FTIR and XPS study of the reaction of phenyl isocyanate and cellulose with different moisture contents
Bibliographic record
Abstract
Purpose To evaluate the competing reaction of isocyanate with cellulose and water which can provide direction for further studies on bonding and curing reactions of isocyanate with wood. Design/methodology/approach Two modern analytical techniques, Fourier transform infra‐red (FTIR) and X‐ray photoelectron spectroscopy (XPS), were used. The FTIR was used to identify the products of the reaction of phenyl isocyanate (PI) with alcohol, water, and cellulose; while the XPS was used to evaluate the proportions of isocyanate that reacted with water or cellulose when PI reacted with cellulose at different moisture contents (MCs), respectively. Findings Methods for the IR identifications of reaction results of PI with n‐propanol, water, and cellulose, in which the reactions of PI with water and PI with cellulose resulted in N,N′‐diphenylurea and carbamate, respectively, were developed. It was discovered that the extent of reaction of isocyanate and cellulose decreased with increasing cellulose MC, and 92.98 per cent isocyanate reacted with water when 9.78 per cent MC was reached. It was confirmed that the products of the PI reaction were distributed mainly on the surface of the cellulose particles. Research limitations/implications The study only focused on the reaction of PI. However, the industrial isocyanates, e.g. methylene diphenyl diisocyanate (MDI), polymerized methylene diphenyl diisocyanate (p‐MDI) that have complexities in chemical structures and components, make analyses with FTIR and XPS impossible. Practical implications The paper provides some instructive information about the isocyanate reaction that will help understanding the characteristics of isocyanate and guiding the design of technology bonding isocyanate to fibre, wood, etc. Originality/value The application of FTIR and XPS for evaluating the reaction of isocyanate with cellulose having different MCs was novel and may be used as a reference for other relevant studies.
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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) | 0.001 | 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".