Synthesis and characterization of bio-based polyurethanes
Bibliographic record
Abstract
Hybrid polyurethanes are commonly made by reacting two chemical building blocks: a polyol and diisocyanate, followed by end-capping with appropriately functionalized silanes to permit moisture curing.This project aims to provide a framework to fully characterize an industrial sealant resin, before incorporating bio-based polyols and isocyanates into the original formulation.The original formulation is derived from petroleum-based monomers.By substituting bio-based molecules in the place of both building blocks, the resulting commercial product will have a higher renewable content.In recent years, finding bio-based alternatives for petroleum products has become a focus of research and industrial efforts in order to decrease petroleum consumption.The industrial partner's (Adfast Corp.) original product was replicated on a small scale and benchmarks for the molecular weight, viscosity, and stress-strain properties were determined.Gel permeation chromatography (GPC) was used to evaluate and compare the molecular weight distributions of multiple resins.Knowing the molecular weight distribution permitted the elucidation of the relationship between the molar ratio of diisocyanate to polyol in terms of chain length (dimer, trimer formation etc.).Once the original resin was fully characterized, three different bio-based polyols were selected and substituted in place of the original petroleum-based polyol.These new formulations were tested in the same manner as the original formulation, and the molecular weight distributions, viscosities, and stress-strain properties were compared.Of the three polyurethanes produced using bio-based polyols, one, using the commercial Myrinol DG-110 polyester polyol, showed promising physical properties: having high elasticity and tensile strength.This formula was then further optimized by the incorporation of a bio-based isocyanate: L-lysine diisocyanate.The properties of this final resin were measured and compared to the original petroleum-based product.It was found that by incorporating the bio-based isocyanate, the physical properties of the PU became more similar to Adfast's original resin.With additional testing (scale-up, adhesion testing, UV stability etc.) and optimization there is potential to have partial and fully bio-based polyurethanes incorporated into Adfast's product line.This project has opened doors for Adfast and McGill to pursue different avenues in order to develop a competitive, commercial bio-sourced product.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 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".