Le réseau
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L'organisation
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La structure de veille et de réflexion prospective
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Actualités
Vers des matériaux conducteurs intelligents pour l’avenir de l’électronique
Un récent article publié dans Advanced Science explore les propriétés révolutionnaires de matériaux polymères conducteurs capables de répondre à des stimuli externes, ouvrant la voie à une électronique plus performante et durable.
Quand les polymères deviennent adaptatifs
Les polymères conducteurs ne sont plus de simples supports d’électronique. Grâce à des avancées en chimie des matériaux, des chercheurs ont mis au point des structures capables de répondre à des changements environnementaux tels que la température, la lumière ou des champs électriques. Ces propriétés permettent de concevoir des dispositifs électroniques plus efficaces, notamment pour les capteurs ou les systèmes d’énergie.
PPWR : L’Europe amorce une transformation majeure sur les emballages
Le règlement européen sur les emballages et déchets d’emballages (PPWR) est sur le point d’être adopté définitivement, marquant une étape clé vers une harmonisation des exigences environnementales au sein de l’Union européenne. Ce texte, qui remplacera la directive actuelle, vise à réduire les déchets d’emballages, à promouvoir le recyclage, le réemploi et l’incorporation de matières recyclées.
Avec des mesures comme l’obligation de recyclabilité pour tous les emballages et un étiquetage harmonisé, le PPWR ambitionne de limiter l’impact environnemental des emballages tout en évitant la fragmentation du marché intérieur. Les entreprises doivent anticiper ces changements pour rester compétitives et conformes aux nouvelles exigences dès leur entrée en vigueur, prévue en 2026.
www.usinenouvelle.com L’intelligence artificielle et le machine learning accélèrent la recherche en matériaux
Deux avancées récentes en intelligence artificielle (IA) et en machine learning promettent de révolutionner le développement de produits en réduisant les délais de recherche. La plateforme MaterialsZone, basée en Israël, a intégré un développement guidé par IA dans ses outils de découverte de matériaux, tandis que des chercheurs japonais ont exploité le machine learning pour optimiser la production de polymères.
MaterialsZone transforme l’expérimentation
MaterialsZone utilise une boucle de retour d’information basée sur l’IA pour affiner les recommandations expérimentales en temps réel. Chaque expérience réalisée enrichit le modèle IA, permettant une optimisation progressive des paramètres tout en prenant en compte les contraintes de coût et d’impact environnemental. La plateforme vise à réduire les cycles d’expérimentation et à améliorer l’efficacité grâce à un cadre sans codage.
Optimisation de la polymérisation au Japon
Au Japon, des chercheurs de l’Institut des sciences et technologies de Nara ont modélisé mathématiquement la polymérisation d’un copolymère styrène-méthacrylate de méthyle à l’aide du machine learning. En combinant une synthèse en flux constant et des algorithmes d’apprentissage, ils ont rapidement identifié les conditions idéales de fabrication. En seulement cinq cycles de calcul, ils ont atteint un équilibre précis de 50 % de styrène, révélant des paramètres clés comme la concentration du solvant et la durée de réaction.
L’IA révolutionne les condensateurs à film avec un nouveau polymère haute performance
Des chercheurs, en collaboration avec le Scripps Research et le Lawrence Berkeley National Laboratory, ont utilisé des modèles d’apprentissage automatique pour identifier un polymère inédit capable de résister à des conditions extrêmes. Ce polymère, issu d’une bibliothèque de 50 000 structures chimiques, établit un record en matière de performance électrique et thermique pour les condensateurs à film.
Les condensateurs à film jouent un rôle clé dans les technologies d’électrification, telles que les véhicules électriques, l’aéronautique, et les énergies renouvelables. Leur efficacité repose sur des films polymères capables de stocker l’énergie tout en tolérant des températures élevées et des champs électriques intenses.
En utilisant des réseaux neuronaux pour analyser une vaste base de données, les chercheurs ont identifié trois polymères prometteurs, issus d’une précédente étude exploitant la « click-chemistry ». L’un d’eux a démontré une combinaison exceptionnelle de résistance thermique, densité énergétique et efficacité, marquant une avancée majeure pour les technologies énergétiques. Cette méthode d’IA ouvre de nouvelles perspectives pour accélérer le développement de matériaux durables et performants.
Atelier de Veille et Prospective 2025 : Réglementation – Moteur d’Innovations Technologiques & de Nouvelles Recherches ?
Les polymères biodégradables peuvent-ils créer des microplastiques ?
Les plastiques biodégradables sont souvent présentés comme une solution pour réduire la pollution plastique, mais ils peuvent également générer des microplastiques. Bien que ces plastiques ne persistent pas indéfiniment, leur dégradation dépend fortement de leur environnement de fin de vie.
Des plastiques comme le PLA, PBAT et PBS, utilisés à grande échelle, sont conçus pour se dégrader plus facilement que les plastiques traditionnels. Toutefois, ils peuvent libérer des microplastiques pendant leur dégradation, et leur impact dépend de leur destination finale. Par exemple, le PLA se dégrade plus rapidement en conditions de compostage industriel, mais il peut libérer des microplastiques dans l’environnement si l’environnement n’est pas propice à sa dégradation complète.
Les chercheurs soulignent qu’il est important de ne pas considérer les plastiques biodégradables comme une solution universelle, car ils doivent être correctement traités pour éviter la pollution. Une bonne gestion des déchets est essentielle pour maximiser les avantages écologiques de ces matériaux.
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Adhérez au GFP
Devenez un membre et découvrez les avantages d’un abonnement GFP.
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Sections locales GFP
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Les partenaires
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cnrs
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lrccp
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logo-ispa_coul_fond-fonce
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ICS
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LPMC
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http://www.waters.com
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arkema
http://www.coatex.com
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http://www.hutchinson.com/fr
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