Unbiased construction of constitutive relations for soft materials from experiments via rheology-informed neural networks.

ABSTRACT: The ability to concisely describe the dynamical behavior of soft materials through closed-form constitutive relations holds the key to accelerated and informed design of materials and processes. The conventional approach is to construct constitutive relations through simplifying assumptions and approximating the time- and rate-dependent stress response of a complex fluid to an imposed deformation. While traditional frameworks have been foundational to our current understanding of soft materials, they often face a twofold existential limitation: i) Constructed on ideal and generalized assumptions, precise recovery of material-specific details is usually serendipitous, if possible, and ii) inherent biases that are involved by making those assumptions commonly come at the cost of new physical

SUBMITTER: Mahmoudabadbozchelou M 

PROVIDER: S-EPMC10786310 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature