In‐situ temperature‐depth profile evaluation of South African unmineable coal seams to determine <scp> CO <sub>2</sub> </scp> sequestration potential
Bibliographic record
Abstract
Abstract This study aimed to investigate the sorption behaviour of South African coal seams with relation to the effect of temperature during CO 2 sequestration. The excess adsorption isotherms of CO 2 adsorption were undertaken using a high‐pressure volumetric system for four coals of different coal rank (denoted by Somkele [SK], anthracite KZN [AN], Tshikondeni [TD], and Syferfontein [SF]). The volumetric pressure step method was conducted at increments of system temperature of 35, 45, 55, and 65°C for pure CO 2 adsorption at incremental pressures up to 93 bar. The results showed that high temperatures have a very significant negative effect on the amount of CO 2 adsorbed on the coal samples. The high‐rank coal samples (SK and AN) demonstrated elevated CO 2 adsorption capacity across all tested temperatures due to their high vitrinite content. The medium‐rank coals (TD and SF) exhibited comparatively lower CO 2 adsorption capacity, attributed to the presence of adsorption hindrances such as higher ash content and volatile and mineral matter. The isosteric heat of adsorption revealed an increasing trend with coverage for all coal samples, with higher rank coals displaying greater slopes. The determined range of the isosteric heat of adsorption, spanning from 10 to 59 kJ/mol, indicated that the adsorption process is primarily of a physisorption nature. Three theoretical models (Langmuir, Freundlich, and Temkin) were evaluated and fitted to the sorption experimental data. The Temkin model exhibited superior fitting compared to the Langmuir and Freundlich isotherms. The Temkin isotherm parameters suggest that the adsorption of CO 2 onto coal is a physisorption process.
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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 | 0.001 | 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 | 0.000 |
| 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".