An overview of conversion of residues from coal liquefaction processes
Bibliographic record
Abstract
Abstract Direct coal liquefaction (DCL) is a process for converting coal to synthetic oils, which can be refined to make transportation fuels. Residue from this process contains inorganic material such as mineral matter originating from the coal and catalysts, and organic matter such as unconverted coal, heavy oils, pre‐asphaltenes and asphaltenes. The conversion of these DCL residues to lighter, high‐value products is an important step in helping to make this technology both commercially viable and environmentally acceptable. This paper provides an overview of the physico‐chemical characteristics and processing options available for coal liquefaction residues and compares and contrasts them to those of petroleum residues. Residue properties vary considerably, since they are highly dependent on feed coal, process configuration and operating conditions. Determination of composition and structural parameters of products derived from residue conversion can help determine their stability, coking and solvent hydrogen donating ability. Thermal conversion processes such as visbreaking and gasification offer the greatest promise for handling these heavy materials. The conversion chemistry, reactivity and kinetics of residue gasification are not well‐understood but are important in optimising hydrogen production for the process. The literature has been comprehensively reviewed to provide characteristics and properties of residues and their potential for conversion. In addition, the potential for producing high‐value carbon products from residues is briefly discussed.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".