Nucleation and Growth of Crystal on a Substrate Surface: Structure Matching at the Atomistic Level
Bibliographic record
Abstract
In natural systems, surface-induced nucleation and growth of minerals on heterogeneous substrates are common on the Earth’s surface and deep subsurface environments. In the synthesis of crystalline materials, different templates have been successfully employed to prepare materials with a specific shape or orientation, or to speed up the synthesis. The structure match between the developed crystals and the substrates plays an important role in initial nucleation. This chapter first presents an overview of the heterogeneous nucleation of crystals on different substrates with varying degrees of mismatch, including highly matched structures, low mismatch with similar lattice parameters, and mismatched interface structures. Then an example about heterogeneous nucleation on substrates with highly matched structures is introduced. First-principles molecular dynamics (FPMD) simulation reveals the complexation of bivalent heavy-metal cations on edge surfaces of 2:1 clay mineral, and the kinetic processes of initial epitaxial growth are further described in detail.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".