Recent advances and perspective on boron nitride nanotubes: From synthesis to applications
Bibliographic record
Abstract
Abstract Boron nitride nanotubes (BNNTs) are emerging nanomaterials with analogous structures and similarly impressive mechanical properties to carbon nanotubes (CNTs), but unique chemistry and complimentary multifunctional properties, including higher thermal stability, electrical insulation, optical transparency, neutron absorption capability, and piezoelectricity. Over the past decade, advances in synthesis have made BNNTs more broadly accessible to the nanomaterials and other research communities, removing a major barrier to their utilization and research. Therefore, the field is poised to grow rapidly and see the emergence of BNNT applications ranging from electronics to aerospace materials. A key challenge, that is being gradually overcome, is the development of manufacturing processes to make “neat” BNNT materials. This overview highlights the history and current status of the field, providing both an introduction to this Focus Issue—BNNTs: Synthesis to Applications—as well as a perspective on advances, challenges, and opportunities for this emerging material. Graphical abstract
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".