Characterization and Micromilling of Flow Induced Aligned Carbon Nanotube Nanocomposites
Bibliographic record
Abstract
Carbon nanotube (CNT) based polymeric composites exhibit high strength and thermal conductivity and can be electrically conductive at a low percolation threshold. CNT nanocomposites with polystyrene (PS) thermoplastic matrix were injection-molded and high shear stress in the flow direction enabled partial alignment of the CNTs. The samples with different CNT concentrations were prepared to study the effect of CNT concentration on the cutting behavior of the samples. Characterizations of CNT polymer composites were studied to relate different characteristics of materials such as thermal conductivity and mechanical properties to micromachining. Micro-end milling was performed to understand the material removal behavior of CNT nanocomposites. It was found that CNT alignment and concentrations influenced the cutting forces. The mechanistic micromilling force model was used to predict the cutting forces. The force model has been verified with the experimental milling forces. The machinability of the CNT nanocomposites was better than that of pure polymer due to the improved thermal conductivity and mechanical characteristics.
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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".