Atomistic and mesoscale simulation of sodium and potassium adsorption in cement paste
Bibliographic record
Abstract
An atomistic and mesoscopic assessment of the effect of alkali uptake in cement paste is performed. Semi-grand canonical Monte Carlo simulations indicate that Na and K not only adsorb at the pore surface of calcium silicate hydrates (C-S-H) but also adsorb in the C-S-H hydrated interlayer up to concentrations of the order of 0.05 and 0.1 mol/kg, respectively. Sorption of alkali is favored as the Ca/Si ratio of C-S-H is reduced. Long timescale simulations using the Activation Relaxation Technique indicate that characteristic diffusion times of Na and K in the C-S-H interlayer are of the order of a few hours. At the level of individual grains, Na and K adsorption leads to a reduction of roughly 5% of the elastic moduli and to volume expansion of about 0.25%. Simulations using the so-called primitive model indicate that adsorption of alkali ions at the pore surface can reduce the binding between C-S-H grains by up to 6%. Using a mesoscopic model of cement paste, the combination of individual grain swelling and changes in inter-granular cohesion was estimated to lead to overall expansive pressures of up to 4 MPa-and typically of less than 1 MPa-for typical alkali concentrations observed at the proximity of gel veins caused by the alkali-silica reaction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".