Thermal conductivity of bulk boron nitride nanotube sheets and their epoxy‐impregnated composites
Bibliographic record
Abstract
The thermal conductivity of bulk, self‐supporting boron nitride nanotube (BNNT) sheets composed of nominally 100% BNNTs oriented randomly in‐plane was measured by a steady‐state, parallel thermal conductance method. The sheets were either collected directly during synthesis or produced by dispersion and filtration. Differences between the effective thermal conductivities of filtration‐produced BNNT buckypaper (∼1.5 W m−1 K−1) and lower‐density as‐synthesized sheets (∼0.75 W m−1 K−1), which are both porous materials, were primarily due to their density. The measured results indicate similar thermal conductivity, in the range of 7–12 W m−1 K−1, for the BNNT network in these sheets. High BNNT‐content composites (∼30 wt.% BNNTs) produced by epoxy impregnation of the porous BNNT network gave 2–3 W m−1 K−1, more than 10× the baseline epoxy. The combination of manufacturability, thermal conductivity, and electrical insulation offers exciting potential for electrically insulating, thermally conductive coatings and packaging. Thermal conductivity of free‐standing BNNT buckypaper, buckypaper composites, and related materials at room temperature.
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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".