Effect of Mg on xonotlite structure and stability
Bibliographic record
Abstract
Minor constituents such as clays or dolomite might be present in the raw materials used for the synthesis of xonotlite (Ca 6 Si 6 O 17 (OH) 2 ). These impurities can introduce additional elements (e.g., Mg, Al, Fe) into the system, affecting the purity of xonotlite, or promoting the formation of secondary phases. This study focuses on the influence of MgO on the formation and stability of xonotlite. A combination of solubility experiments conducted at 7, 20, 50 and 80 °C, along with thermodynamic modelling and atomistic simulations, was employed to investigate Mg incorporation. Structural and phase characterization was performed using XRD, TGA, FT-IR, SEM and 29 Si MAS-NMR. Up to 13 mol% of Mg can be incorporated into the xonotlite structure and the derived thermodynamic properties indicate that this leads to a stabilization of xonotlite. Higher quantities of magnesium lead to a stabilization of other phases such brucite, which may compete with xonotlite crystallization.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".