Oxidative Coal Dissolution a Systematic Study
Bibliographic record
Abstract
The coal industry in Canada boasts abundant reserves, with significant potential for value addition through innovative processes. Oxidative coal dissolution (OCD) emerges as a promising method to generate high-value products from coal, using air as the oxidant, making it a cost-effective and environmentally favorable approach. This thesis focuses on evaluating the impact of critical operating parameters on OCD, seeking to enhance its efficiency and product selectivity for large-scale applications. The research started with a comprehensive overview of coal composition, ranks, and properties, followed by an exploration of the oxidation process itself. The study narrows down the scope to oxygen in air as the oxidant and explores the engineering challenges associated with OCD, including different operating parameters such as oxidant type, oxidant availability, temperature, time, water-to-coal ratio, and pH control. An initial set of experiments at atmospheric pressure with temperatures up to 95 °C revealed that OCD at low temperatures has limited carbon yield to liquid products. To overcome this, OCD reactions at elevated pressures of 5 MPa and temperatures ranging from 90 to 180 °C were conducted. These conditions significantly improve carbon yield to liquid products, providing a better understanding of carbon conversion and product distribution. However, overoxidation remains a challenge at higher temperatures and pressures, leading to increased carbon conversion to gaseous products. To address this issue, further experiments at 1 MPa pressure at same temperature range were performed, improving carbon selectivity to liquid products, though at the cost of decreased yield. It was found that the optimal selectivity and yield towards liquid products occur at 150 °C, Additionally, an unexpected increase in heating value was observed in the residue product after OCD reactions at 90 °C, contradicting conventional expectations. To explore this phenomenon further, additional reactions were conducted using nitrogen instead of air, revealing that the decrease in the oxygen-to-carbon molar ratio responsible for the heating value increase is not solely attributed to the oxidative coal dissolution process. Instead, a hypothesis suggests that under specific reaction conditions, a portion of initially bonded oxygen within the coal molecule is liberated, possibly promoting the exudation of oxygen-rich organic compounds from the coal porous structure.
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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) | 0.000 | 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".