Deterioration mechanism of adhesion properties of FRP–soil interface induced by moisture
Bibliographic record
Abstract
The deterioration of fiber-reinforced polymer (FRP)–soil interfacial adhesion due to water intrusion has been a core issue in geotechnical engineering, but its microscopic mechanism remains unclear. In this study, molecular dynamics (MD) simulation method is employed to reveal the microscopic deterioration mechanism of water on adhesion properties of epoxy–quartz (i.e., FRP–soil subsystem) interface, the structural and dynamic characteristics of interlayer water film. The steered molecular dynamics pulling simulation and the modified Bell's model are used to evaluate the adhesion energy of epoxy–quartz interface in dry and wet cases. The simulation results show that (1) the interfacial water film weakens adhesion strength of epoxy–quartz interface, playing a dual role in “interface isolation” and “lubrication”, aggravating the interfacial debonding. (2) The work of adhesion, maximum pulling force, potential of mean force, and adhesion energy of dry system are significantly higher than those of wet system. (3) The interlayer water film has a distinct layered structure: bound, free, and sparse water layers, which have different angle orientations and density distributions. (4) The diffusion coefficient increases with the rising thickness of free water layer, which may trigger a capillary-seepage effect and aggravate interface deterioration. This study provides atomic-scale insights into moisture-induced FRP–soil interface failure mechanism.
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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".