EMMC related Initiatives

New platform supports open innovation in coating materials

Twelve partners from seven countries have united to make the development and production of corrosion protection technologies more sustainable, economical and faster. The Helmholtz-Zentrum Hereon is coordinating the project. The European Union is funding VIPCOAT within the Horizon 2020 program, specifically for the area of “Nanotechnologies, Advanced Materials, Biotechnology, and Advanced Manufacturing and Processing” (NMBP), over four years. The project has been started on May 1st, 2021.

About the project

The goal of the EU-funded VIPCOAT project is to create an open innovation platform that should assist engineers in developing coating materials and constructing accelerated life test scenarios to assess their durability. Initially, the platform will target the aeronautic industry. However, it will later host interoperable applications, based on standardized ontologies as extensions of the European Materials Modelling Ontology that should enable to transfer methods and insights to other industries. The VIPCOAT platform will open the door to new production concepts with reduced process steps, lower energy consumption and reduced use of natural resources. Supporting modelling, the platform should also promote the development of green, cheap and efficient coatings that inhibit corrosion.

The aim

The aim is to create an open innovation platform that can be used by the research, industrial, political and public sectors alike. The approach facilitates an effective transfer of science and communication between all those involved. The platform is to serve as a database (for experimental, industry-relevant and modeling data), scientific infrastructure and simulation tool at the same time. Machine learning and physics-based modeling are combined here to optimize industry-relevant active protective coating development processes. VIPCOAT is designed to support industry in making the development of customized innovative corrosion protection technologies not only faster and more economical, but mainly to also to make them more sustainable and environmentally friendly.

Duration
Start: 01.05.2021
End: 30.04.2025

Business-to-business data ecosystem

The Digital Open Marketplace Ecosystem (DOME) 4.0 aims at developing a comprehensive industrial data ecosystem aligned with the Open Science and Open Innovation objectives to enable sharing of business-to-business (B2B) data for the purpose of value generation and creation of new or enhanced products, processes, and services. DOME 4.0 will be open to all providers and users of data, and aims to facilitate maximum knowledge extraction with the help of ontology-driven semantic data interoperability and modern data processing technologies adopted from the fields of Machine Learning (ML) and Artificial Intelligence (AI). These features are crucial to scale and advance the proposed ecosystem to any sector of the economy. Given the significant contribution of the materials and manufacturing sectors to the European economy, DOME 4.0 focuses on data-driven knowledge generation within these key sectors.

The project duration is four years and will focus on two parts: a) core ecosystem technology advancement with connectors to other marketplaces, data and knowledge bases; and b) demonstration of added value via nine B2B success stories covering areas such as nanomaterials, manufacturing equipment and processes, lightweight construction, etc., while dealing with data characteristics such as quantity, quality, velocity, formats, and sources. Data governance, sovereignty, provenance and adherence to FAIR principles are proposed.

True to its ethos, DOME 4.0 offers a scalable, convergence mechanism to the vast array of research and innovation activities undertaken within the Horizon 2020 programme. The project coalesces the key H2020 developments from multiple marketplace projects, open simulation platforms, open translation environments, industrial networks, data platforms, and Coordination and Support Actions in advanced materials and manufacturing. Central to DOME 4.0 is its interdisciplinary consortium with European SMEs, large industries, research institutes and academia.

Duration
Start: 01.12.2020
End: 30.11.2024

OntoTrans provides an ontology-based Open Translation Environment. Its Artificial Intelligence approach enables end users to represent in a standard ontological form their manufacturing process challenges and to connect them with relevant information sources and materials modelling solutions, capable to support optimal materials and process design.

OntoTrans provides smart targeted guidance through the whole translation process, namely from the initial user case specification to actual materials modelling workflows with related validation, verification and uncertainty quantifications to deliver a full complete experience to companies.
This is achieved via analysis of available data (data fusion), modelling workflow options, simulation and contextual results interpretation.

OntoTrans is fully integrated into existing and emerging developments in materials and manufacturing, including integration with digital materials modelling marketplaces and open simulation platforms.

Duration
Start: 01.04.2020
End: 31.03.2024

With transport responsible for about a quarter of the world’s greenhouse emissions, the development of electric vehicles (EVs) is deemed crucial.

The EU-funded SUBLIME project aims to significantly increase the use of EVs by taking on the technical challenges presented by the consumer needs. These are mainly associated with reducing EV costs while increasing their ability to travel greater distances and allowing for fast charging.

The SUBLIME project will help develop a complete value chain for new sulfide electrolyte-based solid-state battery cells with high capacity and high voltage stability.

Duration
Start: 01.05.2020
End: 30.04.2024

The EU-funded CHARISMA project is set to harmonise Raman Spectroscopy for characterisation across the life cycle of a material, from product design and manufacture to lifetime performance and end-of-life stage.

The project will demonstrate the feasibility of its concept in three industry cases. In the long term, it aims to make Raman spectroscopy a widespread technology used within the Industry Commons concept.

Duration
Start: 01.11.2020
End: 31.10.2024

The I4BAGS project aims to develop innovative processing and characterisation solutions for microelectronics and battery applications. Driven by topical challenges in communication and energy management, and supported by large industrial demand for innovation, most performing devices have a complex thin-film stacking architecture, the manufacturing processes of which require fine monitoring of materials and their interface properties .

This project aims to demonstrate the versatility of low-energy ion implantation (LEII) protocols as a processing tool to locally modify electronic, electrochemical and electrical properties in different materials and structures. The work is organised and results will be demonstrated on two platforms: materials for thin film solid state batteries (TFSSB) and materials for graphene-on-SiC-enabled systems (GRSiC).

Objectives: Low-energy ion implantation tailored for targeted application. Broad frequency range characterisation methods from DC to millimetre waves supported by suitable modelling and software. Generated data collected within Open Innovation Environment and disseminated throughout European materials’ communities (EMMC, EMCC, AMI2030).

Target applications: electric transportation, smart metering, power applications and electricity storage.

The I4BAGS Consortium comprises partners from Poland and Belgium (Wallonia), connecting two research centres: L-IMiF (Lukasiewicz - Institute of Microelectronics and Photonics) and MateriaNova with two SMEs: QWED (EMMC Organisational Member) and IONICS.

The project is co-funded by the Polish National Centre for Research and Development under M‑ERA.NET3/2021/83/I4BAGS/2022 and the Service public de Wallonie (SPW) under M‑ERA.NET3.

Duration
Start: 01.09.2022
End: 31.08.2025

The main ULTCC6G_EPac objective is to develop novel functional materials based on advanced multilayer technology of Ultra-Low Temperature Co-Fired Ceramics (ULTCC); to characterise their properties; and to demonstrate and validate the new materials in application to telecommunication devices.

Information and communication technologies for 5G and 6G are today one of the most vital areas to address demand for energy efficiency, sustainability, environmental friendliness, low manufacturing cost, and circular economy. There is a great need for new or upgraded materials with specific properties and relevant technologies. The ULTCC6G-EPac will design, implement, validate, and demonstrate ultra-low temperature co-fired ceramics (ULTCC) fabricated at 400-700 °C, destined for multilayer high frequency (GHz-THz) devices. It implements new functional materials, facile ceramic tapes, and  upgraded ULTCC packages (RoHS and REACH compliant) useful for the 6th generation devices in telecommunication K- and D-band.

The materials are characterised in terms of their structural, microwave and mmWave-dielectric, thermal and mechanical properties. Materials’ modelling is used to support the characterisation and also to design 6G electronic components as demonstrators of targeted applications.

The ULTCC6G_EPac Consortium comprises partners from Germany (Fraunhofer Institute for Ceramic Technologies and Systems), Poland (Łukasiewicz - Institute of Microelectronics and Photonics; and QWED), and France (Laboratoire d'électronique des technologies de l'information; and INVEOS).

The work of QWED (EMMC Organisational member) co-funded by the Polish National Centre for Research and Development under M‑ERA.NET2/1/2021 contract.

Duration
Start: 01.09.2021
End: 31.08.2024

BatCAT is the project that realizes the manufacturability programme from the BATTERY 2030+ Roadmap, creating a digital twin for battery manufacturing that integrates data-driven and physics-based methods. It develops a cross-chemistry data space for two technologies, (1) Li-ion and Na-ion coin cells and (2) redox flow batteries, addressing a triple challenge in digital manufacturing: (i) Design, (ii) operation, and (iii) trust.

(i) By improved product and process design and optimization, product quality and process efficiency increase. This requires decision support that makes complex decision problems accessible to human decision makers. The digital twin technology from BatCAT provides an interpretable industrial decision support system (IIDSS) based on multicriteria optimization. Surrogate modelling connects the high-level analysis firmly to ground-truth data.

(ii) Process operation and control is improved by acquiring and analysing sensory and operando data at real time, facilitating live interventions within an Industry 5.0 real-time environment. BatCAT follows a rigorous approach to actionable modelling, combining data-driven methods with deductive reasoning based on ontologies and formal methods (answer set programming and BPMN-based model checking) to guarantee a reliable behaviour.

(iii) The approach from BatCAT produces trustworthy models: Machine learning always retains a clearly characterized connection to the ground truth, and any decision support or decision making from inductive reasoning is safeguarded by constraints through formal deductive reasoning. All our models and methods are explainable, and all our data are FAIR and explainable-AI-ready (XAIR).

The digital twin is validated in pilot production lines for (1) coin cells and (2) redox flow batteries, proving its transferability across chemistries. The project is closely connected to the Advanced Materials 2030 Initiative, BIG-MAP and BATTERY 2030+, BEPA, DigiPass CSA, EOSC, EMMC, and the Knowledge Graph Alliance, ensuring a community and industry uptake of the results.

Duration
Start: 01.01.2024
End: 30.06.2027

Intelligent tool accelerates discovery of high-performance hard metal coatings

Thermal spraying produces coatings based on metals, alloys, ceramics, plastics and composites by projecting melted or heated powders onto surfaces. Among the available coating materials, hard metals provide excellent resistance to wear and corrosion. However, current hard metal coatings are based on critical elements (Co, W). Moreover, their properties are typically optimised by costly trial-and-error approaches. Creating a reliable selection tool solely based on experimental data would be too cumbersome. Even using microstructure-based physical models to predict their properties would take a lot of time. The EU-funded CoBRAIN project aims to tackle these issues by integrating computational and experimental data with artificial intelligence through semantic interoperability. CoBRAIN will develop an intelligent tool to propose novel solutions from the class of critical materials-free high-entropy hard metals.

Objectives

Wear and corrosion protection play a crucial role in the effort of European Manufacturing Industries to maximise both efficiency and productivity because they are inherently related to the lifetime of the components and their manufacturing cost. Thermal Spray technologies for the deposition of Hardmetals were developed for this reason, i.e. specifically to provide higher resistance to sliding and abrasive wear, coupled with good corrosion resistance. In this field innovation is based on experimental trial-and-error and operational feedback, because the equations that can model the coating performance have to consider the mechanical properties of the hard phase and those of the metal binder, their microstructure and interaction, and their evolution during the non-equilibrium Thermal Spray process. The final coating properties depend on all these factors and more, and they are too many for a physical modelling workflow to provide reliable results on a time scale that is compliant with industrial responses to fluctuating markets, supply chains and regulations. On the other hand, tools based on experimental data that rely only on final coating macro properties require extensive datasets to be reliable. This again conflicts with the response time required by industrial innovation. Moreover, innovation in coating technology is not just a matter of performance and costs: industrial companies have to consider multiple other factors such as the impact on workers, hidden regulatory costs, environmental protection costs, and also general public opinion. CoBRAIN offers a solution to this need, exploiting the integration of computational and experimental data through semantic interoperability, and developing an intelligent tool that will be able to propose novel materials from the class of High Entropy Hardmetals for direct deposition by HVOF, HVAF and CGS Thermal Spray, and capable to estimate their impact on the economy and the environment.

Objectives

Magnetic materials are essential for many applications in energy, information, and communication technologies. However, the complex phenomena at different length and time scales often limit the development of new magnetic materials and devices.

The goal of this project is to develop a magnetic multiscale modeling suite that will allow the design and optimisation of magnetic materials and devices based on multiscale modelling, characterisation, and numerical optimisation. To achieve interoperability between software and analysis tools, we will establish a domain ontology for magnetic materials.

We will collaborate with EU magnet industry to create standards for linking simulation software for magnetic materials from first principles simulations and micromagnetics to device level simulators. MaMMoS will use artificial intelligence (AI) to fuse modeling and characterization data. AI methods will identify and correct systematic errors in the simulation data, enabling more accurate predictions. Moreover, AI models can fill gaps where measurements are not available. AI models can also serve as a surrogate in multi-objective optimisation. Optimisation will guide further experiments or simulations, reducing the development time. In MaMMoS, we will apply this approach to speed up the development of permanent magnets with reduced critical elements for electric machines and to optimise the layout of magnetic field sensors for high linearity range. The MaMMoS software will be validated against benchmarks defined according to the industrial requirements for electric machine and sensor design.

The multiscale magnetic materials modeling suite will be made open source to enable easy access to high-end simulation tools. Interoperability will facilitate data sharing and reuse among researchers and industries. Interpretable machine learning will reveal insights into the physics and chemistry of magnetic materials and guide the discovery of new materials for the European green deal.

Duration
Start: 01.01.2024
End: 31.12.2024

The MatCHMaker project is determined to support excellence in research on methods and tools for advanced materials development. MatCHMaker will enable the integration and interoperability of complex C&M workflows matching the needs of EU manufacturing industry. Requirements on multiphase and multiscale materials coming from Construction, Energy and Mobility sectors will be translated into specific innovation challenges that can be addressed by an integrated approach combining characterization and (physics and data-based) modelling for establishing the process-microstructure-macroscopic properties correlation in advanced materials in a reproducible and efficient way reducing development costs, time and risks while improving sustainability.

Knowledge transfer, data sharing and full interoperability between C&M “communities” will be facilitated using data related standards (CHADA, MODA, EMMO) and by the creation of an open repository with connection to design and manufacturing processes. The repository will be based on Semantic Web to represent rich and complex ontologies. EMMO is the starting point, domain and application ontologies related to MatCHMaker use cases and providing a fully semantical vocabulary to describe the produced C&M data will be developed.

Standardisation of MatCHMaker ontologies, data documentation and domain ontologies will be sought via engagement in specific activities (e.g. collaboration with EMMC, EMCC, OntoCommons CSA). The ambition of MatCHMaker is to validate project results on three Use Cases (UC) representatives of low carbon and clean industry: UC1\Construction\Cement; UC2\ Energy\ Solid Oxide Fuel Cells/Solid Oxide Electrolysis Cells (SOFC/SOEC); UC3\ Mobility\Proton-Exchange Membrane Fuel Cells (PEMFC). The project will foster synergies and interaction with EMMC and EMCC to align MatCHMaker results to councils’ objectives.

Duration
Start: 01.12.2022
End: 31.05.2026

OpenModel – Integrated Open Access Materials Modelling Innovation Platform for Europe. OpenModel aims to design, create, provide, and maintain a sustainable integrated open platform for innovation which delivers predictable, validated, and traceable simulation workflows integrating seamlessly third-party physics-based models, solvers, post-processors and databases.

OpenModel thus bridges the gap from industry challenge via translation to actionable results that enable well informed business decisions. Six use cases (Success Stories) show the applicability to a wide range of materials and their related processing technologies and demonstrate how OpenModel facilitates setting up experiments, reducing error and enhancing development efficiency.

Duration
Start: 01.02.2021
End: 31.01.2025

JIDEP brings industry-oriented collaborative spaces supported by decentralising blockchain network that will overcome trust barriers, non-repudiation, and self-sovereignty of identities and data ownership.

This project builds upon the principles of Industry 4.0 by adopting a coherent approach to semantic communication between diverse actors, aiming to make both direct and indirect contributions to the EU climate neutrality goals of 2050.

JIDEP is a landing place for any organisation that has a data challenge to be addressed on its journey toward delivering a more sustainable material, product, service, or solution. The JIDEP tools will help organisations to unlock the value of data, leading to the development of more sustainable solutions, technologies, and materials.

​The JIDEP platform will be designed to cover the entire product life cycle and assist in steering it toward circular standards implementation at both technological and regulatory levels. While the JIDEP architecture and design principles are industry-agnostic, the implementation of JIDEP in the project will focus on composite materials and Printed Circuit Board (PCB). 

Duration
Start: 01.06.2022
End: 31.05.2025