Simbiótica Research

Abstract
Research at the intersection of computational design and material science, utilizing algorithmic biomimicry to re-engineer urban infrastructure. Modeled on Porifera (sea sponges), the project deploys a regenerative matrix of bio-concrete and bio-polyurethane optimized for variable porosity, heavy metal sequestration, and structural self-healing.
Context / Problem
Simbiótica operates at the intersection of computational design and material science, utilizing algorithmic biomimicry to re-engineer urban infrastructure. Modeled on the fluid dynamics and filtration efficiency of Porifera (sea sponges), the project deploys a regenerative matrix of bio-concrete and bio-polyurethane. This system is defined by data-driven performance metrics, specifically optimizing for variable porosity, heavy metal sequestration, and structural self-healing.
Methodology
Our methodology integrates empirical material testing with digital morphogenesis, generating scalable "chunks" — adaptive volumetric units that aggregate based on environmental feedback loops. We translated the morphology and porosity of the sea sponge into a quantifiable, simulation-ready computational model using parametric definitions. Material exploration was conducted through physical experimentation, informed by computational properties and executed via porous scale models.
Results
In Venice, urban cracks are often patched with impermeable materials that disrupt the biological cycles of the ecosystem. We use photogrammetry to model these cracks and calculate the material volume needed to fill each fissure. Simbiótica heals the city by replacing impermeable patches with porous, bio-based alternatives that revitalize Venice's local ecosystem.
Conclusions
By merging physical prototyping with parametric growth simulations, Simbiótica proposes a bio-receptive architecture capable of active water purification and multidirectional expansion, establishing a quantifiable framework for sustainable urban metabolic systems.
Project Documentation






