Quantitative measurements of phase transitions in nano- and glassy materials
Bibliographic record
Abstract
Novel approaches to the collection and treatment of total x-ray scattering using high energy (> 65 keV) x-ray beams and area detectors allow in situ studies of unprecedented precision to be performed on nano-crystalline ( n ) and glassy materials at extremes of pressure ( p ) and temperature (T). Gradual structural transitions in glasses, liquids and nano-materials occurring via continuous changes in density, or involving phases related by pseudo symmetry are inherently difficult to identify due to their disordered nature. In such cases supplementary physical measurements along with modeling of the pair distribution function (PDF) provide powerful constraints on the possible models for the transition. Examples include transitions from n -FeS with a mackinawite-like structure to high p forms with structures related to NiAs structure-type. The distinction between the various high p models – MnP-type, troilite, FeS-III related or mixtures of these phases – is subtle; great care needs to be exercised in refining structure models to fit the observed data. Acoustic techniques are particularly valuable in identifying high p phase transitions in glasses, since measured changes in compressional velocities relate to density changes in the glass while shear waves provide an insight into network rigidity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".