Boron nitride nanotube composites: production and properties
Bibliographic record
Abstract
Boron nitride nanotubes (BNNTs) exhibit a range of properties that are as impressive as those of carbon nanotubes (CNTs), including comparable mechanical properties, but with different multifunctional advantages such as considerably higher thermal stability, polarizability, wide band gap, and high neutron absorption capability. These characteristics make BNNTs attractive for the fabrication of enhanced composites including for mechanical reinforcement, heat dissipation, high temperature composites, neutron shielding, and piezoelectric composites among other possibilities. Recent advances in large-scale production of BNNTs have resolved the supply limitation for BNNT nanocomposites research and the development of BNNT-enhanced composites is now poised to accelerate rapidly. Here we highlight the production of large-scale, composites-relevant quantities of BNNTs based on a scalable RF plasma torch method and present examples from our work on both bulk BNNT-polymer composites and nanocomposites based on BNNT sheets.
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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 | 0.000 |
| 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) | 0.001 | 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".