3D-Printed Wood: Programming Hygroscopic Material Transformations
Name
Correa-2015-3D-Printed Wood_ Pro.pdf
Size
659.22 KB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Correa, David
Reichert, Steffen
Menges, Achim
Papadopoulou, Athina
Guberan, Christopher
Jhaveri, Nynika
Tibbits, Skylar
Date Issued
September 2015
Journal
3D Printing and Additive Manufacturing
Publisher
Mary Ann Liebert, Inc.
Citation
Correa, David et al. “3D-Printed Wood: Programming Hygroscopic Material Transformations.” 3D Printing and Additive Manufacturing 2.3 (2015): 106–116.
Version
Final published version
Abstract
Rapid advances in digital fabrication technologies and new materials development allow for direct control and programmability of physical material transformations. By utilizing multimaterial 3D printing technologies and anisotropic material compositions, we can physically program hygroscopic materials such as wood to precisely sense and self-transform based on fluctuations in the environment. While wood remains one of the most common building materials in use today, it is still predominantly designed to be industrially standardized rather than taking advantage of its inherent anisotropic properties. This research aims to enhance wood's anisotropic and hygroscopic properties by designing and 3D printing custom wood grain structures to promote tunable self-transformation. In this article we present new methods for designing hygroscopic wood transformations and custom techniques for energy activation. A differentiated printing method promotes wood transformation solely through the design of custom-printed wood fibers. Alternatively, a multimaterial printing method allows for greater control and intensified wood transformations through the precise design of multimaterial prints composed of both synthetic wood and polymers. The presented methods, techniques, and material tests demonstrate the first successful results of differentiated printed wood for self-transforming behavior, suggesting a new approach for programmable material and responsive architectures.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Architecture
Massachusetts Institute of Technology. Self-Assembly Lab
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1089/3dp.2015.0022
