Applied TEM Approach for Micro/Nanostructural Characterization of Carbon Nanotube Reinforced Cementitious Composites
Bibliographic record
Abstract
A novel colloidal technique for transmission electron microscopy (TEM) of graphitic nano-reinforced cementitious (GNRC) composites was developed. Single-walled and multiwalled nanotubes (SWNTs and MWNTs) were functionalized using an acid etching technique to obtain stable aqueous suspensions that were incorporated in the mix design of a cement paste. Effective functionalization was demonstrated by Raman spectroscopic measurements and time resolved dynamic light scattering measurements. The functionalized nano-reinforcement and binding characteristics were observed at the nanoscale for the first time using high resolution TEM imaging. Functionalized CNTs were found to be well distributed and preferentially associated with the cementitious matrix. This newly developed colloidal technique for TEM imaging of GNRC composites is a viable approach to characterize the interfacial compatibility between graphitic nano-reinforcement and cementitious matrices.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".