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DISCOVER

Automated Model Discovery for Soft Matter Systems

Grant period2024-07-01 - 2029-06-30
Funding bodyEuropean Union
 CORDIS
Call numberERC-2023-ADG
Grant number101141626
IdentifierG:(EU-Grant)101141626

Note: Automated models boosting research on soft matter. Soft materials, which can be easily deformed or structurally altered by thermal or mechanical stress, are essential in modern life, affecting autonomy, sustainability and health. However, accurately modelling these materials is complex and usually limited to a few well-trained experts. The ERC-funded DISCOVER project aims to make constitutive modelling more accessible through automated model discovery. Objectives include developing neural networks that autonomously find the best models, parameters and experiments for various soft matter systems. Furthermore, researchers will assess model performance in different experiments and use Bayesian analysis to measure uncertainties. Automated model discovery should enable exploration of a vast range of model parameters, offering insight into soft matter systems that traditional methods cannot achieve.
   

Recent Publications

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A note on constitutive artificial neural networks for finite strain plasticity
Mechanics research communications 155, 104707 () [10.1016/j.mechrescom.2026.104707]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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A generalized dual potential for inelastic Constitutive Artificial Neural Networks: A JAX implementation at finite strains
Journal of the mechanics and physics of solids 206, 106337 () [10.1016/j.jmps.2025.106337]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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A note on constitutive artificial neural networks for finite strain plasticity (source code and data)
Zenodo () [10.5281/ZENODO.16900782]  GO BibTeX | EndNote: XML, Text | RIS

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A note on constitutive artificial neural networks for finite strain plasticity
9 Seiten () [10.2139/ssrn.5588650]  GO  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Automated model discovery for tensional homeostasis: Constitutive machine learning in growth and remodeling
Computers in biology and medicine 186, 109691 () [10.1016/j.compbiomed.2025.109691]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

All known publications ...
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 Record created 2025-08-14, last modified 2025-08-23
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