Thermal Conductivity of Bentonite Grout Containing Graphite or Chopped Carbon Fibers
Bibliographic record
Abstract
The effectiveness of chopped carbon fibers to enhance the thermal conductivity of bentonite-based grout was examined. Fibers of 3 mm and 150 μm in length were added to sodium bentonite and silica sand mixtures at different volumetric concentrations. The thermal conductivity of the resulting composite material was then measured using a non-steady-state needle probe technique. The conductivities of the fibrous materials were compared to bentonite and sand mixtures containing natural flake graphite and milled, compressed exfoliated graphite at corresponding volumetric concentrations. The resulting conductivities for all tested materials increased with the volumetric fraction of additive. However, the 3-mm carbon fibers were more effective as compared to either granular graphite; at a volume fraction of 0.68% the 3-mm fibers were approximately twice as effective as either form of graphite.
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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".