Lattice Metamaterials with Mesoscale Motifs: Exploration of Property Charts by Bayesian Optimization
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Bibliographic record
Abstract
Through the current work, the usefulness of the concept of architectured rod lattices based on unit cell motifs designed at mesoscale is demonstrated. Specifically, 2D triangular lattices with unit cells containing different numbers of rods are considered. Combinations of rods of two different types provide the lattices explored with a greater complexity and versatility. For mesocells with a large number of variable parameters, it is virtually impossible to calculate the entire set of the points mapping the material onto its property space, as the volume of calculations would be gigantic. The number of possible motifs increases exponentially with the number of rods. Herein, the lattice metamaterials with mesoscale motifs are investigated with the focus on their elastic properties by combining machine learning techniques (specifically, Bayesian optimization) with finite element computations. The proposed approach made it possible to construct property charts illustrating the evolution of the boundary of the elastic compliance tensor of lattice metamaterials with an increase in the number of rods of the mesocell when a full‐factor experiment would not be possible.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it