Optical Spectroscopy of Crystal Nucleation One Nucleus at a Time
Bibliographic record
Abstract
Crystallization is an important process in a wide range of disciplines from fundamental science to industrial application. Despite the importance of controlling the crystallization and its morphology (e.g. polymorphism), the lack of microscopic description of crystal nucleation often limits the rational approach to its engineering and control. The biggest challenge to experimentally track the nucleus formation is the stochastic and heterogeneous nature of the nucleation occurring at nanometer scale. To overcome this challenge, we developed a method we call “Single Nucleus Spectroscopy” or SNS and use it to follow the formation of single crystal glycine nucleus by Raman spectroscopy at 46 ms time resolution. The spectral evolution was analyzed by non-supervised spectral decomposition algorithm which unraveled the Raman spectrum of prenucleation aggregates. In order to gain microscopic insights into the structure of these aggregates we have established a direct comparison between the experiments and theoretical works. The outcome of our analysis is a new hypothesis of glycine crystal nucleation mechanism.
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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 | 0.000 |
| 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 | 0.001 |
| 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".