Hi everyone,
I’ve been building an end-to-end differentiable pipeline that designs kirigami — a variant of origami with cuts instead of folds — by gradient descent in JAX.
It works very well, but it had a blind spot. Every hinge (the part connecting the faces), where all the stress and failure typically live — was modeled as a simple energetic model with stiffnesses I picked by hand. No geometry.
To fix that I needed real continuum mechanics for soft materials (SOFA), but SOFA is slow, non-differentiable, and operates within an incompatible runtime. This is where Tesseract turned out to be the perfect bridge: wrap its /apply + /jacobian, and the black-box FEM solver becomes a differentiable function.
Using Tesseract, I optimized a hinge’s actual cross-section against a fatigue objective — yielding a TPU flexure that folds a full 90° for ~2,000 cycles. Better still, I could measure the hinge’s true spring law and feed it back to the fast JAX model.
Finally, I explore how the macro and micro-level simulators can enable the co-design of kirigami structures perfectly tuned to a target physical behavior and geometry. This unlocks a whole new dimension of design where we can now precisely tune either the structural stiffness or the final geometry at every level based on our needs.
I would be glad to hear your thoughts on this!
Julien
Full writeup — details + repo:
→ Tesseract | Julien Kloers
In the end-to-end differentiable pipeline, the kirigami hinges are modeled by a simple energy function.