Ramus Tree is a semi-permanent suspended architectural installation testing the potential of fibrous biomaterials as ecologically healthier alternatives to industrial wood.
Current industrial wood products pose challenges in ecological reintegration due to use of heavy-metal preservatives, synthetic formaldehyde-based resins, and volatile organic finishes—which undergo environmental leaching during decomposition, introducing persistent toxins that bioaccumulate across trophic levels.
Extrusion-printed using a 6-axis robotic arm, 18 modules form a 4m-tall tensioned structure pushing regenerative and bio-based materials beyond small-scale lab experiments and toward deployed architectural applications. Through the combination of biopolymer science, computational design, additive manufacturing, and reconfigurable assembly, Ramus Tree produces mechanically tunable, lightweight, geometrically differentiated panels that can be locally bent and recombined. The system compares raw and weather-resistant modules to discern the capacity of bio-composites to perform under outside weathering. It presents architecture as an evolving material system and explores how simple renewable materials might support future construction methods that are lightweight, materially efficient, and increasingly capable of operating in outdoor environments.
Location: Suburban Station Courtyard, Center City Philadelphia, USA.
Team: Led by Bowen Qin (PhD Student Arch), Jessy Xu (MArch Grad), Behzad Modanloo (PhD Student Arch), Begum Birol (PhD Student Arch), Kelly Rice (MSc Arch), and Dr Laia Mogas-Soldevila. With production and installation support from Rhada Iyer, Sophia Wang, Sophia Chen and Santiago Cortes.
Support: Commissioned by Design Philadelphia for their 2026 "Design Revolution Festival". We are very grateful to logistics support from Trebor Adams and Jermaine Jenkins at DesignPhiladelphia. Material development funding by Penn's University Research Foundation and the Johnson&Johnson Foundation. Materials and Methods developed at DumoLab Research (DLR).
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