Revealing the Mechanics of Helicoidal Composites through Additive Manufacturing and Beetle Developmental Stage Analysis
Bibliographic record
Abstract
Abstract Investigation into the microstructure of high performance natural materials has revealed common patterns that are pervasive across animal species. For example, the helicoid motif has gained significant interest in the biomaterials community, where recent studies have highlighted its role in enabling damage tolerance in a diverse set of animals. Moreover, the helicoid motif corresponds to a highly adaptable architecture where the control of the pitch rotation angle between fibrous structures produces large changes in its mechanical response. Nature, takes advantage of this special feature enabling an active response to particular biological needs occurring during an animal's ontogeny. In this work, we demonstrate this adaptive behavior in helicoidal architectures by performing a mechanistic analysis of the changes occurring in the cuticle of the figeater beetle (Cotinis mutabilis) during its life cycle. We complement our investigation of the beetle with the testing of 3D printing samples and a systematic analysis of the effect of pitch angle in the inherent mechanics of helicoidal architectures. Experimentation and analysis reveal improved isotropy and enhanced toughness at lower pitch angles, highlighting the flexibility of the helicoidal architecture. Moreover, trends in stiffness measurements were found to be well‐predicted by laminate theory, suggesting facile mechanics laws for use in biomimicry.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".