H2020
Europeo
ExpectedOutcome:Projects are expected to contribute to the following outcomes:
Enable industry to more effectively develop new and work with existing advanced materials by building on digitally integrated and validated modelling and characterisation methods for enhanced materials knowledge along value chains.Accelerate the materials innovation process by allowing a better interpretation of available experimental data and by providing more effective guidance on further experiments.Overcome gaps in modelling and characterisation capabilities targeted at different stages in materials and production value chains by means of adapted and benchmarked suites covering all steps from materials design (including several scales, e.g. from molecular to macroscale) to product development.Achieve an integrated European materials platform,[1] allowing a systemic use of tools and capabilities including materials modelling, characterisation, robotics, data documentation, ontologies, artificial intelligence and machine learning, which are orchestrated to accelerate the design, development and application of chemicals, materials and related processes and manufacturing.
Scope:To sup...
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ExpectedOutcome:Projects are expected to contribute to the following outcomes:
Enable industry to more effectively develop new and work with existing advanced materials by building on digitally integrated and validated modelling and characterisation methods for enhanced materials knowledge along value chains.Accelerate the materials innovation process by allowing a better interpretation of available experimental data and by providing more effective guidance on further experiments.Overcome gaps in modelling and characterisation capabilities targeted at different stages in materials and production value chains by means of adapted and benchmarked suites covering all steps from materials design (including several scales, e.g. from molecular to macroscale) to product development.Achieve an integrated European materials platform,[1] allowing a systemic use of tools and capabilities including materials modelling, characterisation, robotics, data documentation, ontologies, artificial intelligence and machine learning, which are orchestrated to accelerate the design, development and application of chemicals, materials and related processes and manufacturing.
Scope:To support the green and digital industrial transition, there is the need to develop innovative routes to accelerate the design and production of new advanced materials, improving the circular economy and developing alternative feedstocks to support the EU’s open strategic autonomy throughout value chains (and covering all aspects of sustainability). Industrial research for materials from laboratory to production requires the extension of current knowledge on materials behaviour to the entire value chain.
To tackle this challenge, we can build on European leadership in recent advances in multi-scale modelling and characterisation.
The development of novel advanced materials requires a wide and complex range of trusted information on materials and process behaviour, along the entire life-cycle of a material, reaching far beyond the data sets generally available to industry currently. In particular, an approach is required that provides end users with highly flexible, adaptable modelling and characterisation tools as a source of data and knowledge in critical application fields. Subsequently, the validation of the developed methods will help industry to establish trust in these methods. This will also support the emerging need for adopting alternative materials as feedstock compliant with the high qualification standards and strengthen the strategic autonomy and resilience of EU’s industry.
Proposals should address the development of benchmarked, integrated suites of models and characterisation methods for critical application fields in strategic innovation markets (*) covering the different stages in materials and industrial production value chains and circularity.
In particular, proposals should address all of the following:
Develop integrated methodologies of multi-scale and multi-technique characterisation, combined with respective multi-scale modelling and machine learning to improve the reliability and quality of data; understand scaling relationships in the behaviour of advanced materials; develop complex structure-property correlations in advanced materials; ensure complete coverage of conditions in industrial environments. Integrate modelling and characterisation, in particular by Developing modelling methods that provide the capabilities to virtually characterise materials and enhance the interpretation of the results of particular characterisation methods in order to guide and refine experiments;Developing accurate, validated physics-based models, in areas where these capabilities are a bottleneck, by utilising a combination of characterisation and machine learning to generate material and application specific parameters and equations (called materials relations, ref. CWA 17284[2]). Demonstrate the functionality of the suites for the development of certain advanced materials for the green transition. Validate the methodologies and provide benchmarks, i.e. clear documentation of capabilities that can serve as a standard point of reference for industrial application. Research should build on existing standards or contribute to standardisation. Documentation and interoperability for data sharing should be addressed, based on the OntoCommons EcoSystem (OCES).
Projects should build on and seek collaboration with existing projects and develop synergies with other relevant European, national or regional initiatives, funding programmes and platforms. In particular, projects funded under this call should collaborate under the umbrella of the EMMC and EMCC and interact closely with topic HORIZON-CL4-2023-RESILIENCE-01-39 (CSA).
Specific Topic Conditions:Activities are expected to start at TRL 3 and achieve TRL 5 by the end of the project – see General Annex B.
[1]https://ec.europa.eu/info/sites/default/files/research_and_innovation/research_by_area/documents/advanced-materials-2030-manifesto.pdf
[2]https://www.cencenelec.eu/media/CEN-CENELEC/CWAs/RI/cwa17284_2018.pdf
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