Atomistic simulations of nucleation and growth of CaCO<sub>3</sub> with the influence of inhibitors: A review
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Bibliographic record
Abstract
Abstract Calcium carbonate (CaCO 3 ) is a crucial mineral with great scientific relevance in biomineralization and geoscience. However, excessive precipitation of CaCO 3 is posing a threat to industrial production and the aquatic environment. The utilization of chemical inhibitors is typically considered an economical and successful route for addressing the scaling issues, while the underlying mechanism is still debated and needs to be further investigated. In this context, a deep understanding of the crystallization process of CaCO 3 and how the inhibitors interact with CaCO 3 nuclei and crystals are of great significance in evaluating the performance of scale inhibitors. In recent years, with the rapid development of computing facilities, computer simulations have provided an atomic‐level perspective on the kinetics and thermodynamics of possible association events in CaCO 3 solutions as well as the predictions of nucleation pathway and growth mechanism of CaCO 3 crystals as a complement to experiment. This review surveys several computational methods and their achievements in this field with a focus on analyzing the functional mechanisms of different types of inhibitors. A general discussion of the current challenges and future directions in applying atomistic simulations to the discovery, design, and development of more effective water‐scale inhibitors is also discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it