Fate\nof Mercury in Volatiles and Char during in Situ\nGasification Chemical-Looping Combustion of Coal
Bibliographic record
Abstract
Mercury emission is an important\nissue during <i>in-situ</i> gasification chemical-looping\ncombustion (<i>i</i>G-CLC)\nof coal. This work focused on experimentally “isolating”\ntwo elementary subprocesses (coal pyrolysis and char gasification)\nduring <i>i</i>G-CLC of coal, identifying mercury distribution\nwithin the two subprocesses, and examining the effects of a hematite\noxygen carrier (OC) on the mercury fate. The mercury measurement accuracy\nwas carefully ensured by comparing online measurements (by a VM 3000\ninstrument) and benchmark measurements (by the standard Ontario Hydro\nMethod, ASTM D6784) as well as repeated tests (10 times for each case).\nThe mercury mass balance was 115% for the entire <i>i</i>G-CLC. A total of 44.7% of the mercury was released as the gas phase\nform within the coal pyrolysis process at a typical CLC operation\ntemperature (950 °C), whereas 13.4% was released during the char\ngasification process. The release rate and amount of mercury were\nminimally affected by the presence of OC; however, the OC promoted\nthe conversion of Hg<sup>0</sup>(g) to Hg<sup>2+</sup>(g). Only a\nsmall amount of mercury was absorbed by the OC and transported into\nthe air reactor along with carbon residue, released as Hg<sup>0</sup>(g) and Hg<sup>2+</sup>(g) or remained in the OC and coal ash as\nparticulate mercury.
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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) | 0.001 | 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 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".