Thermally Conductive and Electrical Insulation BNNS/CNF Aerogel Nano-Paper
Bibliographic record
Abstract
Adding heat conducting particles to a polymer matrix to prepare thermally conductive and electrical insulation materials is an effective approach to address the safety issues arising from the accumulation of heat in the working process of electronic devices. In this work, thermally conductive and electrical insulation nano-paper, consisting of Boron Nitride nano-sheet (BNNS) and cellulose nanofiber (CNF), was prepared using an aerogel 3D skeleton template method. For comparison, BNNS/CNF nano-paper was also produced using a simple blending method. At a BNNS loading of 50 wt%, the thermal conductivity of BNNS/CNF aerogel nano-paper and blended nano-paper at 70 °C are 2.4 W/mK and 1.2 W/mK respectively, revealing an increase of 94.4%. Under similar conditions, the volume resistivity of BNNS/CNF aerogel nano-paper and blended nano-paper are 4.0 × 1014 and 4.2 × 1014 Ω·cm respectively. In view of its excellent thermal conductivity and electrical insulation performance, therefore, BNNS/CNF aerogel nano-paper holds great potential for electronic-related applications.
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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".