Use of biocrude derived from woody biomass to substitute phenol at a high‐substitution level for the production of biobased phenolic resol resins
Bibliographic record
Abstract
Abstract Phenolic bio‐oil produced by the direct liquefaction of Eastern white pine (Pinus Strobus L.) sawdust in a hot‐compressed ethanol‐water (1:1 w/w) medium at 300 °C was used to partially substitute for phenol in the synthesis of bio‐oil‐phenol‐formaldehyde (BPF) resol resins. Bio‐based resol resins with high levels of phenol substitution (up to 75 wt%) could be used as plywood adhesives because of the low molecular weights found for the phenolic bio‐oil (weight‐average molecular weight = 1072 g/mol, number‐average molecular weight = 342 g/mol). The properties of the BPF resol resins were analyzed by differential scanning calorimetry, Fourier transform infrared spectroscopy, gel permeation chromatography, and thermogravimetric analysis. All of the experimental BPF resins possessed broad molecular weight distributions but had similar chemical/thermal properties compared to a conventional phenol–formaldehyde (PF) resol resin reference (or 0 wt % BPF resin). The BPFs exhibited the typical properties of a thermosetting PF resin, for example, an exothermic curing temperature of 140–150°C and an acceptable residual carbon yield of 48–72 wt % nonvolatile content at 700°C. The experimental BPFs were applied as adhesives in the assembly of plywood, and then, the dry/wet tensile strengths were evaluated. The tensile strengths of the dry plywood samples bonded with the BPF resins up to a high ratio value of 75 wt % bio‐oil exceeded or were comparable to that of the conventional pure PF resin adhesive. All of the BPF‐resin‐bonded plywood samples gave wet tensile strengths comparable to those of the conventional PF adhesive. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 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) | 0.001 | 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 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".