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  • 2020Blaneyphd

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Designing parametric matter: Exploring adaptive self-assembly through tuneable environments

Research output: ThesisDoctoral Thesis

Published
  • Adam Blaney
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Publication date30/09/2020
Number of pages432
QualificationPhD
Awarding Institution
Supervisors/Advisors
Award date28/09/2020
Publisher
  • Lancaster University
<mark>Original language</mark>English

Abstract

3D digital models can be created using generative processes, which can be transformed and adapted almost infinitely if they remain within their digital design software. For example, it is easy to alter a 3D structure’s/object's colour, size, geometry and topology by adjusting values associated with those attributes. However, when these digital models are fabricated using traditional, highly deterministic fabrication processes, where form is imposed upon materials, the physical structure typically loses all of these adaptive abilities. These reduced physical abilities are primarily a result of how design representations are fabricated and if they can maintain relationships with the physical counterpart/materials post-fabrication. If relationships between design representations and physical materials are removed it can lead to redundancy and significant material waste as the material make-up of a physical structure can’t accommodate fluctuating design demands (e.g. aesthetics, structural, programmatic). This raises the question: how can structures be grown and adapted throughout fabrication processes using programmable self-assembly?
This research explores and documents the development of an adaptive design and fabrication system through a series of ‘material probes’, which begin to address this aim. The series of material probes have been carried out using research through design as an approach, which enables an exploration and highlights challenges, developments and reflections of the design process as well as, the potentials of rethinking design and fabrication processes and their relationships with materials. Importantly, the material probes engage with material computation (e.g. self-assembly/autonomous-assembly) and demonstrate that various patterns, shapes and structures can have various material properties (e.g. volume, composition, texture, shape) tuned and adapted throughout the fabrication process by inducing stimuli (e.g. temperature, magnetism, electrical current) and altering parameters of stimuli (e.g. duration, magnitude, location). As a result, the structures created can tune and adapt their material properties across length scales and time scales. These adaptive capacities are enabled by creating what is termed ‘tuneable environments. Significantly, tuneable environments fundamentally rethink design and fabrication processes and their relationships with materials, since inducing stimuli and controlling their parameters can be used as an approach to creating programmable self-assembly. Consequently, the material platforms’ units of matter do not have to have pre-design properties (e.g. geometries, interfaces)
This research points towards future potentials of structures that can physically evolve and lead to the decarbonising of urban contexts where they could behave like ‘living material eco-systems’, and resources are shared to meet fluctuating demands through passive means.