Anisotropic Deformation in a Polymer Slab Subjected to Fluid Adsorption
Bibliographic record
Abstract
Nanoporous adsorbents can mechanically swell or shrink once upon the accumulation of guest fluid molecules at their internal surfaces or in their cavities. Existing theories in this field attribute such sorption-induced swelling to a tensile force, while shrinkage is always associated with a contractive force. In this study, however, we propose that the sorption-induced deformation of a porous architecture is not solely dictated by the stress conditions but can also be largely influenced by its mechanical anisotropy. In more detail, the sorption-induced deformation of a polymeric slab is investigated using a hybrid molecular dynamics and Monte Carlo algorithm. When subjected to water loading, the slab is found to swell along its normal direction and display an overall positive volumetric strain. Moreover, the surface roughness is enhanced as a response to the surface energy decrease induced by the water covering the slab external surface. Unexpectedly, the in-plane deformation of the slab material seems to be highly constrained, so that it is far below its normal counterpart. This anisotropy is enhanced when the slab thickness decreases. With a thickness of around 1.35 nm, an in-plane shrinkage is observed throughout the entire hygroscopic range. A theoretical analysis based on a poromechanical model suggests that the anisotropic mechanical properties, which are common for a slab material, are the essence of the constrained in-plane swelling or even shrinkage under the isotropic sorption-induced tensile forces. This study, unveiling overlooked mechanisms of sorption-induced shrinkage in mechanically anisotropic materials, provides new insights into this field.
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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".