Thermal rectification in a polymer-functionalized single-wall carbon nanotube
Bibliographic record
Abstract
Thermal rectification occurs when heat current through a material is favored in one direction but not in the opposite direction. These materials, often called thermal diodes, have the potential to perform logic calculations with phonons. Rectification obtained with existing material systems is either too minor or too difficult to implement practically. Hence, we present a scheme to enable higher rectification using a single-wall carbon nanotube (SWCNT) that is covalently functionalized near one end with polyacetylene (PA) chains. This composite structure allows rectification R up to 204%, which is higher than the values reported for SWCNTs. Here, [Formula: see text], where [Formula: see text] and [Formula: see text] are the heat currents for forward and reverse bias, respectively. The interatomic interactions in the SWCNT-PA nanocomposite are nonlinear, i.e., they are anharmonic, which is a requirement for thermal rectification. Through atomistic simulations, we identify two additional conditions to accomplish thermal rectification at the nanoscale, namely, (1) structural asymmetry, and (2) that the influence of this asymmetry on thermal transport is temperature dependent. The optimum temperature difference to achieve the highest thermal rectification with the structure is 40-80 K.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".