Effects of Microstructure and Sample’s Surface to Volume Ratio on Pressure-Induced Nucleation and Transformation to Crystalline and Apparently Amorphous Solids
Bibliographic record
Abstract
Heterogeneous nucleation in a polycrystalline solid occurs (i) at the surface of its container, (ii) at its microstructural sites, namely, grain boundaries, grain junctions, and intergrain-strain regions, and (iii) at the defect sites, namely, dislocations, vacancies, and stacking faults (planar defects) in its single crystal grains. We analyze their thermodynamic and kinetic effects in terms of classical nucleation theory by taking into account (a) the increase in Gibbs free energy, G, due to the lattice misfit of the nuclei forming in the parent phase and (b) the decrease in G due to the angle subtended by the nucleus on the external surface, grain boundaries, and grain junctions. Hence we deduce that several combinations of nucleation sites in different materials and also in different polycrystalline samples of the same material may produce the same energy barrier against nucleation and overall growth. The overall nucleation and growth rates are dependent upon the surface to volume ratio, χ, of a sample in a vessel and the vessel’s material. Pressurizing a crystalline solid is known to produce either its polymorphic crystal form or a solid that shows no Bragg peaks and appears amorphous. We argue that when self-diffusion rate becomes slower than the pressurizing rate, (dP/dt)T, a multiplicity of states nucleating at different sites become kinetically frozen on their path to crystal growth. In such a case, the transformed solid would appear amorphous. A solid of high χ would transform to a polymorph when (dP/dt)T is low and to a state that appears amorphous when (dP/dt)T is high. Known studies of 0.08–0.1 cm3 volume samples in diamond-anvil high pressure cells provide qualitative evidence of formation of both crystal polymorphs and apparently amorphous solids. Methods are suggested for observing such an occurrence in large polycrystalline samples.
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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) | 0.000 | 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 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".