On the computation of diffraction peaks from discrete defects in continuous media: comparison of displacement and strain-based methods
Bibliographic record
Abstract
This study introduces a numerical tool to generate virtual diffraction peaks from known elastic displacement or strain fields arising in the presence of discrete straight or curved dislocations in continuous media. The tool allows for the generation of diffraction peaks according to three methods: the displacement-based Fourier method of Warren, the Stokes–Wilson approximate method and a new average-strain-based Fourier method. The trade-off between the accuracy and the demand for computational power of the three methods is discussed. The work is applied to the cases of single-crystal microstructures containing (i) straight dislocations, (ii) low-angle symmetric tilt grain boundaries, (iii) a restrictedly random distribution of dislocations and (iv) complex microstructures generated by discrete dislocation dynamics, to illustrate the differences and domains of validity of the aforementioned methods. Dissimilar diffraction profiles reveal that peak broadening from dislocated crystals has additional contributions coming from strain gradients – a feature that is rejected in the Stokes–Wilson approximation. The problem of dealing with multi-valued displacement fields faced in the displacement-based Fourier method is overcome by the new average-strain-based Fourier method.
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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 | 0.001 | 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".