Bibliographic record
Abstract
Recent research attention has focused on soybean-based adhesives because of increased phenolic resin prices and adhesive demand. This study was conducted to investigate the adhesive properties of crosslinked soy flour and/or soy hydrolyzate with phenol-formaldehyde (PF) resins for use in structural panels. Neutral phenolic soy (NPS) and alkaline phenolic soy (APS) resins were prepared and used to bond southern pine plywood. Adhesive bond quality of the soybean-based phenolic resins was evaluated by glueline shear test following the procedure detailed in Product Standard PS 1-95 for construction and industrial plywood. Within the range of variable levels investigated, the following conditions produced higher wet wood failure than a control glue mix. For NPS resins best results were obtained with a 160 cps PF, a 30 minute assembly time, and no extender. For APS resins best results were obtained with a 50 cps PF, a 200°C press temperature, 19% corn-cob powder, and a 60 minute assembly time. Comparable results were obtained with either a 40% or 50% PF level in the resins. Under these conditions, the wet wood failure of plywood bonded with both resins approached the requirement of PS 1-95 for construction and industrial plywood. The APS resins were also used to fabricate homogeneous hybrid poplar flakeboards with different resin solid levels (5%, 7%, and 9%), press temperatures (175 and 200°C), and press times of 8 and 10 minutes. Internal bond strength, wet modulus of rupture, and dimensional stabilities of flakeboard improved with increased press time, press temperature, and PF level in the resins. In particular, increased press time can be used to offset the poor internal bonding associated with high resin content and the excessive moisture present in the mat. However, APS resin-bonded flakeboards provided higher mechanical and better dimensional stability properties compared to the Canadian Standard Association O437 standard, except for modulus of elasticity, which could be easily improved by flake alignment. Optimum production condition for flakeboard bonded with the APS resins are a 5% resin level, a 50% PF level, a 200°C press temperature, and an 8 minute press time. Although NPS and APS resins can be competitive with other conventional adhesives, further improvements are required to reduce press times for industrial applications.
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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) | 0.003 | 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".