a typical elaboration of a ε-CoNP/Gox catalyst, 200 mg of Gox were added in 60 mL of toluene in which were suspended 1.263 g of the powder containing the ε-CoNP powder. The suspension was sonicated for 10 min and let to decant overnight under inert atmosphere. The light grey supernatant was removed, and the solid was washed three times with 20 mL toluene, dried, and stored in the glove-box. (ICP-OES: Co = 4.49 w%, elemental analysis: N =0.28 w%). The same procedure was used for the immobilization of ε-Co*NP on Gox to give ε-Co*NP/Gox. (ICP-OES: Co = 4.48 w%, elemental analysis: N = 0.03 w%).

Catalytic tests

No H2 treatment of the catalysts was performed prior to the catalysis. The autoclave was charged in the glovebox. All chemicals were degassed before using. For all catalytic runs the Co amount introduced in the autoclave was between 1 and 2.6 mg (the exact Co amounts used in the catalytic runs are given in Table 1). The catalyst, 442 mg of cinnamaldehyde, 167 mg of nonane and 25 mL of solvent were added in the autoclave and mixed vigorously. The autoclave was then sealed and taken out of the glovebox, purged three times with 3 bar H2 and then filled with 20 bar H2. The temperature was increased to 120 °C and the stirring speed was fixed at 1200 rpm. Samples were taken from the autoclave at regular intervals and were analyzed on a Perkin Elmer, Clarus 580 gas chromatograph equipped with an Elite-5MS capillary column (30 m × 0.32 × 0.25 μm) and with a flame ionization detector. The activity was calculated on the basis of the exact mass weighted and the Co content measured by ICP analysis of each catalyst employed. The conversion and selectivity were calculated according to the following equations:

Conv% = (ni-nf)/ni *100% Sx% = nx/nprod*100%
ni: mol of CAL introduced nf: mol of CAL remaining at the end of the reaction nx: mol of product x nprod: total number of moles of products

The activity was calculated from the following relationship:

Activity = molCAL molCo -1 h -1 molCAL: mol of CAL converted molCo: mol of Co amount introduced Recycling of ε-CoNP/Gox
The first run of recycling of ε-CoNP/Gox in ethanol followed the same procedure as described above, except that after 2h reaction, the reactor was cooled down rapidly and reintroduced into the glovebox. The reactor was let still for 2h to let the catalyst decant. The supernatant (20 mL) was removed carefully. 442 mg of cinnamaldehyde, 167 mg of nonane and 20 mL of ethanol were added. The reactor was then sealed and taken out of the glovebox for the second run of recycling. The recycling was carried out six times. To calculate the loss of activity, the cinnamaldehyde conversion of the first run was set to 100%. The conversion of each run versus the first run was calculated as the activity drop percentage.

Calculation of the nano-object geometric specific surface area

The geometric specific surface areas (SSA) of the nanoparticles were calculated using the formula 𝑆𝑆𝐴 =𝑆𝑡𝑜𝑡/(𝑑𝐶𝑜.𝑉), where Stot = the surface of hcp-CoNR or ε-CoNP, V their volume and dCo the density of Co (8.86 g cm -3 ). The values for the hcp-CoNR and ε-CoNP samples were obtained by using the mean dimensions determined by TEM and assuming simple geometrical models, considering a spherical shape for the ε-CoNP and a hexagonal prismatic shape for the hcp-CoNR.

Characterization

The size and the morphology of the cobalt nano-objects were studied by transmission electronic microscopy (TEM). All samples for TEM and high-resolution TEM (HRTEM) were prepared by evaporating a drop of a diluted suspension in toluene on a carbon-coated copper grid. Conventional TEM characterizations were performed on a JEOL JEM 1011 CX-T electron microscope operating at 100 kV with a point resolution of 4.5 Å. The particle size distribution was determined through a manual measurement of enlarged micrographs from different areas of the TEM grid (at least 200 particles). HRTEM was performed on a JEM-ARM200F Cold FEG equipped with a GATAN ULTRASCAN CCD camera and having a 1.9 Å point resolution.

The X-ray diffraction (XRD) patterns were obtained from samples encapsulated between two Kapton® foils to avoid sample oxidation. The diffractograms were recorded on a PANalytical Empyrean diffractometer using Co-Kα radiation (λ = 0.1789 nm) at 45 kV and 40 mA. The ε-CoNP powder contained an excessive amount of ligand that did not allow identification of the Co peaks. The XRD measurement for the crystal structure determination was performed on a sample purified from the large excess of residual native ligands (ε-Co*NP), using a Thermo Fisher Scientific Sorvall MTX150 micro-ultracentrifuge. Two centrifugation cycles were performed at 50 000 rpm for 15 minutes. This allowed crystal structure and crystallite size determination, even though the presence of residual ligands is still visible in the XRD diffractogram. The crystallite size was calculated using the Scherrer equation by analysis of the ε-Co (221) peak. The XRD diffractograms of the Gox supported catalysts did not allow identification of the Co-peaks due to the low Co-content (about 5 w%).

Infrared spectra were recorded on the isolated solid of ε-CoNP, on a Nicolet 6700 FT-IR spectrometer in the range 4000-500 cm -1 using a Smart Orbit ATR platform (diamond crystal). The hcp-CoNP and ε-Co*NP spectra were recorded from samples obtained by depositing on a Ge wafer a few drops of a toluene suspension of the isolated solids and letting the solvent evaporate.

ICP-OES and elemental analyses were performed by KOLBE Mikroanalytisches

Laboratorium on a Spectro Acros instrument and a "Elementar" Model "Vario Micro Cube" CHN analyzer, respectively. X-ray photoelectron spectroscopy (XPS) spectra were recorded from samples prepared by depositing on a Si wafer a few drops of a toluene suspension of the isolated solid of ε-CoNP, and the solvent was fully evaporated. The spectra were recorded using a K-alpha plus system (Thermo Fisher Scientific, East-Grinstead, U.K.) fitted with a microfocused and monochromatic Al Kα X-ray source (1486.6 eV, spot size of 400 μm). The spectrometer pass energy was set to 150 and 40 eV for the survey and the narrow highresolution regions, respectively.

The magnetic measurements were performed by a Vibrating Sample Magnetometer (VSM) for hcp-CoNR and ε-Co*NP and by a Superconducting QUantum Interference Device (SQuID) for ε-CoNP. The samples were prepared in the glove box. In order to confirm the absence of any oxidation on the hcp-CoNR sample, the M(H) hysteresis loops were recorded from -6 T to +6 T at 300 K (after a zero-field cooling (ZFC) and after a field cooling (FC) under +6 T) at 5 K. No Co/CoO exchange bias was detected at 5 K after the FC process. The same procedure was followed for ε-CoNP and ε-Co*NP, with the only difference of the applied field intensity (-5 T to +5 T).

Results and Discussion

CoNR of 97.9 ± 9.4 nm mean length and 5.9  0.6 nm mean diameter (Figure 1a) and isotropic CoNP of 6.5  1.0 nm mean diameter (Figure 1b) are produced simultaneously, by reduction of Co/LA/HDA solutions. [START_REF] Cormary | Concerted Growth and Ordering of Cobalt Nanorod Arrays as Revealed by Tandem in Situ SAXS-XAS Studies[END_REF] Post-synthesis selective precipitation allows separation of the CoNR from the CoNP. The CoNR, which have been characterized in previous publications, can be easily purified after isolation. [START_REF] Cormary | Concerted Growth and Ordering of Cobalt Nanorod Arrays as Revealed by Tandem in Situ SAXS-XAS Studies[END_REF][START_REF] Kaźmierczak | Influence of Capping Ligands on the Catalytic Performances of Cobalt Nanoparticles Prepared with the Organometallic Route[END_REF] They adopt the hcp phase and they expose {112 ̅ 0} type facets laterally and {0002} facets at their extremities. The CoNP were isolated by complete evaporation of the reaction supernatant after CoNR removal. The as obtained CoNP fraction is mainly composed of organic products (99.4 w %). In agreement with previous analyses on CoNR, [START_REF] Kaźmierczak | Influence of Capping Ligands on the Catalytic Performances of Cobalt Nanoparticles Prepared with the Organometallic Route[END_REF] this residue mainly consists in hexadecylammonium laurate and N-hexadecyl laurylamide, resulting from the condensation between LA and HDA during the nano-object synthesis. This was confirmed by IR and X-ray photoelectron spectroscopy (XPS) analyses of the powder containing the CoNP and the native ligand matrix (Fig S1a-c). A fraction of the CoNP sample was centrifuged to remove the majority of the organic residue yielding Co*NP. The IR spectra of the CoNR and the Co*NP show that the ligands are the same in both cases (Figure S1d). The synthesis and the purification procedure are outlined in Scheme 1.

Scheme 1. Outline of the synthesis and the isolation of the Co nano-objects.

Interestingly, while the CoNR crystallize in the hcp phase [START_REF] Cormary | Concerted Growth and Ordering of Cobalt Nanorod Arrays as Revealed by Tandem in Situ SAXS-XAS Studies[END_REF] (Fig. S2), the spherical CoNP (Figure 1c) adopt the ε crystal structure, as evidenced by X-ray diffraction (XRD) of the purified ε-Co*NP (Figure 1d). In agreement with TEM data, the crystallite size was calculated to be 6.5 nm using the Scherrer equation, which confirms the single-crystal structure. Their spherical shape indicates that they are enclosed by facets of different types, albeit, of completely different symmetry than the facets exposed by the hcp-CoNR. Magnetic measurements evidenced the absence of surface oxidation (Fig. S3). Indeed, the hysteresis loops measured after the field cooling (FC) procedure from 300 K down to 5 K under a magnetic field remain symmetric, which is a clear indication that no Co oxide layer is present on the surface of the nano-objects. The fact that nano-objects of two different structures could be isolated from the same synthesis, offered the opportunity to compare their catalytic performances without having to address the additional role that ligands of different nature may play.

The catalytic performances of freestanding hcp-CoNR and ε-CoNP were evaluated in the selective hydrogenation of CAL at 120 °C and 20 bar of H2. Dioxane was the first solvent used, in order to avoid the formation of acetal by-products usually produced in alcohols from the acid-catalyzed condensation reaction between CAL (or HCAL) and the solvent. [START_REF] Zhang | Efficient Selective Hydrogenation of Cinnamaldehyde over Zeolite Supported Cobalt Catalysts in Water[END_REF] In Figure 2 and Table 1 we report the catalytic performances of the catalysts tested. Despite the lower geometric specific surface area of hcp-CoNR (89.2 m 2 .g -1 ) as compared to -CoNP 104 m 2 .g -1 ), the hcp-CoNR were more active than the -CoNP, but the selectivity towards COL (at iso-conversion 40%) was higher for the -CoNP (86.8 % versus 66.7% for hcp-CoNR). ligand excess; e) data given at 30% conversion; f) NE = not estimated, N w% was below detection limit.

These results can be rationalized either by considering a different intrinsic performance of the two Co nano-objects, or by considering that the ligands, which are in high excess in the case of -CoNP (Co/N atomic ratio = 0.03) as compared to hcp-CoNR (Co/N atomic ratio = 96.8), reduce the activity of -CoNP because they block numerous active sites, and at the same time increase their selectivity to COL. While for Co catalysts there are no dedicated studies in the literature, a positive influence of long chain amine ligands on the selectivity to COL has been reported for Pt based catalysts. [START_REF] Wu | Selective Hydrogenation of α,β-Unsaturated Aldehydes Catalyzed by Amine-Capped Platinum-Cobalt Nanocrystals[END_REF][START_REF] Peres | Selective Hydrogenation of Cinnamaldehyde by Unsupported and Few Layer Graphene Supported Platinum Concave Nanocubes Exposing {110} Facets Stabilized by a Long-Chain Amine[END_REF] In order to estimate the influence of the initial ligand coverage on -CoNP, we also tested a purified fraction of the -CoNP sample (-Co*NP), which presented the same particle size (Fig. S5) but much higher metal content (Co/N atomic ratio = 28.3). The activity (Figure 3a), but also the selectivity (Figure 3b) of -Co*NP are significantly lower than the ones of the -CoNP. The activity decrease upon ligand partial elimination could be rationalized by an influence of ligand ordering on the NP surface (2D versus 3D ordering), as already reported for PdNP hydrogenation catalysts. [START_REF] Albani | Ligand Ordering Determines the Catalytic Response of Hybrid Palladium Nanoparticles in Hydrogenation[END_REF] In that case, the authors also showed that ordering on the NP surface is highly dependent not only on the ligand concentration but also on the ligand nature. Indeed, ligands containing ionic groups, are subjected to conformation changes depending on their concentration. Such an effect could also account for the significantly lower activity observed by the -Co*NP as compared to the -CoNP. As far as selectivity is concerned, the most probable explanation is that in the case of -CoNP a 3D ordering of the ligands induces a higher COL selectivity due to the favorable orientation of the C=O group of CAL and its preferential adsorption. [START_REF] Wu | Selective Hydrogenation of α,β-Unsaturated Aldehydes Catalyzed by Amine-Capped Platinum-Cobalt Nanocrystals[END_REF][START_REF] Peres | Selective Hydrogenation of Cinnamaldehyde by Unsupported and Few Layer Graphene Supported Platinum Concave Nanocubes Exposing {110} Facets Stabilized by a Long-Chain Amine[END_REF] The hcp-CoNR, which present a higher activity have the lowest ligand content and present a lower selectivity as could be expected.

However, their significantly higher activity despite their lower ligand content and their lower surface area points towards the conclusion that hcp-CoNR are inherently more active. It has to be noted that this does not mean that the hcp phase is generally a more active phase, but that the {112 ̅ 0} facets, which constitute the majority of the hcp-CoNR exposed facets are more active than the facets of the -CoNP. All freestanding hcp-CoNR, -CoNP and -Co*NP are affected under the catalytic reaction conditions. Indeed, TEM observation of the crude reaction media after catalysis revealed the presence of CoNP of about 13 nm size for -CoNP, agglomeration for -Co*NP, while the CoNR appear more agglomerated and slightly corroded (Fig. S6). As NP separation is tedious, immobilization on appropriate supports of colloidal NPs appears as the best approach to ensure optimized performance, stability and easy catalyst separation. [START_REF] Costa | Synthesis of Supported Metal Nanoparticle Catalysts Using Ligand Assisted Methods[END_REF] In parallel, immobilization should result in elimination of the surfactant excess, thanks to ligand displacement. In this context, hcp-CoNR and ε-CoNP were immobilized on fewlayer graphene (G), which had been previously functionalized through treatment with HNO3 to produce Gox. This treatment produces oxygen containing functions (mainly carboxylic and phenolic), [START_REF] Contreras | Effect of Mesoporous Carbon Support Nature and Pretreatments on Palladium Loading, Dispersion and Apparent Catalytic Activity in Hydrogenation of Myrcene[END_REF] which favor the immobilization of the nano-objects on the Gox support. A 5 w% nominal Co loading was targeted through mixing in toluene the freestanding CoNR and ε-CoNP with the Gox at room temperature. After immobilization and washing, the ICP analyses of hcp-CoNR/Gox and -CoNP/Gox showed Co loadings of 3.7 and 4.5 w%, respectively. The Co/N atomic ratios were 0.03 and 3.8 for -CoNP and -CoNP/Gox, respectively. Therefore, upon immobilization of the -CoNP, a significant part of the residual ligand is eliminated. The Co/N atomic ratio in hcp-CoNR/Gox could not be calculated since nitrogen content was lower than the detection limit (0.01%). Therefore, a higher amount of ligand for -CoNP is still present even on the supported catalysts. The nano-objects were well-dispersed on the Gox as shown in the TEM images on Figure 4. Immobilization of the hcp-CoNR on Gox has no pronounced effect on their activity and selectivity to COL (Table 1). Globally, the immobilization allows reaching slightly higher activity (Figure 5a). XRD is not conclusive concerning the conservation of the structure after catalysis, because the Gox exhibits strong reflections in the same 2 range as the Co peaks (Fig. S7). However, TEM observation of the spent hcp-CoNR/Gox catalyst shows that nanorod morphology is not impacted after 6 hours of reaction and that the hcp structure is conserved.

(Fig. S8) On the other hand, for the -CoNP/Gox catalyst the initial activity is increased (Figure 5b) and the selectivity to COL reaches 100 % at 40 % conversion (Figure 2d and Table 1). If

our assumption is correct that besides the Co structure, a 2D versus 3D ligand ordering also controls activity, and if for the 3.8 Co/N ratio the 3D ordering is still operative, it is logic that the -CoNP/Gox catalyst, which presents a higher Co/N ratio than the -CoNP catalyst, is more active.

Furthermore, the NPs on the -CoNP/Gox catalyst seem to be intact even after complete CAL conversion, their size (6.11.2 nm) remaining practically unmodified. (Fig S9 ).

Therefore, upon immobilization, ε-CoNP double their initial activity and improve their selectivity, while no significant change is noticed for hcp-CoNR. Furthermore, and as for freestanding nano-objects, the supported hcp-CoNR are more active and less selective than the supported ε-CoNP nano-objects.

We also investigated the reactivity of the -Co*NP/Gox catalyst, which present a higher Co/N ratio compared to the -CoNP/Gox catalyst (35.4 and 3.8, respectively). As for the unsupported samples, we found that the sample with less ligand is globally less active and less selective (Figure 6). This result is consistent with a partial confinement of -CoNP between the Gox layers and ligand residue adsorption on the surface of the support and could explain the very higher selectivity of the -CoNP upon immobilization.

To summarize, several parameters including the crystallographic phase of the metal, the ligand coverage and the possible confinement of the cobalt must be at the origin of the excellent results obtained with the -CoNP/Gox system. Since the ligand coverage is often advanced as a key parameter in this type of catalysis, we have attempted to correlate the Co/N ratio with the catalytic performance (Fig. S10). It can be seen from Fig. S10a and 10b that no simple correlation exists between this ratio and the activity or selectivity of cobalt. Overall, it emerges that hcp-CoNR seem more active and less selective than -CoNP, which could be related to the specific activity of the facets exposed in each case.

The results obtained with the ε-CoNP/Gox catalyst are very encouraging as tentatively compared to the data reported in the literature for pure cobalt catalysts, even if the conditions under which the reactions have taken place are not the same. (Table S1). This prompted us to investigate alternative solvents, since it has been shown that alcohols can be beneficial in terms of activity in the case of cobalt catalysts. [START_REF] Zhang | Efficient Selective Hydrogenation of Cinnamaldehyde over Zeolite Supported Cobalt Catalysts in Water[END_REF] In methanol, a large activity increase is noticed, however, acetal formation is very high (Table 1). Ethanol constitutes a better choice, leading to very high activity and COL selectivity with limited acetal production (Fig. S11 and Table 1). Figure 7a shows the evolution of activity and selectivity with conversion for ε-CoNP/Gox and the results of recyclability tests are shown in Figure 7b. TEM and HRTEM images of the catalyst after recycling are shown in (Fig. S12). While low catalyst loading has not allowed confirming the conservation of the ε-structure by XRD after the catalytic runs, HRTEM on a ε-CoNP after recycling points toward the conservation of the ε-phase (Fig. S12b). Remarkably, the ε-CoNP/Gox catalyst achieves high COL selectivity (> 85%) even at complete CAL conversion, while maintaining a catalytic activity comparable to some Ru catalysts presenting significantly lower COL selectivity. [START_REF] Leng | Selectivity Shifts in Hydrogenation of Cinnamaldehyde on Electron-Deficient Ruthenium Nanoparticles[END_REF] These latter results place the ε-CoNP/Gox catalyst largely above all the catalysts based on pure cobalt reported in the literature (Table S1 and Fig. S13).

Conclusion

We have shown that metallic Co nano-objects prepared by an organometallic route are active catalysts for the selective hydrogenation of cinnamaldehyde to cinnamylalcohol. In particular, ε-CoNP supported on oxidized few-layer graphene, outperform their counterparts reported so far in the literature. Their good stability under the reaction conditions, and the higher selectivity as compared to the hcp-CoNR point towards a positive role of the largely unexplored in catalysis ε-Co structure. At this point, it would be premature to attribute the differences in the performances of the two types of nano-objects only to their different structure and further studies combining experiment and theory will allow determining the underlying reasons of their different performances.

ASSOCIATED CONTENT

Figure 1 .

 1 Figure 1. Cobalt nano-objects. TEM of (a) hcp-CoNR and (b) ε-CoNP. (c) Higher magnification view of ε-CoNP. (d) XRD pattern of the ε-Co*NP. The peaks marked with a red mark are due to the ligand residues (Fig. S4).

Figure 2 .

 2 Figure 2. Catalytic performances in dioxane. (a) Freestanding hcp-CoNR; (b) freestanding -CoNP; (c) hcp-CoNR/Gox and (d) -CoNP/Gox.

  from ICP and elemental analyses of Co and N respectively, b) at 4 h reaction; c) activity (molCAL molCo -1 h -1 ) and selectivity at 40% conversion; d) -Co*NP are -CoNP purified from the

Figure 3 .

 3 Figure 3. Comparison of the catalytic performances of -CoNP and -Co*NP; (a) activity and (b) selectivity to COL.

Figure 4 .

 4 Figure 4. Supported cobalt nano-objects. TEM of (a), (b) hcp-CoNR/Gox and (c), (d) -CoNP/Gox.

Figure 5 .

 5 Figure 5. Comparison of the activity of freestanding and Gox supported nanoparticles: (a) hcp-CoNR and (b) -CoNP.

Figure 6 .

 6 Figure 6. Comparison of -CoNP/Gox and -Co*NP/Gox catalysts: (a) activity and (b) selectivity to COL.

  * NP /G ox (Co/N = 35.4) e-Co NP /G ox (Co/N = 3* NP /G ox (Co/N = 35.4) e-Co NP /G ox (Co/N = 3.8)

Figure 7 .

 7 Figure 7. ε-CoNP/Gox catalyst performances in ethanol. Evolution of (a) the selectivity to COL and the activity as a function of conversion and (b) the selectivity to COL and the activity during recycling.

  IR of hcp-CoNR, ε-CoNP, ε-Co*NP and XPS of ε-CoNP,, XRD and VSM of hcp-CoNR, ε-CoNP and ε-Co*NP, TEM of ε-Co*NP, TEM of spent freestanding catalysts, XRD of fresh and spent hcp-CoNR/Gox compared to Gox and hcp-CoNR, TEM and HRTEM of spent hcp-CoNR/Gox , correlation between Co/N ratio and activity and selectivity of hcp-CoNR and ε-CoNP, comparison of the catalysts presented here and catalysts in the literature, comparison of catalytic performances in dioxane and ethanol of ε-CoNP/Gox, TEM and HRTEM of ε-CoNP/Gox after recycling.

Table 1 .

 1 Hydrogenation of cinnamaldehyde catalyzed by Co catalysts (120 °C, PH2 = 20 bar).

	Catalyst

Co (10 -2 mmol) Co/N a (atomic) Solvent Conversion b (%) Activity c (h -1 ) Selectivity c (%) COL HCAL HCOL Acetal

	hcp-CoNR	3.6	96.8	Dioxane	59.7	16.6	66.7	16.2	17.1	0
	-CoNP	1.7	0.03	Dioxane	26.8	11.7	86.8 100 e	7.8	5.4	0
	-Co*NP d	4.5	28.3	Dioxane	19.1	4.3 e	83.5 e	8.9 e	7.6 e	0 e
	hcp-CoNR/Gox	3.1	NE f	Dioxane	64.0	19.3	66.7	9.7	23.6	0
	-Co NP /G ox	3.1	3.8	Dioxane	45.1	10.8	100	0	0	0
	-Co*NP/Gox	4.4	35.5	Dioxane	38.4	7.0	75.8	14.8	9.6	0
	-CoNP/Gox	3.1	3.8	Methanol	92.5	57	28.6	0	0	71.4
	-CoNP/Gox

Acknowledgements D. Yi, K. S. and P. S. thank the EUR grant NanoX n° ANR-17-EURE-0009 for financial support in the framework of the "Programme des Investissements d'Avenir" through the project. Y. M., B. M., A. M., P-F. F., T. B., G. V., and K.S. also thank the European Union's Horizon 2020 research and innovation program for financial support of the SWIMMOT project under grant agreement No 899612. The authors thank Simon Cayez, Angélique Gillet and Adeline Pham for technical support.

AUTHOR INFORMATION Corresponding Authors

Katerina Soulantica-Université de Toulouse, LPCNO CNRS, INSA, UPS UMR 5215, 31077 Toulouse, France; orcid.org/0000-0003-3033-1620; Email: ksoulant@insa-toulouse.fr Philippe Serp-LCC, CNRS-UPR 8241, ENSIACET, Université de Toulouse, France; orcid.org/0000-0003-1424-2724 Email: philippe.serp@ensiacet.fr

Author Contributions

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