Highly Thermoconductive, Thermostable, and Super‐Flexible Film by Engineering 1D Rigid Rod‐Like Aramid Nanofiber/2D Boron Nitride Nanosheets
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Polymer‐based thermal management materials have many irreplaceable advantages not found in metals or ceramics, such as easy processing, low density, and excellent flexibility. However, their limited thermal conductivity and unsatisfactory resistance to elevated temperatures (<200 °C) still prevent effective heat dissipation during applications with high‐temperature conditions or powerful operation. Therefore, herein highly thermoconductive and thermostable polymer nanocomposite films prepared by engineering 1D aramid nanofiber (ANF) with worm‐like microscopic morphologies into rigid rod‐like structures with 2D boron nitride nanosheets (BNNS) are reported. With no coils or entanglements, the rigid polymer chain enables a well‐packed crystalline structure resulting in a 20‐fold (or greater) increase in axial thermal conductivity. Additionally, strong interfacial interactions between the weaved ANF rod and the stacked BNNS facilitate efficient heat flux through the 1D/2D configuration. Hence, unprecedented in‐plane thermal conductivities as high as 46.7 W m −1 K −1 can be achieved at only 30 wt% BNNS loading, a value of 137% greater than that of a worm‐like ANF/BNNS counterpart. Moreover, the thermally stable nanocomposite films with light weight (28.9 W m −1 K −1 /10 3 (kg m −3 )) and high strength (>100 MPa, 450 °C) enable effective thermal management for microelectrodes operating at temperatures beyond 200 °C.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 it