domain: phys spi

text:
Akash Patil

Roberto Simola
email: roberto.simola@st.com

Jean-François Robillard
email: jean-francois.robillard@iemn.fr

Yannick

Philippe Boivin
email: philippe.boivin@st.com

Jury Sandrini
email: jury.sandrini@st.com

Emmanuel Dubois
email: emmanuel.dubois@iemn.fr

Raman Thermometry Characterization of GeSbTe based Phase Change Materials

Keywords: Phase change memories, Ge-rich GST N-doped, Raman thermometry, structure, thermal conductivity

Ge-rich GeSbTe N-doped alloys present a solution for the reliability and thermal stability requirements of Phase Change Memories for embedded non-volatile memory automotive applications. The thermal performance of these memories is defined by the optimization of crystallization temperature, kinetics and thermal properties of materials and interfaces. In this work, we study the structural evolution and crystallization temperature of Ge-rich GeSbTe N-doped alloy from amorphous phase to complete crystallization by Raman spectroscopy. We highlight the beginning of crystallization process by Ge crystallization, followed by crystallization of both GeTe and SbTe related structures. Further, the sensitivity of the vibrational modes present in this ternary chalcogenide alloy to temperature and power is examined to identify potential thermometers. Finally, we present the working principle of Raman thermometry to extract the thermal conductivity aided by finite-element calculations and report the thermal conductivity of Ge-rich GeSbTe N-doped alloy.

I. INTRODUCTION

Phase change materials are the basis of optical and nonvolatile memory (NVM) storage systems due to their high optical or electrical resistance contrast upon phase transition. (GeTe)n-(Sb2Te3)m ternary alloy system based phase change materials are at the heart of Phase Change Memories (PCMs). PCMs are one of the most mature NVM owing to its high temperature data retention, fast read/write access, better endurance, high scalability, and ease of integration with CMOS. This has been proven by its commercial realization for storage class memory [START_REF] Cappelletti | Phase change memory for automotive grade embedded NVM applications[END_REF], automotive microcontroller [START_REF] Arnaud | High Density Embedded PCM Cell in 28nm FDSOI Technology for Automotive Micro-Controller Applications[END_REF] and smart power applications [START_REF] Carissimi | 2-Mb Embedded Phase Change Memory With 16-ns Read Access Time and 5-Mb/s Write Throughput in 90-nm BCD Technology for Automotive Applications[END_REF].

The working principle of PCM is based on reversible switching between amorphous and crystalline phases. For reversible switching, the electric pulses (SET/RESET) locally heat the material via a heater to crystallize the material or to melt quench the crystalline phase to amorphous phase. As this switching is thermally initiated, knowledge of crystallization temperature, thermal properties of materials and interfaces are key to optimize this nanoscale non-volatile memory. Also, PCMs use for automotive applications is hindered by the stringent requirements for robust high temperature operation which challenges the materials thermal stability for data retention.

PCMs based on Ge2Sb2Te5 (GST-225) are the widely studied and is the reference material for this technology [START_REF] Fong | Phase-Change Memory-Towards a Storage-Class Memory[END_REF]. The drawback of low crystallization temperature of 150°C for GST-225 was resolved by materials engineering to cope up with the automotive standards. This was achieved by doping it with C [START_REF] Hubert | Lowering the Reset Current and Power Consumption of Phase-Change Memories with Carbon-Doped Ge2Sb2Te5[END_REF], N [START_REF] Cheng | A thermally robust phase change memory by engineering the Ge/N concentration in (Ge, N)xSbyTe z phase change material[END_REF] or increasing the Ge content [START_REF] Zuliani | Overcoming Temperature Limitations in Phase Change Memories With Optimized $\rm Ge_\rm x\rm Sb_\rm y\rm Te_\rm z[END_REF] and recently by GeSe1-xTex [START_REF] Tomelleri | Overcoming the Thermal Stability Limit of Chalcogenide Phase-Change Materials for High-Temperature Applications in GeSe1-xTex Thin Films[END_REF]. For the Ge-rich GST, the crystallization temperature scaled with increasing Ge-content [START_REF] Zuliani | Overcoming Temperature Limitations in Phase Change Memories With Optimized $\rm Ge_\rm x\rm Sb_\rm y\rm Te_\rm z[END_REF] and was significantly improved over 300°C with Ndoping. Ge-rich GST with N-doping (GGSTN) has been extensively studied for its crystallization kinetics [START_REF] Gomiero | Crystallization Speed in Ge-Rich PCM Cells as a Function of Process and Programming Conditions[END_REF], effect of N-doping [START_REF] Luong | Impact of Nitrogen on the Crystallization and Microstructure of Ge-Rich GeSbTe Alloys[END_REF] and structural evolution [START_REF] Prazakova | Temperature driven structural evolution of Ge-rich GeSbTe alloys and role of N-doping[END_REF] [START_REF] Rahier | Crystallization of Ge-Rich GeSbTe Alloys: The Riddle Is Solved[END_REF]. So, GGSTN has proved to be a potential material for commercialization. Also, along with the progress in materials engineering for automotive applications, it is also key to optimize the thermal budget of the PCM cell. It has been reported that a total of less than 2% of heat is used for switching the phase of the PCM cell [START_REF] Sadeghipour | Phase change random access memory, thermal analysis[END_REF]. The thermal management can be improved by knowledge of thermal properties of these newly developed chalcogenide materials and better understanding of thermal behavior of the cell. So, it is also crucial to study the thermal properties of GGSTN for optimizing PCMs.

In this work, we employ Raman spectroscopy to study the structural evolution, crystallization temperature and Raman thermometry to extract the thermal conductivity of the GGSTN. The key advantages of this method over other techniques like 3-ω and TDTR for thermal characterization are that it doesn't require any additional device design like heater or contact pads, has better micrometer spatial resolution and better material selectivity [START_REF] Stoib | Spatially resolved determination of thermal conductivity by Raman spectroscopy[END_REF] [START_REF] Jaramillo-Fernandez | Raman thermometry analysis: Modelling assumptions revisited[END_REF]. The key requirement is that the material to be probed should have vibrational modes which are sensitive to temperature -Raman active modes [START_REF] Sandell | Thermoreflectance techniques and Raman thermometry for thermal property characterization of nanostructures[END_REF]. It means that change in temperature of the material should affect the position of the Raman shift of a vibrational mode or the FWHM of the peak or its intensity. These characteristics can be used to build a thermometer. So, by using a focused laser on a Raman active material, the local temperature and thermal conductivity of the material can be extracted. This method has been widely used to study temperature dependence of different vibrational modes or to extract the thermal conductivity of materials like Graphene [START_REF] Calizo | Temperature Dependence of the Raman Spectra of Graphene and Graphene Multilayers[END_REF], Si [START_REF] Hart | Temperature Dependence of Raman Scattering in Silicon[END_REF] [14], Ge [START_REF] Jaramillo-Fernandez | Raman thermometry analysis: Modelling assumptions revisited[END_REF], SiGe [START_REF] Stoib | Spatially resolved determination of thermal conductivity by Raman spectroscopy[END_REF], MoS2 [START_REF] Yalon | Temperature-Dependent Thermal Boundary Conductance of Monolayer MoS2 by Raman Thermometry[END_REF], WTe2 [START_REF] Chen | Thickness dependent anisotropy of in-plane Raman modes under different temperatures in supported few-layer WTe 2[END_REF], TiO2 [START_REF] Zani | Contactless Temperature Sensing at the Microscale Based on Titanium Dioxide Raman Thermometry[END_REF]. It is applied in this work to a chalcogenide ternary alloy for the first time for extraction of its thermal conductivity.

In the first section of this work, we give a detailed analysis of the vibrational modes present in the ternary system of GGSTN and its structural evolution for different annealing temperatures. In the second section, we introduce Raman thermometry and examine the sensitivity of the vibrational modes to temperature and power which aids the extraction of the thermal conductance of the material. Finally, we present the first results for the thermal conductivity of GGSTN by using finite element model.

II. EXPERIMENTAL METHODS

A. Sample Preparation

The Ge-rich GST N-doped (GGSTN) 200 nm thick films were deposited by physical vapor deposition on 300 mm silicon (100) wafers using an industrial tool. The GGSTN thin films were capped by a 45 nm Silicon Nitride thin film to avoid oxidation. This thickness of SiN was selected to enhance the absorbance of laser in GGSTN thin film.

B. Characterization Methods

The samples were annealed at temperatures ranging from 350°C to 500°C for 5 mins under N2 gas flow using a Rapid Thermal Annealing setup, JIPILEC TM . Raman spectra of all samples was acquired using a Horiba TM Labram HR using a 473 nm continuous wave diode pumped laser with an 1800 l/mm grating. The laser emission was focused on the sample using a long distance 100x objective with numerical aperture of 0.5. The maximum power of the laser is 26mW. A continuously variable neutral density filter was used to change the input laser power with optical density ranging from 0.04 to 4. The power was monitored by using a power meter with a photodiode sensor and a multimeter. All measurements were performed under vacuum to avoid convective losses using a LINKAM TM HFS350-PB4 with liquid N2 temperaturecontrolled stage. Thermalization of the sample and chamber stage was assured prior to each Raman spectra acquisition.

III. RESULTS AND DISCUSSION

A. Raman spectra of amorphous GGSTN

First, we investigate the Raman spectra of GGSTN. The Raman spectra of as-deposited GGSTN is recorded under These vibrational modes are related to different species of GeTe (An), SbTe (Bn) and Ge (Cn). The modes related to GeTe are primarily based on the tetrahedral structure of type GeTe4-nGen. The mode present at 76 cm -1 (A1) can be associated to the F2 bending modes of the GeTe4 tetrahedra [START_REF] Andrikopoulos | Raman scattering study of GeTe and Ge2Sb2Te5 phasechange materials[END_REF]. The vibrational modes at 96 cm -1 (A2) and 220 cm -1 (A4) can be assigned to one of the bending modes and the F2 antisymmetric stretching mode of GeTe4 tetrahedra, respectively [START_REF] Andrikopoulos | Raman scattering study of the a-GeTe structure and possible mechanism for the amorphous to crystal transition[END_REF] [START_REF] Mazzarello | Signature of Tetrahedral Ge in the Raman Spectrum of Amorphous Phase-Change Materials[END_REF]. A weak presence of A1 corner-sharing tetrahedral units GeTe4-nGen (n=1,2) can be spotted at 124cm -1 (A3). Further, the most prominent peak at 154cm -1 (B1) is related to the stretching mode of SbTe vibrations in SbTe3 pyramidal structure [START_REF] Petit | Correlation between physical, optical and structural properties of sulfide glasses in the system Ge-Sb-S[END_REF] [START_REF] Němec | Amorphous and crystallized Ge-Sb-Te thin films deposited by pulsed laser: Local structure using Raman scattering spectroscopy[END_REF]. The GeTe modes appear to be less sensitive to Raman scattering than SbTe modes, due to their lower polarizability in this ternary mixture. The amorphous phase is assured by the presence of the peak at 272 cm -1 (C1), which is associated to longitudinal vibration mode of amorphous Ge in tetrahedral sites [START_REF] Kazimierski | Transition from Amorphous Semiconductor to Amorphous Insulator in Hydrogenated Carbon-Germanium Films Investigated by Raman Spectroscopy[END_REF].

B. Temperature dependent structural evolution of GGSTN

After mapping the different vibrational modes present in as-deposited GGSTN, we study its structural evolution as a function of annealing temperature ("Fig. 2"). The spectra were recorded at room temperature in vacuum condition, after annealing at 300°C, 350°C, 400°C, 450°C and 500°C. Up to 300°C, all the vibrational modes assigned to this ternary system, appear to be stable with no structural changes. This indicates structural stability of the material up to 300°C, which is crucial for PCMs. Next, the phase transition takes place between 300-350°C, confirming the increased crystallization temperature. This phase transition alters the structure of the material as can be clearly observed in "Fig. 2". At 350°C, it begins with transition of amorphous Ge vibrations at 272cm -1 to crystalline Ge vibrations at 297cm -1 [START_REF] Kazimierski | Transition from Amorphous Semiconductor to Amorphous Insulator in Hydrogenated Carbon-Germanium Films Investigated by Raman Spectroscopy[END_REF]. As the annealing temperature increases from 350°C to 450°C, the crystalline Ge peak narrows indicating complete crystallization. For GeTe4-nGen based vibrations, the prominent peak in amorphous phase at 96 cm -1 transitions to the one at 124cm -1 indicating a change in the tetrahedral structure, whereas the F2 antisymmetric tetrahedral vibration at 220cm -1 completely disappears Fig. 2 Raman spectra of as-deposited and annealed (300°C to 500°C) of GGSTN. Arrows indicating phase transition indicating a reorganization in the GeTe units. In case of SbTe3 pyramidal units, they remain stable throughout the phase transition and their crystallization is delayed. This can be observed by narrowing of the peak at 154 cm -1 after 450°C.

To sum up, the crystallization begins with Ge as the peak gets narrower with increasing temperature with FWHM decreasing significantly. The delayed crystallization is a result of N-doping as it primarily bonds with Ge, inducing reduced crystallization rate and ensuring stability of the amorphous phase till higher temperature [START_REF] Luong | Impact of Nitrogen on the Crystallization and Microstructure of Ge-Rich GeSbTe Alloys[END_REF]. Further followed by reorganization in the structure of GeTe units. The most significant observation is the stability of SbTe3 vibrational mode throughout crystallization.

C. Raman Thermometry

Now, we have mapped out the vibrations related to different structural units in amorphous and crystalline GGSTN Raman spectra. The basic working principle of Raman thermometry is based on temperature dependent phonon properties of the material. As the temperature of the material changes, it affects the vibrational properties of the material. This affects the position of Raman shift, line width (FWHM) and intensity of the peaks. This property is used to extract the temperature of the material. To perform thermometry, we need to identify such vibrational modes from this convoluted Raman spectra that can act as potential thermometer. For this purpose, in-situ acquisition of Raman spectra was performed for varying temperature under vacuum. Each spectrum was recorded at a step of 20°C from room temperature to 200°C and Lorentzian fitting procedure was followed. After this, calibration coefficient () was extracted from fitting the modes. This parameter is defined as the change in Raman shift peak position with respect to changing temperature -((T)= 0+ T where 0 is the Raman shift recorded at 0 K). For each state of GGSTN material, the vibration mode that show the highest sensitivity to temperature change (i.e. the calibration coefficient) are then selected. For amorphous GSSTN, the vibrations of SbTe3 pyramidal structural units positioned at 154 cm -1 show a calibration coefficient,  = -0.01865 cm -1 /K. "Fig. (3)" represents the change in the Raman shift position of SbTe3 mode as the temperature of the material increases. In the crystalline GSSTN spectrum, the vibrations of crystalline Ge positioned at 300 cm -1 gives  = -0.01795 cm -1 /K, as shown in "Fig. ( 4)", is consistent with previously recorded values [START_REF] Jaramillo-Fernandez | Raman thermometry analysis: Modelling assumptions revisited[END_REF]. This analysis helps us to corelate the temperature of the material to Raman shift. In the next step, the stage temperature that is the material temperature was maintained at room temperature and input power was varied. This yielded a relation between the absorbed power in the material to the Raman shift, giving the power sensitivity. Corelating the power and temperature sensitivity, gives us the local temperature rise of the material relative to the stage temperature (hotspot temperature) as a function of input power intensity by formulism (1) as shown in "Fig ( 5)". Where p is the peak position recorded for a particular intensity of power, 0 is the peak position at 0K and  is the calibration coefficient. From this we know the local temperature of the material for a specific input power and hence, the global thermal conductance (W/K) of the stack was extracted.

The global thermal conductance of amorphous GGSTN is 23 ± 1.5 µW/K and that of crystalline GGSTN is 99.5 ± 13.85 µW/K. Here, we study the sensitivity of these specific vibrational modes of SbTe3 and c-Ge to temperature and power, but their behavior reflects the conductance of the global material and not only the specific material structure. Next step is to build a numerical model for extraction of the GGSTN thermal conductivity.

D. Extracting the thermal conductivity

A finite element based numerical model was built using COMSOL 6.0. A 2D axisymmetric heat transfer model based on Fourier heat diffusion equation was built. A detailed flowchart connecting the experimental and the numerical model is represented in "Fig. [START_REF] Cheng | A thermally robust phase change memory by engineering the Ge/N concentration in (Ge, N)xSbyTe z phase change material[END_REF]". The numerical model was built under following boundary conditions. A radial Gaussian shaped power density profile was defined (2):

(2)

(3)
Here, the Pabs is the absorbed power, Pin is the incident power and Rw is the laser beam waist. The absorbed power was evaluated by measuring the absorbance of the as-deposited and crystalline thin film stacks using a reflectometer. A model was also built to evaluate the absorbance of GGSTN thin film [START_REF] Byrnes | Multilayer optical calculations[END_REF]. The laser beam was measured using the knife-edge method. The contact between the sample and stage was assumed as an ideal heat sink with no thermal resistance. The bottom of the surface is maintained at room temperature. Power amplitude was provided as an input and GGSTN thermal conductivity was parametrized in the model.

The local hotspot temperature was extracted by defining an effective Raman temperature to replicate the experimental conditions [START_REF] Stoib | Spatially resolved determination of thermal conductivity by Raman spectroscopy[END_REF]. Similar to experimental procedure, the local temperature gradient was extracted for different input power and the thermal conductance was mapped with respect to thermal conductivity of GGSTN "Fig. ( 7)". The thermal conductance value extracted from experiments was compared to the simulated thermal conductance vs thermal conductivity map, and its coincidence gave us the precise thermal conductivity of the material. The thermal conductivity for GGSTN in amorphous and crystalline phase are 0.29 W m -1 K -1 and 1.38 W m -1 K -1 respectively.

IV. CONCLUSION

In summary, first we laid out a map of possible vibrational modes related to different structural organizations of GeTe4-nGen and SbTe3 in GGSTN. The temperature dependent study revealed the transition in structural details from amorphous to crystalline. It begins with Ge crystallization and then the narrowing of the peak from 350°C to 450°C indicating complete crystallization. The GeTe modes switch from symmetric tetrahedral to corner sharing tetrahedral structure, whereas the SbTe3 structure shows strong stability over the phase transition. In the next part, we were successful in identifying vibrational modes that show strong dependency on temperature from a convoluted Raman spectrum. SbTe3 mode in amorphous and c-Ge mode in crystalline phase were identified as thermometers with good calibration coefficients. Further, we demonstrated the extraction of local temperature and thermal conductance of the material. This functionality can further be helpful in thermal mapping of devices based on GST as they are being employed extensively for RF, NVM and neuromorphic devices. Finally, the precise thermal conductivity of GGSTN (amorphous and crystalline phase are 0.29 W m -1 K -1 and 1.38 W m -1 K -1 respectively) was extracted by Raman thermometry for the first time.

Fig. 1

 1 Fig. 1 Raman spectra of as-deposited GGSTN, inset: Lorentzian fit for spectra with peaks assignment vacuum is presented in "Fig. 1". Low laser power was incident on the sample to minimize the heating effect inflicted by the laser to avoid structural changes. The inset shows the Lorentzian fit of the spectra. A total of 6 peaks related to different Raman active vibrational modes present in ternary GeTe-SbTe system were identified to properly fit with the experimental Raman spectrum.

Fig. 3

 3 Fig. 3 Calibration curve for as-deposited GGSTN -SbTe3 mode

Fig. 5

 5 Fig. 5 Power absorbed vs local hotspot temperature of the material extracted from Raman measurements. Fit gives the thermal conductance of the material.

Fig. 6 Fig. 7

 67 Fig. 6 Experimental workflow to obtain thermal conductance of the material for changing temperature and power, Simulation workflow to map thermal conductivity to the precise thermal conductance

*Univ. Lille, CNRS, Centrale Lille, Junia, Univ. Polytechnique Hauts-de-France, UMR 8520 -IEMN -Institut d'Electronique de microélectronique et de Nanotechnologie, F-59000 Lille, France.

ACKNOWLEDGMENT

This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 101007321. The JU receives support from the European Union's Horizon 2020 research and innovation programme and France, Belgium, Czech Republic, Germany, Italy, Sweden, Switzerland, Turkey. This project has also received funding from the STMicroelectronics-IEMN common laboratory and is partly supported by the French RENATECH network.


Jean Launaya

Gilles Hiveta

Ahn Vu Duonga

Philippe Boisse
email: philippe.boisse@insa-lyonfre

Experimental analysis of in plane shear behaviour of woven composite reinforcements. Influence of tensions

Keywords: Fabric, Textile, Shear behaviour, Picture frame, Tension PACS: 81.70.-q, 81.70.Bt, 62.20.-x

Two tests are mainly used to identify the shear behavior of fabrics. The "picture frame" which uses a lozenge framework made of four rigid and articulated bars and the "bias test" which is a tensile test on a sample with initially a 45° angle between the yams and the edges. The picture frame test is the more commonly used because the whole specimen is theoretically in a pure shear state. Nevertheless the absence of tension in the woven reinforcement supposes a perfect alignment of fibres and positioning of the clamping point with regards to the framework articulations. In addition, it is often necessary in practice to impose an initial tension which is not quantified and whose consequences are ignored in the classical picture frame test. An experimental device making it possible to measure the tensions during the test is carried out. Different types of teste on different fabrics have been performed. Results presented here concern a twintex fabric that has been selected for a shear benchmark Thanks to this device, it is shown that tensions play an important role in plane shear behaviour.

PICTURE FRAME WITH TENSION MEASUREMENTS Standard Measurements of Shear Behavior

The experimental analysis of in plane shear behaviour of textile performs has been the subject of many works probably because it is the principal deformation mode of these woven fabrics. Among many we can cite [START_REF] Cao | A cooperative benchmark effort on testing of woven composites[END_REF][START_REF] Prodromou | On the relationship between shear angle and wrinkling of textile composite preforms[END_REF][START_REF] Wang | Experimental investigation of the draping properties of reinforcement fabrics[END_REF][START_REF] Peng | Experimental and numerical analysis on normalization of picture frame tests for composite materials[END_REF][START_REF] Lomov | Model of shear of woven fabric and parametric description of shear resistance of glass woven reinforcements[END_REF][START_REF] Potluri | Measurement of mesa-scale shear deformations for modelling textile composites[END_REF][START_REF] Boisse | A mesoscopic approach for the simulation of woven fibre composite forming[END_REF]. Two principal devices are used: the hinged framework or "picture frame" and the tensile test at 45° or "bias test".

A benchmark carried out by different laboratories on identical woven composite fabrics led to large discrepancy between the results especially for those obtained via the picture frame test [START_REF] Cao | A cooperative benchmark effort on testing of woven composites[END_REF]. This tends to show that this test is not completely controlled. A practical difficulty in this test resides in the need for the strict positioning of yam clampings on the straight line that joins to articulations of the frame. If the ends of the yarns are not clamped on this straight line, the kinematics imposed to the specimen does not correspond to pure shear, the yams are stretched and are thus subjected to spurious tensions. It is necessary to scrupulously respect this alignment [. The significant difference between the response to the different picture frame tests and to the bias tests can also be explained by the boundary conditions on the fabric. In the first case the yams are clamped on the rigid bars of the framework whereas for the bias test they are free. It is supposed that taking into account the geometry and kinematics of the picture frame the tensions remain small during the test. This aspect is questionable especially because a small tensile strain of the yams leads to significant strain energies taking into account the much larger tensile rigidity in comparison to that of shearing. An other point concerns the assumption made in most experimental and simulation works that consists in assuming that the effort Fsh (or the in plane shear stress) only depends on the shear angle y. In order to measure the warp and weft tensions during a picture frame test and to analyse the consequences of these tensions on the shear stiffness, a specific device is proposed.

Assumptions And Results Format

Even though it was shown that the results of shear tests are modified when the test is repeated on the same specimen and that some cycles are necessary before obtaining a stabilized value. Nevertheless, since it is the behaviour during forming which interests us, we will always consider the first cycle of loading in present work, as it is the case in a forming process.

In this work a new experimental device is implemented which makes it possible to measure the tensions in a fabric during a shear test. This device will show that, as opposed to the classically used assumptions, the shear stiffness varies with the tensions. In addition it will be seen that the classical "picture frame" test used as pure shear test may cause tensions in the yams of the fabric depending on the limit conditions imposed near the picture frame arms. The tests presented in the present paper are carried out on two composite woven reinforcements: a Twintex ® plain weave composed of glass fibres (60%) and polypropylene fibres (40%) (743g/m2) [l]. In the present work, Fsh will be used, to give the results of the different tests. F sh is normalized from the frame load using:

F = F norm with F = F c L frame (1) sh 2 cos( a I 2) ' norm L }ab
where Lfra me and L rab are the lenghts of the side of the picture frame and of the sample respectively [START_REF] Cao | A cooperative benchmark effort on testing of woven composites[END_REF][START_REF] Peng | Experimental and numerical analysis on normalization of picture frame tests for composite materials[END_REF]. a= n/2-y is the angle between the two bars connected at of top of the picture frame.

Picture Frame With Tension

Devices for measurement and adjustment of the tension are added to a picture frame in the warp and weft directions. (Fig. 1). In each direction the yams are fixed on a system which is connected to the picture frame by a load sensor on one end and by an adjustment on the other end. So it is possible to measure the warp and weft tensions during the test and to adjust the initial tensions. Possibly, by stopping the test, warp and weft tensions can be set to given values. The shear angle can be calculated from the frame displacement or be measured by optics measurements. The values of angles provided in the present work will be the average values measured by optical measures in the useful zone of the specimen. The load sensors added on the frame measure the load at right angles to the rigid bar. The yams do not remain perpendicular to the bars during the test (Fig. 1). It is thus necessary to correct the values measured by the sensors to obtain the tensions in the yams. The tension in the yam is obtained from the measure of the sensor by: T = F s en sor yarn cos ( y) [START_REF] Prodromou | On the relationship between shear angle and wrinkling of textile composite preforms[END_REF] This device will first enable to analyze the influence of a initial tensions on the shear rigidity of a woven reinforcement. Then in the second time the evolution of the tension will be analyzed during a shear test. Finally tests for which the tension will be set to zero during all the tests will be performed.

RESULTS OBTAINED

Tensions in the yarns during shear de ormation

Influence Of The Initial Tension On Shear Stiffness

Fig. 2 shows the shear loads obtained in the case of the Plain Weave fabric for initial tensions equal to 0, 10 and 20 N per yam. These results show that the shear load is increased by the tension in the yams especially in the first part of the shear curve (small and medium shear angles). For a 25° shear angle, the ratio between the shear load of a test without initial tension and with an initial tension equal to 20 N is close to 2. This result is not surprising because the shear rigidity is for a part due to frictions between the yams (especially in the first part of the curve). When increasing the tension in the yams, the weaving brings a transverse compressive force and consequently the friction loads and consequently the shear stiffness increases. For large shear angles, the shear load is less affected by the initial tensions. The initial tensions are applied for a null shear angle and their influence on the tension state after a large shear is less important. Although the yam tensions are null at the beginning of the test, they increase in a significant way during the test. Such a picture frame shear test is thus not strictly a pure shear test since fairly important yam tensions are superimposed. A possible explanation for theses tensions can be found in the geometry on a mesoscopic scale (i.e. the scale of the unit woven cell) and in the woven nature of the reinforcement [START_REF] Lomov | Model of shear of woven fabric and parametric description of shear resistance of glass woven reinforcements[END_REF].

Although the distance from one edge to the other of the picture frame is constant during the test, the yam length increases slightly. The boundary conditions and the need for the strict positioning of yam clampings can induce tension. When the shear kinematics is prescribed to the fabric, the contact with nearby yams tends to create an in plane undulation of the yams. Taking into account the clamping of the yams in the rigid bars of the framework and the strong tension rigidity of the yams, it results a tension in the yams. It can be noted that the tension in the yams remains null in the first part of the shear test (Fig. 3). This is reasonable since it as been shown [START_REF] Boisse | A mesoscopic approach for the simulation of woven fibre composite forming[END_REF] that, in the first part of the shear test, the yarns undergo a rigid body rotation and are not in contact with their neighbours. The tension in the yams only increases starting from the beginning of the side contacts

Comparison between picture frame tests and bias test

The test carried out in the present section consists to maintain the tensions very near a zero value. Fig. 4 shows the comparison between the shear curve obtained in this case with that obtained with a standard picture frame test i.e. without relaxing the tension during the test and the bias test. The results obtained by setting the tension to zero in the picture frame test are rather close to those obtained by the bias test. This is explained by the fact that tensions in the bias test are null or very small because the ends of yarns of the sheared zone are free. This test clearly shows the significant consequences of the tensions in a standard picture frame test. Other tests on other fabrics have been performed that lead to the same type of results.

CONCLUSION

A new experimental device makes it possible to measure the tensions in the warp and weft directions during a picture frame shear test. The first results show that the tensions which generally are not taken into account play a significant role in shear beahaviour. When the initial tensions vary, the obtained shear loads in the first part of the test increase with the initial tension. The measurement of the tensions during a picture frame shear test shows that those tensions may not remain null during the test. It has been shown that the tensions influence significantly the picture frame results and can explain the differences observed between the different picture frame tests (benchmark) and the differences between the bias test results and the standard picture frame results. The real coupling between shear and tension behaviour has then to be further investigated and maybe taken into account in the finite elements computations of fabric forming [START_REF] Dumont | Identification des caracteristiques mecaniques de renforts tisses a partir de mesures de deformations par correlation d' images[END_REF]. Especially when the forming processes uses tools, especially blank holders, because the tensions can become significant.

1 , 8 -FIGURE 2 .

 182 FIGURE 2. Shear load curves for different initial tensions.

FIGURE 3 .

 3 FIGURE 3. Tension during the picture frame test on the Plain-Weave fabric.

2 _ 4 .

 24 �--_ _ P _i c _ tu _ re _ f _ ra _ m _ e _ w _ ith _ t _ en _s _ i o _ n _ se _ t _ t o _ z _ er _ o � i-;.;-.----------= -::: :;�����:==J Picture frame test with tensions equal to zero on the Plain Weave fabric. Comparison with strandard picture frame and bias test.

ACKNOWLEDGMENTS

The authors acknowledge the support provided by the EADS aeronautical company and by the European Commission (ITOOL STREP Project).


Julien Monniot
email: julien.monniot@inria.fr

François Tessier

Modeling the Allocation of Heterogeneous Storage Resources on HPC Systems

Conclusion:

The required storage capacity is not far over 16TB. Splitting the requests and using an algorithm well suited for this strategy is however necessary (random choice or worst-fit is this case).

Figure 3 .Figure 4 .

 34 Figure 1. Top500: I/O bandwidth to computing power ratio for the top 3 HPC platforms, last 10 years.

Figure 2 .

 2 Figure 2. Percentage of the sum of the requested capacities (from all requests of dataset) that could be successfully allocated during simulation. One marker per simulation run, for a 16TB platform. Results show the algorithm and layout in use, and are grouped by split strategy.


Cédric Prigent

Alexandru Costan

Gabriel Antoniu

Loïc Cudennec

Loïc Cudennec Supporting

Efficient Workflow

Supporting Efficient Workflow Deployment of Federated Learning Systems across the Computing Continuum

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

Our Proposal

Early Results

Inconsistent performance

Adapt models for each clients with their local data distribution

Impact of data drift on model performance Impact of client learning rate and number of local epochs on training

Performing FL training over smartphone data from 8 users for recognition of Daily Living Activities