Selected techniques in diamond anvil cell crystallography: centring samples using X-ray transmission and rocking powder samples to improve X-ray diffraction image quality
Bibliographic record
Abstract
The distinct X-ray transmission profile obtained by scanning a sample in a diamond anvil cell across a collimated X-ray beam is used to monitor sample displacement brought about by rotation. This measured displacement can in turn be used to calculate, and subsequently correct, the sample position with respect to a centre of rotation. This centring method differs from others also based on transmission in that it does not require a 180 degrees sample rotation, nor does it require prior positioning of the rotation axis in the path of the X-ray beam. After a full description of the method, an example is presented together with an extended record of use to evaluate the method in a practical setting. The practice and benefits of rocking polycrystalline samples during X-ray exposure have also been quantitatively examined. Changing the orientation of the sample grains with respect to the incident beam yields the expected result of a more homogeneous intensity distribution along Debye rings. Interestingly, by limiting the amount of time large grains assume a particular orientation, rocking brings about the added effect of significantly reducing detector saturation. Sample rocking yields more reliable relative intensities, a more appropriate line shape and narrower line width. Data are presented for a calibration standard at ambient pressure as well as a research sample at high pressure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".