Study of the Influence of Na <sup>+</sup> and Mg <sup>2+</sup> on CaCO <sub>3</sub> Cluster Nucleation and Growth Based on ReaxFF Molecular Dynamics Simulations
Bibliographic record
Abstract
Understanding the nucleation and growth mechanisms of calcium carbonate (CaCO 3 ) in multicomponent aqueous environments is essential for regulating mineralization. Here, ReaxFF molecular dynamics simulations were employed to investigate the effects of Na + and Mg 2+ on CaCO 3 cluster formation. Unlike prior studies focusing on single-ion systems, we constructed Ca–Na–CO 3 –H 2 O and Ca–Mg–CO 3 –H 2 O systems to directly compare cation interference under 300 and 400 K. Results show that both Na + and Mg 2+ inhibit CaCO 3 nucleation, with Mg 2+ having a stronger effect by forming stable MgCO 3 clusters and competing for CO 3 2– . Na + exhibits weaker coordination and remains mostly unbound. Elevated temperature and Mg 2+ further reduce the formation of calcite-like structures. Scattering amplitude and structure factor analyses confirm that Na + and Mg 2+ induce less ordered and less compact cluster morphologies. This study highlights the value of atomistic simulations for probing ion-specific effects on nucleation, offering new insights into crystallization control in environmental and industrial applications.
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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) | 0.000 | 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".