Journées SCOPe


22 et 23 juin – IEMN – Amphithéâtre LCI – Villeneuve d’Ascq

L’objectif de ces journées est de réunir au niveau national les acteurs français et francophones impliqués dans la recherche sur le silicium et les semi-conducteurs/oxydes poreux et leurs applications.

Cette 4ème édition des journées SCOPe sera l’occasion pour notre communauté de partager nos dernières avancées dans le domaine et de promouvoir la jeune génération.

Les doctorants et post-doctorants seront prioritaires pour les présentations orales.

Thèmatiques abordées :

  • Elaboration, techniques de fabrication, structures
  • Luminescence et photonique
  • Microélectronique
  • Systèmes et intégration
  • Coatings fonctionnels
  • Capteurs
  • Photovoltaïque
  • Matériaux d’électrodes, énergie, conversion, stockage
  • Imagerie médicale, thérapie

PRESENTATION


Un intérêt nouveau pour les semi-conducteurs poreux a émergé dans la communauté scientifique dans les années 90, notamment grâce à la découverte de la photoluminescence du Si poreux. Les procédés électrochimiques sont devenus des méthodes phares de nano-structuration de la plupart des semi-conducteurs (Si, GaAs, InP, etc…) et ont permis la génération de réseaux poreux auto-ordonnés (Al2O3, TiO2, etc…). Ils ont dès lors été largement étudiés car ils ont ouvert des perspectives pour la fabrication de nano-objets à propriétés nouvelles, en particulier électroniques et optiques. Par la suite, les domaines d’applications potentielles de ces structures anodiques poreuses, n’ont cessé de croître et d’évoluer.  En particulier, le Si poreux dotés de fonctionnalités variées a révélé un potentiel considérable pour des applications en opto- et microélectronique, systèmes, capteurs, matériaux pour l’énergie, ainsi que pour la nanomédecine.

Aujourd’hui, le silicium et les semi-conducteurs poreux sont au cœur des intérêts scientifiques de nombreuses équipes de recherche dans le monde entier, attirant l’attention de chimistes, de physiciens, de biologistes et de médecins.

COMITE SCIENTIFIQUE


  • BASTIDE Stéphane – ICMPE-CMTR – Université Paris-Est
  • BILLOUÉ Jérôme – GREMAN – Université de Tours
  • COFFINIER Yannick – IEMN – Université de Lille 1
  • CUNIN Frédérique – Institut Charles Gerhardt Montpellier – Université de Montpellier
  • DJENIZIAN Thierry – MADIREL – Aix Marseille Université
  • GAUTIER Gaël – GREMAN – Université de Tours
  • SANTINACCI Lionel – CiNaM – Aix Marseille Université

COMITE D’ORGANISATION


  • COFFINIER Yannick – IEMN – Université de Lille 1HOSU
  • Ioana Silvia  – IEMN – Université de LilleHAMDI
  • Abderrahmane  – IEMN – Université de Lille
  • BILLOUÉ Jérôme – GREMAN – Université de Tours
  • CUNIN Frédérique – Institut Charles Gerhardt Montpellier – Université de Montpellier
  • GAUTIER Gaël – GREMAN – Université de Tours

Pour plus de renseignement : yannick.coffinier@univ-lille1.fr
ou sur le site :scope2017.sciencesconf.org

Une étude dans le cadre d’une collaboration entre l’IEMN et le Fraunhofer Institute for Photonic Microsystems

fait la couverture du journal Analytical Methods (RSC)

(c) IEMN-ECM – Création graphique : Anne Callewaert – Duchêne

A user-friendly guide to the optimum ultraviolet photolithographic exposure and greyscale dose of SU-8 photoresist on common MEMS, microsystems, and microelectronics coatings and materials

Fraunhofer Institute for Photonic Microsystems, Maria-Reiche-Str. 2, 01109 Dresden, Germany
matthieu.gaudet@ipms.fraunhofer.de

Abstract :

We provide here a user-friendly guide to find the optimum i-line (365 nm) photolithographic exposure dose of an arbitrary thickness of SU-8 on various substrate materials and thin film coatings used in MEMS, microsystems and microelectronics technologies: semiconductors, 2D materials (graphene and MoS2) plastics, glass, metals and ceramics. By considering the variation of the absorption coefficient of SU-8 to ultraviolet light and the effect of partial reflections during the photolithography, we develop an analytical model for the exposure of SU-8. The critical exposure dose of the SU-8 enables a calculation of the exact greyscale photolithographic exposure time of the photoresist which optimizes the fabrication of microsystems structures (microcantilevers, microbridges, microchannels…) of a desired thickness. The optimum exposure doses are presented in both graphical and tabular format to enable user-friendly information based on the desired SU-8 thickness, the desired greyscale thickness and the specific wafer or coating used for the deposition. Interestingly, in the context of grey-scale lithography the model predicts that the surface reflectivity has a major impact on the resulting membrane thickness for a fixed dose and reducing the SU-8 thickness – on a highly reflecting surface a thicker membrane is obtained, on a low reflecting surface a thinner membrane in obtained when reducing the SU-8 thickness. The result is a useful guide for designers working with SU-8 in the context of many fabrication processes, e.g. MEMS, laboratory on a chip, microfluidics, microsystems, microengineering, micromoulding, and flexible electronics etc. – where a myriad of coatings and wafers are now used.

Anal. Methods, 2017,9, 2495-2504
DOI: 10.1039/C7AY00564D, Paper

IEMN : Romain Peretti reçoit une chaire d’excellence internationale

La Région Hauts-de-France et le Fond Européen de Développement Régional ont attribués une chaire d’excellence internationale à Romain Peretti, chercheur à l’IEMN, pour son projet  » TeraHertz Optical Traping of Viruses  » (THOTroV). Grâce à cette chaire, Romain Peretti a pour ambition de développer une technique de piégeage optique dans une nouvelle plage de longueur d’onde : le TeraHertz, afin de l’appliquer à des objets aussi petits que des virus.

Séminaire : Terahertz sources based on quantum cascade heterostructures – Juraj Darmo

In the framework of MNO department, IEMN is pleased to announce the seminar of Dr. Juraj Darmo

Date : thursday 4 mai at 15h00
Location : Salle du Conseil – IEMN-LCI

Pr. Juraj Darmo : Photonics Institute, Vienna University of Technology Gusshausstr. 27-29, 1040 Vienna (Austria)

The state-of-the-art of terahertz (THz) sources based on quantum cascade heterostructures will be reviewed from the viewpoint of short pulse generation. There are two principal applications of the concept of quantum cascade – for the emission and for the detection of terahertz waves. On the emitter’s side, THz quantum cascade lasers (QCLs) are increasingly exploited for sensing and imaging applications. Today QCLs span a frequency range from 1.8THz to 5 THz with record peak output powers of 1 W and CW single-mode average powers in the 100s mW range. Recently, a concept of heterogeneous QCL active region has been successfully implemented leading to broadband emission over one octave and even to frequency comb operation with a 600 GHz bandwidth. Such active medium can be used for the generation of short (bandwidth limited) pulses.

In this work we have exploited broadband QCLs active regions to demonstrate an alternative route to boost the performance of time-domain spectroscopy (TDS), the main spectroscopic technique used in the THz frequency range. The available broad THz QCL gain is used to amplify a weak broadband THz spectrum generated through optical-to-THz low-efficiency conversion. In the 2.0-3.0 THz window this approach leads to an increase of SNR by two orders of magnitude compared to a standard TDS system. Moreover we demonstrate the generation of amplified pulses as short as 2.5 ps and analyse hurdles preventing us from exploiting all the gain bandwidth available from the broadband THz QCL gain medium. The presentation will end with an outlook on the future developments of the presented technology.

 

Séminaire MNMB : Analyse biomécanique et fluidique des anévrismes aortiques – Francesca Condemi

Francesca Condemi, chercheuse post-doctorante à l’École Nationale Supérieure des Mines de Saint-Étienne, viendra nous présenter ses travaux sur l’analyse biomécanique et fluidique des anévrismes aortiques.

Date : Vendredi 5 mai 2017 – 13h30
Lieu : Amphithéâtre – IEMN-LCI

Francesca Condemi: École Nationale Supérieure des Mines de Saint-Étienne

Abstract:

Ascending thoracic aorta aneurysm (ATAA) is known to be the 19th common cause of human death. Although prophylactic surgery is the only treatment suitable, the risk of mortality associated to elective surgical repair is up to 5%. In clinical practice, maximum diameter is the standardly used risk of rupture indicator with a critical diameter threshold of 5.5 cm. However, for aneurysms with a diameter smaller than 5.5 cm, negative outcomes (rupture, dissection and death) before surgical repair are of 5-10%.

Biomechanical studies showed that ATAA results in disturbed aortic hemodynamics and mechanical weakening of the aortic wall. However, there is still a lack of insight on how the disturbed hemodynamics and the mechanical weakening may be related.

In this talk the speaker will give a brief introduction on the methodology developed at the EMSE to analyze the fluid- and biomechanical behaviors of the ascending thoracic aorta aneurysm with concomitant aortic insufficiency (AI). This methodology combines 4D flow MRI, CFD models and the mechanical bulge inflation test to determine possible correlation between the aortic flow pattern/WSS distribution and the ATAAs wall strength in patients affected by ATAA and AI.

Biography:

Dr. Francesca Condemi obtained her PhD in Biomedical and Computer Science Engineering from the University Magna Graecia of Catanzaro (UMG), Italy in 2015. During her PhD, she was a visiting scholar at University of Kentucky (UKY), Lexington, Kentucky, USA from 2013 to 2015. She remained at UKY until March 2016 as a Postdoctoral Fellow. Currently she is a Postdoctoral Fellow at École Nationale Supérieure des Mines of Saint-Étienne (EMSE), France, in the Computational Fluid Dynamics (CFD) Branch. Her research interests revolve around the development of numerical models for the design of cardiovascular assist devices and for the analysis of the human cardiovascular system. Currently she is working on the development of a comprehensive and original model for the biomechanical analysis of the ascending thoracic aorta affected by aneurysm and concomitant aortic insufficiency (AI).

 

Séminaire: Electroactive 2D-Materials: Growth, Properties and Applications – Pr Mohamed Siaj

Jeudi 27 avril 2017 14 h00,
Amphithéâtre de l’IEMN

Pr Mohamed Siaj, Professeur invité Université Lille 1, IUT A
Chemistry Department, Université du Québec à Montréal (UQAM)
Abstract.
Two-dimensional (2D) materials have attracted much attention due to their unique properties. Controllable synthesis of 2D materials with high quality and high efficiency is essential for their large-scale applications. In parallel to the chemical synthesis  route, chemical vapor deposition (CVD) has been one of the most important techniques for the synthesis of 2D materials. For the present talk I will briefly overview our most recent work on CVD growth of graphene, boron nitride, core-shell nanoparticles@graphene and transition metal dichalcogenides (TMDs) including MoSe2 and WSe2. In parallel, I will show that the resulting electroactive nanomaterials could be used as electrodes for chemical and biosensing as well as hydrogen evolution reaction applications.
 
Short CV.
Mohamed Siaj holds the Canada Research Chair in 2D-Materials for Chemical and Biosensing applications since 2016. He received his Ph.D. in Chemistry at Laval University, Quebec, Canada, under the supervision of Peter McBreen, a world leader in Surface Science. Following postdoctoral training at the Colin Nuckolls group at Columbia University, New York, a leading institution in graphene research, Siaj joined the Department of Chemistry at Université de Quebec à Montréal as an assistant professor, and he is holding the rank of associate professor since 2012. He is acting as Co-Director of the Research Center on Nanomaterials and Energy (NanoQAM) and Director of Analysis of Materials and Microsystems Regrouping (RAMM), Faculty of Science, UQAM. Prof. Siaj has extensive experience in different areas of surface science and nanomaterials-based graphene. Siaj’s group activities focus on the growth, synthesis, processing and characterization of advanced nanostructured electroactive materials and their integration into chemical and biosensors.

 

Sputtered Titanium Carbide Thick Film for High Areal Energy on Chip Carbon-Based Micro-Supercapacitors

Manon Létiche, Kevin Brousse, Arnaud Demortière, Peihua Huang, Barbara Daffos,Sébastien Pinaud, Marc Respaud, Bruno Chaudret, Pascal Roussel, Lionel Buchaillot, Pierre Louis Taberna, Patrice Simon, and Christophe Lethien*

The areal energy density of on-chip micro-supercapacitors should be improved in order to obtain autonomous smart miniaturized sensors. To reach this goal, high surface capacitance electrode (>100 mF cm−2) has to be produced while keeping low the footprint area. For carbide-derived carbon (CDC) micro-supercapacitors, the properties of the metal carbide precursor have to be fine-tuned to fabricate thick electrodes. The ad-atoms diffusion process and atomic peening effect occurring during the titanium carbide sputtering process are shown to be the key parameters to produce low stress, highly conductive, and thick TiC films. The sputtered TiC at 10−3 mbar exhibits a high stress level, limiting the thickness of the TiC-CDC electrode to 1.5 µm with an areal capacitance that is less than 55 mF cm−2 in aqueous electrolyte. The pressure increase up to 10−2 mbar induces a clear reduction of the stress level while the layer thickness increases without any degradation of the TiC electronic conductivity. The volumetric capacitance of the TiC-CDC electrodes is equal to 350 F cm−3 regardless of the level of pressure. High values of areal capacitance (>100 mF cm−2) are achieved, whereas the TiC layer is relatively thick, which paves the way toward high-performance micro-supercapacitors.

First published: 31 March 2017
>> DOI: 10.1002/adfm.201606813

© WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Un neurone artificiel mille fois plus économe en énergie qu’un neurone biologique

Chef d’œuvre de l’évolution, le cerveau humain est une source d’inspiration pour les scientifiques. Des chercheurs de l’IEMN et de l’Ircica ont ainsi mis au point un neurone artificiel ultra-efficace en énergie et qui reproduit très précisément les signaux électriques générés dans le cerveau. Ces travaux sont publiés dans la revue Frontiers in Neuroscience.

Dans notre cerveau, les neurones sont connectés entre eux et génèrent une réponse binaire aux informations qu’ils reçoivent des autres cellules nerveuses : soit ils émettent un signal électrique, appelé aussi potentiel d’action, soit ils restent silencieux. Ce système est à la base de tous nos processus cognitifs et moteurs. Des chercheurs de l’Institut d’électronique, de microélectronique et de nanotechnologie (IEMN, CNRS/Université Lille I/ISEN Lille/Université Valenciennes Hainaut-Cambresis/École centrale de Lille) et de l’Institut de recherche sur les composants logiciels et matériels pour l’information et la communication avancée (Ircica, CNRS/Université Lille 1) ont reproduit ces propriétés à l’aide de dispositifs électroniques nanométriques.

Mesurant quelques microns carrés, ces neurones artificiels sont disposés en grand nombre sur un circuit intégré en silicium. Ils ne consomment que quelques dizaines de femtojoules (10-15 J) lors de la génération d’un potentiel d’action. Une performance énergétique environ 1000 fois supérieure à celle d’un neurone biologique, et qui dépasse de plusieurs ordres de grandeur celle de tous les autres neurones artificiels existants. Ces travaux ouvrent de nombreuses perspectives, comme la création de réseaux ultra-faible énergie pour l’intelligence artificielle. Ils pourraient également servir à développer les interactions entre neurones artificiels et neurones vivants, par exemple pour traiter des maladies comme celle de Parkinson ou réparer des altérations de la moelle épinière. Cette étude remet au passage en cause l’idée que les neurones naturels sont parfaitement optimisés sur le plan énergétique.

Contacts chercheurs :
Alain Cappy – IEMN et Ircica
Contact communication INSIS :
insis.communication@cnrs.fr

Références :

A 4-fJ/Spike Artificial Neuron in 65 nm CMOS Technology
Ilias Sourikopoulos, Sara Hedayat, Christophe Loyez, François Danneville, Virginie Hoel, Eric Mercier and Alain Cappy
Front. Neurosci., 15 March 2017
https://doi.org/10.3389/fnins.2017.00123

Extrait de l’article      __________________________________________________________________________

Ilias Sourikopoulos 1  –  Sara Hedayat 1  –  Christophe Loyez 1, 2,  –  François Danneville 1, 2,  –  Virginie Hoel 1, 2,  –  Eric Mercier 3, 4 and Alain Cappy 1, 2

  • 1 CNRS, Université Lille, USR 3380 – IRCICA, Lille, France,
  • 2 CNRS, Université Lille, ISEN, Université Valenciennes, UMR 8520 – IEMN, Lille, France,
  • 3 Université Grenoble Alpes, Grenoble, Grenoble, France,
  • 4 CEA, LETI, MINATEC Campus, Grenoble, France

As Moore’s law reaches its end, traditional computing technology based on the Von Neumann architecture is facing fundamental limits. Among them is poor energy efficiency. This situation motivates the investigation of different processing information paradigms, such as the use of spiking neural networks (SNNs), which also introduce cognitive characteristics. As applications at very high scale are addressed, the energy dissipation needs to be minimized. This effort starts from the neuron cell. In this context, this paper presents the design of an original artificial neuron, in standard 65 nm CMOS technology with optimized energy efficiency. The neuron circuit response is designed as an approximation of the Morris-Lecar theoretical model. In order to implement the non-linear gating variables, which control the ionic channel currents, transistors operating in deep subthreshold are employed. Two different circuit variants describing the neuron model equations have been developed. The first one features spike characteristics, which correlate well with a biological neuron model. The second one is a simplification of the first, designed to exhibit higher spiking frequencies, targeting large scale bio-inspired information processing applications. The most important feature of the fabricated circuits is the energy efficiency of a few femtojoules per spike, which improves prior state-of-the-art by two to three orders of magnitude. This performance is achieved by minimizing two key parameters: the supply voltage and the related membrane capacitance. Meanwhile, the obtained standby power at a resting output does not exceed tens of picowatts. The two variants were sized to 200 and 35 μm2 with the latter reaching a spiking output frequency of 26 kHz. This performance level could address various contexts, such as highly integrated neuro-processors for robotics, neuroscience or medical applications.

Introduction

Computing technology, based on binary coding, Von Neumann architecture and CMOS technology, is currently reaching certain limits (Waldrop, 2016). Traditional computers, the champions for the resolution of complex equation systems, have difficulties to classify/organize data, something that the human brain seems to accomplish effectively. For this reason, research in the field of Artificial Neural Networks (ANNs) is attracting much attention and is quickly developing worldwide. At the bottom of these efforts lies the ultimate goal to realize machines that could surpass the human brain, in some aspects of cognitive intelligence. In that sense, brain research and ANNs bear the promise of a new computing paradigm.

Currently, traditional, discrete-time, digital ANNs, fueled by the unprecedented computational capability of modern Graphics Processing Units (GPUs), represent the state-of-the-art for addressing cognitive tasks (Oh and Jung, 2004; LeCun et al., 2015) such the ones encountered in computer vision applications. However, it is the more recent class of Spiking Neural Networks (SNNs), often referred to as the third generation of neural networks, that are known to be bio-realistic and more computationally potent compared with their predecessors (Maass, 1997). The functional similarity with the actual biological networks permits envisioning, apart from interfacing or reproducing brain processes, the implementation of circuits and systems with cognitive characteristics without explicit programming tasks. This would endow the modern generation of computers with the capacity to learn from input data.

In SNNs, neuronal communication is carried out in the form of noise-robust, signal pulses or “spikes.” SNNs try to reproduce the physical characteristics of the brain, through highly connected neurons dendrites and axons. At present, two main methodologies fulfill neuro-inspired computing tasks: digital simulation and hardware implementation.

In digital simulations, the dynamics of neuronal models are coded in software and calculated on general-purpose digital hardware. Digital simulations have the advantage that they can be reliably programmed using numerical operations of very high precision. However, their reliability comes at the cost of high circuit complexity, which is necessary for the data transfer, exchange and processing (Cao et al., 2015). Accordingly, the energy consumption remains still very high, especially as one juxtaposes biological data for comparison. For instance, the brain of the cat is emulated at the cost of a power dissipation in the megawatt range (Ananthanarayanan et al., 2009), while the animal brain actually consumes only a couple of watts.

As far as hardware implementations of SNNs are concerned, the alternative, “neuromorphic,” approach consists of employing VLSI circuit technology, namely CMOS fabrication processes which can be possibly associated with more advanced device technology such as memristors (Kim et al., 2012). The analog hardware approach consists of a large-scale integration of silicon artificial neurons (AN) and synapses, in an attempt to produce low power neuro-inspired architectures compatible with the current electronics technology.

The efficiency of such architectures can be revealed in contrast to the energy consumption of biological neurons (BN). Brain activity needs a continuous exchange of ions through the cell membrane and these exchanges correspond to the charge and discharge of the neuron capacitance (soma, dendrite, and axon). As a consequence, the important parameters for energy dissipation are the membrane capacitance and the voltage swing. Membrane capacitance varies considerably according to the type of neuron cell, ranging from picofarads to nanofarads for the largest ones (Amzica and Neckelmann, 1999; Golowasch et al., 2009; Rössert et al., 2009; Tripathy and Gerkin, 2012). Interestingly, a recent estimation of the capacitance that could be involved for computation in the human cortex is proposed in Hasler and Marr (2013). The calculations are based on a digital power model and suggest a biological system of 1012 neurons with a 0.5 Hz average firing rate. The total capacitance value is calculated at 245 pF that is high when compared with the femtofarad order common in integrated circuits. Indeed, energy savings could be envisioned in silicon AN by aiming at reducing the capacitance and/or the voltage swing.

Next to a reduced capacitance, low power operation in silicon neurons can be facilitated by the physics of the MOS transistors. Indeed, as it has been observed (Mead, 1989, 1990) the nervous system uses, as its basic operation, a current that increases exponentially with the membrane voltage, similar to the current-voltage characteristic of a MOS transistor operating in subthreshold. However, the physical origins of these exponential dependencies are very different: a non-linear voltage controlled conductance in biological membrane against a current controlled by an energy barrier in the transistor. Due to this, the MOS transistor can only asymptotically approach a slope of kT/q per e-fold of current change, while the biology is not limited as such (Mead, 1989, 1990). Even if I-V characteristics show different slopes, a bridge between the physics of biological membrane and the one of electronic devices has been established, especially when the energy and power properties are considered. This led to the advent of neuromorphic silicon neurons, which allowed neuronal spiking dynamics to be directly emulated on analog large-scale integration chips. So far, several generations of SNNs have been proposed and the reader could refer to the relevant works (Misra and Saha, 2010; Indiveri et al., 2011; Hasler and Marr, 2013) to obtain more information.

Based upon these previous works, this paper describes the design and measurement results of a new family of silicon AN. It was designed under the guidelines of (i) a biophysically meaningful model, (ii) a minimum energy dissipation, (iii) an analog circuit that would allow a complete time variation modeling of the membrane potential and (iv) a resulting topology, that when implemented in CMOS technology, it would occupy a minimum area in order to enable large scale integration. This unique combination of characteristics resulted in a neuron topology that was measured to consume several orders of magnitude less energy than the values encountered either for BN or the AN reported so far.

The rest of this paper is organized as follows: The “Materials and methods” section will be devoted to a discussion on neuron energy efficiency, the selection of the mathematical model and the circuit topology and functionality. The circuit proposed in this paper was fabricated and characterized experimentally. Both simulation and experimental results are described in the “Results” section. The “Discussion” section presents a comparison with the state of the art and highlights issues regarding noise, supply voltage sensitivity and temperature impact. Finally conclusions are drawn in the eponymous last section.

Présentation de la plateforme Microscopie en champ proche

Vendredi 31 mars 2017 à 9:00
Amphithéâtre du LCI IEMN

Ce séminaire est destiné aux membres du laboratoire souhaitant (mieux) connaitre la plateforme et les possibilités offertes pour l’analyse de surfaces, de composants et de nanostructures jusqu’à l’échelle atomique à l’aide des instruments AFM (microscope à force atomique) et STM (microscope à effet tunnel).

Programme prévisionnel :

  • 9:00 : Introduction « Scanning Probe Microscopy » Dominique Deresmes
  • 9:15 : La microscopie à force atomique à l’IEMN Dominique Deresmes
  • 9:35 : Mesures AFM en liquide pour la caractérisation de matériaux actifs Alexis Vlandas
  • 9:55 : Mesures des propriétés électriques à l’échelle de la molécule par microscopie champ proche Stéphane Lenfant
  • 10:15 : Café
  • 10:35 : La microscopie à effet tunnel à l’IEMN Maxime Berthe
  • 10:55 : Exemples et applications de la microscopie à effet tunnel Bruno Grandidier

CONTACT :
Maxime Berthe
Ingénieur de Recherche – Plateforme Champ Proche
Tél : +33 (0)3 2019 7863
maxime.berthe@iemn.fr

Première journée de rencontre du Réseau Optique, Photonique et Applications Lasers (OPAL)

Le réseau régional Optique Photonique et Applications Lasers organise sa première journée de rencontre le 15 Mars 2017 à l’Amphithéâtre de l’IRCICA sur la Haute Borne à Villeneuve d’Ascq

Le réseau Optique, Photonique et Applications Lasers (OPAL) vient d’être créé dans la région Hauts-de-France
Il a pour mission :
• d’identifier les acteurs relevant de son champ thématique dans la région Hauts-de-France ;
• de mettre en place une organisation et des actions structurantes pour sa communauté ;
• d’organiser les échanges et le partage du savoir, des compétences et des bonnes pratiques ;
• de proposer des actions de formation ;
• d’être des acteurs et interlocuteurs auprès des tutelles et des collectivités territoriales.

Pour cela, il bénéficie du soutien du Réseau Optique et Photonique (ROP) de la plateforme des réseaux de la Mission pour l’Interdisciplinarité du CNRS (http://www.cnrs.fr/mi/spip.php?article465) et du CERLA.

Le réseau OPAL s’organise sur la base du volontariat. Toute personne souhaitant adhérer au réseau et à sa liste de diffusion peut adresser sa demande à : opal-contact@services.cnrs.fr

Cette première rencontre des membres du réseau régional métier OPAL est ouverte à tous (membres et futurs membres), elle présentera les différentes forces de compétences ou instrumentales de la région Hauts-de-France dans le domaine de l’optique.

Quelques présentations scientifiques, beaucoup d’échanges, posters et buffet au sein de l’Institut de Recherche sur les Composants logiciels et matériels pour l’Information et la Communication Avancée à l’université de Lille Sciences et Technologies (accès).

Pour participer gratuitement à cette journée dont le programme provisoire est en ligne, inscrivez-vous jusqu’au 27 Février 2017 sur : https://opal.sciencesconf.org/