Development of hydrolysed protein-based plywood adhesive from slaughterhouse waste: effect of chemical modification of hydrolysed protein on moisture resistance of formulated adhesives
Bibliographic record
Abstract
Specified risk materials (SRM) constitute the proteinaceous waste of slaughterhouses and are currently being disposed off either by incineration or by land filling. Over the last few years, our efforts have focused on developing technology platforms for deployment of this renewable resource for various value-added industrial applications. This report describes a technology for utilization of SRM for the development of an environmentally friendly plywood adhesive with an improved water resistance property. The feedstock (SRM) was first thermally hydrolysed according to a standard protocol, and the hydrolysed protein fragments (peptides) were recovered from the hydrolysate. The recovered peptides were chemically modified through esterification reaction using ethanol, and then chemically crosslinked with polyamideamine-epichlorohydrin (PAE) resin to develop a wood adhesive system. Plywood specimens were then developed using the peptides-PAE resin-based adhesive. The effects of crosslinking time, solid content of the adhesive formulation, ratio of peptides and crosslinking agent in the formulation, and curing conditions of specimen preparation on lap shear strength of resulting plywood specimens were systematically evaluated. Despite the hydrophilic nature of hydrolysed protein fragments, the peptides-PAE resin formulations exhibited remarkable water resistance property after curing. Capping of polar carboxyl groups of peptides by converting them to esters further improved the water resistance property of this adhesive system. Under the optimum conditions of adhesive preparation and curing, the ethyl ester derivative of peptides and PAE resin-based formulations resulted in plywood specimens having comparable dry as well as soaked shear strengths to those of commercial phenol formaldehyde resin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".