Biological growth as an alternative approach to on and off-Earth construction
Bibliographic record
Abstract
A critical aspect of human space exploration and eventual settlement is the ability to construct habitats while minimizing payload mass launched from Earth. To respond to this challenge, we have proposed the use of fungal bio-composites for growing extra-terrestrial structures, directly at the destination, significantly lowering the mass of structural materials transported from Earth and minimizing the need for high mass robotic operations and infrastructure preparations. Throughout human history, the construction of habitats has used biologically produced materials, from bone and skins to wood and limestone. Traditionally, the materials are used only post-mortem. Currently, the idea of working with living biological organisms, and the phenomenon of growth itself, is of increasing interest in architecture and space applications. Here, we describe the use of mycelium-based composites as an alternative, biological approach for constructing regenerative and adaptive buildings in extrem environments and extraterrestrial habitats. It is a continuation of our research program initiated under the auspices of the “Myco-architecture Off Planet” NASA NIAC Team. These composites, which are fire-resistant, and insulating, do not consist of volatile organic compounds from petrochemical products and can be used independently or in conjunction with regolith, could employ the living biological growth in a controlled environment, for the process of material fabrication, assembly, maintenance, and repair, providing structures resilient to extra-terrestrial hazards. Here we outline the potential and challenges of using bio-composites for Earth and space applications. We describe how these might be addressed to make this biological approach feasible, providing new, growing materials for designing and building sustainable habitats, both on Earth and for long-duration space missions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".