Analysis of kaolinite/chrysotile mixtures by ashing and x-ray diffraction
Bibliographic record
Abstract
A simple ashing procedure for a mixture containing kaolinite and chrysotile is described that converts kaolinite to amorphous metakaolinite while retaining the diffraction intensity of chrysotile. This ashing procedure removes the X-ray diffraction (XRD) pattern overlap between kaolinite and chrysotile that can interfere with the analysis of even high concentrations of chrysotile. Samples are ashed at 460 °C in a muffle furnace for 40 h to completely convert kaolinite to metakaolinite. The complete conversion of 1 g of kaolinite under these conditions was determined for two standard kaolinite samples from Georgia, KGa-1 and KGa-2. Two of the most common types of commercial chrysotile, long-fiber Canadian and short-fiber Californian chrysotile, are demonstrated to retain diffraction intensity after ashing at 460 °C. Both chrysotile samples have the same integrated intensity for the (002) reflection prior to ashing, although the peak breadths for the two samples are quite different. Ashing at 480 and 500 °C reduces the diffraction intensities of both chrysotile samples by 15%, and broadens the peaks by approximately 3%. Using the prescribed ashing procedure and x-ray diffraction with an internal corundum standard, two kaolinite-bearing building materials containing chrysotile near 0.01 mass fraction were analyzed. The ashing procedure has additional advantages in reducing some samples to powders and removing volatile components, thereby eliminating some sample preparation procedures and concentrating any chrysotile present in the sample. The removal of volatile components improves the sensitivity of XRD analysis to concentrations below 0.01 mass fraction chrysotile.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".