Synthesis of nanostructured titanium carbide ( <scp>TiC</scp> ) from bitumen coke by mechanical alloying process
Bibliographic record
Abstract
Abstract This study explored synthesizing titanium carbide (TiC) from bitumen coke using mechanical alloying. Initially, raw bitumen coke (5.9 wt.% sulphur) from delayed coking was desulphurized to produce low sulphur coke with a sulphur content of 0.2 wt.% for comparison purposes. Both high and low sulphur coke samples were mechanically alloyed with titanium (Ti) powder in a planetary ball mill under various conditions (milling time, milling speed, and ball‐to‐material ratios [BMR]). TiC was successfully produced from both high sulphur and low sulphur coke samples. The formation of TiC was confirmed by X‐ray diffraction (XRD) analysis. The effects of the experimental parameters on the production of TiC were evaluated. The experimental results showed that the high sulphur coke and Ti were converted into TiC after 10 h milling, whereas the low sulphur coke and Ti were converted into TiC much faster (after 5 h milling) at the same milling speed and BMR. Under the same milling time and BMR, the high sulphur coke and Ti were converted into TiC at 400 rpm, whereas the low sulphur coke and Ti were converted into TiC at 300 rpm. In addition, the high sulphur coke and Ti were converted into TiC when the BMR was 60:1, and the low sulphur coke and Ti were converted into TiC when the BMR was 40:1 under the same milling time and speed. Overall, preliminary results suggest that the conversion of low sulphur coke samples is easier and requires less energy to produce TiC compared to the high sulphur coke samples.
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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".