Impact of raw material on thermo‐physical properties of carbon foam
Bibliographic record
Abstract
Abstract Carbon foam materials are currently used in several industrial and engineering applications due to their outstanding properties. The properties of carbon foam can be altered through the manufacturing processes applied in specific applications. In this paper, we collected and analyzed four samples manufactured by CFOAM and one sample developed by Ohio University (OU) to understand the behaviour of this material and determine its properties. We utilized advanced techniques to experimentally measure and determine the following properties: pore size and volume, porosity, specific surface area, mass, density, and thermal conductivity. Among the samples, the low‐porosity CFOAM (CF35) and the OU sample exhibited higher specific surface areas and densities compared to the others. However, CF35 demonstrated the highest thermal conductivity, while OU displayed the lowest. As a result, CF35 emerges as the optimal choice for applications requiring high‐rate heat transfer, while the remaining CFOAM samples are well‐suited for lightweight applications. Thus, OU foam proves to be a highly suitable candidate for insulation applications such as building sidewalls.
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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 | 0.000 | 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) | 0.000 | 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".