Artificial intelligence is a focal point of the AID4GREENEST project. Rina Jaeken from ePotentia attended the AI MSE 2023 Congress (https://dgm.de/aimse/2023/), where she presented a poster titled ‘Artificial Intelligence for the Materials Industry (AI4MI): An Open Online Course Using Open Data.’
AI4MI is an online course funded by ESF, which is designed to bridge the gap between materials researchers and artificial intelligence (https://ai4mi.epotentia.com/). It revolves around four case studies that guide users through solving practical materials problems using AI. Each case study explains the problem, the theoretical details of the models, how to use them, and their interpretation using explainable AI. This approach aims to increase the adoption of AI techniques for those accustomed to working with physical models, providing inspiration for researchers and educational users to integrate these generic AI techniques into their projects.
The AID4GREENEST project will add more content and build a new open data repository for steel data, including microscopy images and data (OM, (B)SE, EBSD), and creep data. Additionally, the project will focus on extracting creep and EBSD data, material properties, and processing parameters using self- and semi-supervised learning, as well as generative AI. Classical machine learning and deep learning techniques will also be further developed. An open data repository will be created to make the data public, with AI tools used to automatically curate the data.
AI4MI will serve as a supporting platform to share further results and provide examples of how to use the dataset. If you wish to stay informed or contribute data, please don’t hesitate to contact us!