Transport of water and oxygen in epoxy-based coatings
Bibliographic record
Abstract
Epoxies are used in various industrial applications as corrosion barriers but quantitative time-dependent predictions of their ability to mitigate corrosion attack at the metal/coating interface remain elusive. Permeability data for water and oxygen through epoxy-based coatings are of particular interest because the coating’s barrier performance in humid environments is directly related to how quickly these reactants get to the metal/coating interface. There is, however, an absence of literature data to explain oxygen transport within coatings in the presence of condensed water and its associated plasticization effects. We show that water is a dominant player in the barrier performance of epoxy coatings because it blocks the transport of other permeants. Through analysis of the sorption isotherms and empirical permeation data, we determined adjustable parameters that explain water vapor plasticization effects in fusion bonded epoxy (FBE) at 65°C. At this temperature, evolution of cavity formation and break-up of water clusters result in high mobility of water molecules inside the epoxy network. We also modeled oxygen transport through FBE in wet-state conditions based on time lag measurements, and with reported literature data on vapor and gas sorption in epoxy. In a mixed gas/vapor system, condensed water in FBE blocks and/or significantly decreases gas permeation in the coating. If the service temperature is low (less than 40°C), water immobilizes the oxygen gas within microvoid regions in the glassy epoxy. Our experimental measurements, combined with Freeman’s theoretical model for upper bound limits, showed that this water-induced blocking mechanism is sufficient to suppress corrosion reactions on the underlying substrate material. At 65°C and above, the synergistic effect of coating plasticization by water molecules and dissolution of oxygen in a mobile water phase results in significant gaseous transport. We applied mathematical models based on proven sorption and transport models to FBE free-standing films and derived adjustable parameters to quantitatively explain this competitive permeation. Our O2 transport data show that, compared to the single-layer FBE, epoxy-based coatings with additional polyolefin layers can improve the barrier performance by deprivation of micropore channels for gas transport.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".