Semi-intrinsic self-healing epoxy coating using ionic liquid and super absorbent polymer
Bibliographic record
Abstract
In recent years, there has been a growing interest in self-healing materials due to their capacity to mend micro to nano-scale damages, enhancing longevity and reducing maintenance costs associated with equipment repair. This study introduces a self-healing epoxy-based polymeric coating achieved through the incorporation of a reversible ionic liquid (IL) network and a superabsorbent polymer (SAP) in a straightforward one-pot blending process. The reversible interaction between the hydroxyl groups of epoxy and ionic groups initiates the healing process under dry conditions. Moreover, the addition of SAP enhances the system's ability to initiate healing in wet and moist environments. Evaluation of the healing capability through SEM images reveals complete healing after 14 h in dry conditions and 24 h in wet conditions. Additionally, a series of physical and thermal tests were conducted to assess the effects of increasing IL concentration and curing agent in the epoxy system. For instance, the modified sample with 8 % weight of IL exhibited a 63 % higher elongation break compared to pure epoxy. It is believed that this straightforward one-pot composition holds significant potential for various applications, including the construction and automotive industries. • One-pot self-healing epoxy produced with ionic liquid and super absorbent polymers. • Total healing achieved in 14 and 24 h in dry and wet conditions, respectively. • Tensile strength enhanced and hardness reduced with added curing agents. • Repeatable healing and improved stability were demonstrated at moisture conditions. • Potential applications of self-healing epoxy are in buildings and automotives.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".