Grateful to be part of the 2025 NAS Kavli Fellows cohort representing MIT MechE —a week of discussions w/ early career leaders across disciplines! Enjoyed sunny SoCal, enthralled w/ ‘diverse’, ‘engaging’, and ‘insightful’ scientific discourse, especially in the current scientific context.

We used this model to inversely design spinodal metamaterials for large deformations, validated by exp. on the optimized designs. This work aids in understanding structure-property relations of high-density spinodals at finite strains, relevant to energy absorption applications.

The experimental data served to develop a physics-enhanced deep learning framework that leverages multiple convex energy potentials to provide a nonconvex potential, whose derivative yields the nonlinear stress-strain responses of spinodal metamaterials.

We used >300 large-deformation experiments on samples spanning the design space, accompanied by nonlinear computational models, to gain insight on the deformation and energy dissipation mechanisms towards enhanced structure-property relations in this nonlinear regime.

Starting 2025 w/ a collaborative effort w/ @sid-kumar.bsky.social & team using experimental data sets, physics-enhanced ML, and computational models to predict, understand, and inversely design spinodal metamaterials for large deformation and energy absorption. doi.org/10.1016/j.em...