Synthesis of biobased phenolic resins/adhesives with methylolated wood‐derived bio‐oil
Bibliographic record
Abstract
Abstract Bio‐oil from the hydrothermal liquefaction of Eastern White Pine (Pinus strobus L.) sawdust was methylolated with formaldehyde in the presence of sodium hydroxide. The obtained methylolated bio‐oil (MB) was used to synthesize methylolated bio‐oil–phenol formaldehyde (MBPF) resol resins with a phenol substitution ratio of up to 75 wt %. All of the resins were used as wood adhesives for the production of a three‐layered plywood. The MBPF resol resins were comprehensively characterized for their physical, chemical, thermal, and mechanical properties (e.g., viscosity, nonvolatile content, shelf life, free formaldehyde level, molecular weight and distribution, curing temperature, bonding strength) when used as plywood adhesives. All of the MBPF resins contained similar nonvolatile contents as the reference pure phenol formaldehyde (PF) resin but had higher viscosities and shorter shelf lives, depending on the amount of MB in the MBPF. All of the MBPF resins displayed a lower curing temperature than the reference PF resin, with the main curing peak around 140°C, which was similar to that of the pure PF resin. According to thermogravimetric analysis, the methylolation treatment of bio‐oil improved the thermal stability of the MBPF resins compared to the bio‐oil–PF resol resins, which used untreated bio‐oil. The dry/wet bonding strengths of the plywood specimens glued with the MBPF resol resins with up to 60 wt % phenol substitution exceeded or were comparable to those of the conventional PF resol resin. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012
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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) | 0.001 | 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".