DEVELOPMENT OF CONTINUOUS SOLVENT EXTRACTION PROCESSES FOR COAL DERIVED CARBON PRODUCTS
Bibliographic record
Abstract
This NETL sponsored effort seeks to develop continuous technologies for the production of carbon products, which may be thought of as the heavier products currently produced from refining of crude petroleum and coal tars obtained from metallurgical grade coke ovens. This effort took binder grade pitch, produced from liquefaction of West Virginia bituminous grade coal, all the way to commercial demonstration in a state of the art arc furnace. Other products, such as crude oil, anode grade coke and metallurgical grade coke were demonstrated successfully at the bench scale. The technology developed herein diverged from the previous state of the art in direct liquefaction (also referred to as the Bergius process), in two major respects. First, direct liquefaction was accomplished with less than a percent of hydrogen per unit mass of product, or about 3 pound per barrel or less. By contrast, other variants of the Bergius process require the use of 15 pounds or more of hydrogen per barrel, resulting in an inherent materials cost. Second, the conventional Bergius process requires high pressure, in the range of 1500 psig to 3000 psig. The WVU process variant has been carried out at pressures below 400 psig, a significant difference. Thanks mainly to DOE sponsorship, the WVU process has been licensed to a Canadian Company, Quantex Energy Inc, with a commercial demonstration unit plant scheduled to be erected in 2011.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".