Shape from Release

Objects with different shapes can dissolve in significantly different ways inside a solution. Predicting different shapes' dissolution dynamics is an important problem especially in pharmaceutics. More important and challenging, however, is controlling the dissolution via shape, i.e. , designing shapes that lead to a desired release behavior of materials in a solvent over a specific time. Here, we tackle this challenge by introducing a computational inverse design pipeline. We begin by introducing a simple, physically-inspired differentiable forward model of dissolution. We then formulate our inverse design as a PDE-constrained topology optimization that has access to analytical derivatives obtained via sensitivity analysis. Furthermore, we incorporate fabricability terms in the optimization objective that enable physically realizing our designs. We thoroughly analyze our approach on a diverse set of examples via both simulation and fabrication.