Physical and Chemical Mechanism for Increased Surface Area and Pore Volume of CaO in Water Hydration
Bibliographic record
Abstract
The present work explores the fundamental mechanism behind the increased surface area and pore volume of CaO after hydration. First, a widely believed mechanism, the “physical attrition theory”, is experimentally examined and is found to have limitations in explaining this phenomenon. Next, to explain the improvement of morphological properties by hydration, a typical water hydration process is examined by dividing the process into four independent chemical and physical substeps. The morphological changes of Ca(OH) 2 and its derived CaO by each substep are measured by Brunauer–Emmett–Teller (BET) analysis. During the first step, the intrinsic chemical conversion from CaO to Ca(OH) 2, the formed Ca(OH) 2 product layer disintegrates because of its low tensile strength and weak crack resistance, which explains the increases in surface area and pore volume by steam/moisture hydration as well as the rapid heat release during hydration. The physical interaction with water (the second step) slightly decreases the surface area and pore volume, possibly by lodging microparticles into the porous structure of bigger particles and inducing stronger particle agglomeration. The Ca(OH) 2 solid can further chemically bond water molecules (the third step), which significantly enlarges the solid volume during water-bonding and consequently generates a more porous structure during dehydration. The final precipitation of the dissolved Ca(OH) 2 (the fourth step) decreases the solid’s surface area and pore volume. This decrease is attributed to the formed microparticles from solution, which can plug some surface pores on the larger particles during the drying process.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".