Evaluation of Theoretical Models for Determining Effective Thermal Conductivity and Interfacial Thermal Resistance of Carbon Nanotube Polydimethylsiloxane Nanocomposites
Bibliographic record
Abstract
Thermal conductivity is an important parameter for many industrial applications of nanocomposites. Carbon nanotube nanocomposites often have measured thermal conductivity well below expected values. Some models have been proposed that consider the unique structure of nanocomposites to predict their effective thermal conductivity. These models include the nanoparticles’ interfacial thermal resistance, aspect ratio, and volume fraction. In this work, the thermal conductivity of multiwalled carbon nanotube (MWCNT) polydimethylsiloxane nanocomposites has been studied and the thermal conductivity and interfacial thermal resistance in a polymer matrix have been estimated using suitable models. Nanocomposites made using CNTs with an aspect ratio <100 were found to be below the percolation threshold at 3.5% loading. In situ, the thermal conductivity of MWCNTs was estimated to be 412 ± 252 W m –1 K –1 and interfacial thermal resistance was estimated at an R K of 6.6 ± 0.3 × 10 –8 m 2 K W –1 .
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".