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001016297 001__ 1016297
001016297 005__ 20250823040225.0
001016297 0247_ $$2CORDIS$$aG:(EU-Grant)101141626$$d101141626
001016297 0247_ $$2CORDIS$$aG:(EU-Call)ERC-2023-ADG$$dERC-2023-ADG
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001016297 0247_ $$2doi$$a10.3030/101141626
001016297 035__ $$aG:(EU-Grant)101141626
001016297 150__ $$aAutomated Model Discovery for Soft Matter Systems$$y2024-07-01 - 2029-06-30
001016297 372__ $$aERC-2023-ADG$$s2024-07-01$$t2029-06-30
001016297 450__ $$aDISCOVER$$wd$$y2024-07-01 - 2029-06-30
001016297 5101_ $$0I:(DE-588b)5098525-5$$aEuropean Union$$bCORDIS
001016297 680__ $$a
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.

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