- A new European project, AID4GREENEST, aims to design new AI-powered characterisation and modelling tools for steel production.
- These tools will allow industry to replace time-consuming ‘trial and error’ approaches, reducing waste, lowering emissions, and saving costs.
Enhanced material quality, the reduction of carbon emissions and waste generation, and reduced risks to the supply of critical raw materials.
These are the three principal objectives of a new international research initiative involving 10 partners from four European countries in which IMDEA Materials Institute (Madrid, Spain) will play a key role.
The project, AID4GREENEST, coordinated by IMDEA Materials, will develop six new AI-based rapid characterisation methods and modelling tools for advanced and more sustainable ‘green steel’ production.
As well as coordinating the project, IMDEA Materials is set to carry out crucial research relating to the
development of an AI-based tool to predict the steel processing techniques required to develop optimised steel parts with pre-defined microstructural components.
This will include new methodologies for accelerated testing of how the metal will perform under stress at high temperatures (creep testing). Understanding how this type of deformation will affect the material over time is vital in producing steel with adequate long-term strength and heat resistance.
Such tools will allow steel manufacturers to design and test new steel grades computationally, prior to production, eliminating the traditional experimental ‘trial and error’ approach to steel production.
In total, the project’s scope will cover the steel design (chemistry and microstructure), process design (processing parameters), product design (processing and heat treatments) and product performance (creep) stages.
Developing new AI-powered characterisation and modelling techniques will help to reduce component rejection rates, and thus waste, by detecting inadvertent design flaws earlier in the production process.
This will allow steel producers to avoid the production of flawed steel pieces which must then be rejected and discarded. As well as limiting waste, this will also lead to major cost savings.
Additionally, the tools to be designed through AID4GREENEST will also enhance material quality by reducing defects, lower the industry’s carbon footprint and decrease dependence on key raw materials.
AID4GREENEST earlier this week held its official kick off meeting at IMDEA Materials Institute in Madrid, Spain, in which all 10 of the collaborating partners were represented.
Among those in attendance was IMDEA Materials’ researcher, Dr. Ilchat Sabirov, the coordinator of this ambitious project. Having spent the past decade working on research related to the steel industry, he said that improved sustainability has become an ever-increasing concern for steel manufacturers.
“Steel production is one of the leading causes of industrial carbon emissions worldwide,” he acknowledged. “This is a reality that the industry must face and resolve in order to meet the goals of the European Union to reduce CO2 emissions by at least 55% by 2023 compared to 1990 levels, and to become completely carbon neutral by 2050.”
“This challenge is not one that any individual research centre, institute or country can overcome on its own. That’s why collaborative projects like AID4GREENEST are so important in ensuring that science and industry are working together to meet these common goals of greater sustainability, while also carrying out cutting-edge research and development here in Spain and in Europe.”
Besides IMDEA Materials, the international team behind AID4GREENEST also includes Spanish steel manufacturer Reinosa Forgings and Castings and the Spanish Association for Standardisation (UNE), the Fraunhofer Institute for Mechanics of Materials IWM and consultants EurA AG (Germany), Oulu University (Finland), Ghent University, the University of Liège, ePotentia and OCAS NV (Belgium).
AID4GREENEST is funded by the European Union through the Horizon Europe Framework Program (HORIZON) for the modelling and characterisation of advanced materials under grant agreement number 101091912.