Inverse Designing Surface Curvatures by Deep Learning

Inverse-designed growth-based cellular metamaterials

Predicting the influence of geometric imperfections on the mechanical response of 2D and 3D periodic trusses

Neural cellular automata for solidification microstructure modelling

Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID

Enhanced Floating Isogeometric Analysis

Single-test evaluation of directional elastic properties of anisotropic structured materials

Automated discovery of generalized standard material models with EUCLID

Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling

Automated identification of linear viscoelastic constitutive laws with EUCLID

Inverting the structure–property map of truss metamaterials by deep learning

NN-EUCLID: Deep-learning hyperelasticity without stress data

Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties

Floating Isogeometric Analysis

Discovering plasticity models without stress data

Numerical Approaches for Investigating Quasiconvexity in the Context of Morrey’s Conjecture

Unsupervised discovery of interpretable hyperelastic constitutive laws

Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy

Inverse-designed spinodoid metamaterials