Poly(3,4-epoxycyclohexylmethyl acrylate) Synthesis and Use in the Preparation of an Exceptionally Hard yet Flexible Organic Polymer Coating
Bibliographic record
Abstract
Despite the commercial availability of 3,4-epoxycyclohexylmethyl acrylate (ECMA), its homopolymerization is not reported. In this study, liquid viscous poly(3,4-epoxycyclohexylmethyl acrylate) (PECMA) is synthesized via free radical polymerization and fractionated to obtain samples with varying molecular weights. After casting with a cationic photoinitiator and photocuring of the resultant film to cross-link the epoxide groups via ring-opening polymerization, a hard solid coating is formed. For fully cured coatings, hardness ( H ) increases with the molecular weight of PECMA. At a weight-average molecular weight ( M w ) of 14.5 kDa, the H value of the fully cured coating reached 0.78 ± 0.02 GPa, over five times that of poly(ethylene terephthalate) (PET) and three times that of polystyrene (PS), representing the highest H value reported for an organic material. This exceptional hardness correlates with excellent wear resistance, as no wear tracks are observed after 250 abrasion cycles with steel wool under 13 kPa. The coating also exhibits high transparency, with 97% transmittance at 500 nm for a 50 μm-thick film, and remains thermally stable up to 300 °C. These properties indicate that PECMA holds significant potential for diverse 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) | 0.001 | 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) | 0.002 | 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".