Liquefaction of corn distillers dried grains with solubles (DDGS) in hot-compressed phenol
Bibliographic record
Abstract
The present work aims to liquefy corn Distillers Dried Grains with Solubles (DDGS), a by-product in corn ethanol production, to produce liquid products as a potential substitute for petroleum-derived phenol or an additive in the manufacturing of phenolic resins. Efficient liquefaction of DDGS has been realized with hot-compressed phenol at 200-450°C. Effects of liquefaction temperature, initial phenol/DDGS ratio (wt/wt), residence time, and catalysts on yields of liquefaction products, as well as characterizations of typical liquid and solid products, have been investigated. The yield of liquid products increased with temperature, while it peaked at around 300°C, due to condensation/cracking reactions of the liquid intermediates/products to form solid products (i.e., coke/char) at temperatures higher than 300°C. The liquid yield increased monotonically with the initial phenol/DDGS ratio for a specified treatment time and temperature. An increased residence time generally produced a lower yield of liquid products, and a higher yield of solid residue, which was likely due to the increased coke/char formation from liquid products for a prolonged residence time. The yield of liquid products reached a maximum of 97 wt% at 300°C for 5 min-operation with Phenol/DDGS of 2/1. K2CO3, Rb2CO3, and NaOH were found very effective catalysts for enhancing the liquid yields. The use of these catalysts resulted in a 25% relative increase in the liquid yields for 5 minute operation with Phenol/DDGS of 1/1 at 300°C.
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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 | 0.000 | 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 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".