Effect of grain size on the optimal architecture of electrodeposited metal/polymer microtrusses
Bibliographic record
Abstract
Nanocrystalline microtruss materials are novel cellular hybrids of metal and polymer produced by electrodepositing thin coatings of nanocrystalline metal over rapid prototyped polymer preforms. This study develops an optimisation method for the architectural design of electrodeposited metal/polymer composite microtrusses used as cores in sandwich beams. For an optimally designed structure employing conventional polycrystalline nickel, a direct substitution of nanocrystalline nickel will improve structural performance; however, it is likely that the structure will also become significantly sub-optimal. Achieving optimal design with nanocrystalline nickel entails large geometric changes from the conventional polycrystalline case. The same applies if the polymer preform is removed after electrodeposition. The strong connection between optimal architecture and grain size was therefore examined for the limiting cases of polymer-filled and hollow microtrusses. It was found that grain size reduction was more important than polymer preform removal such that grain size effects dominate over the majority of microtruss design space.
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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 | 0.001 |
| 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) | 0.001 | 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".