Characteristics of Pyrolytic Graphite as a Neutron Monochromator
Bibliographic record
Abstract
Pyrolytic graphite (PG) has become nearly indispensable in neutron spectroscopy. Since the integrated reflectivity of the monochromatic neutrons from PG crystals cut along its c-axis is high within a wavelength band from 0.1 nm up to 0.65 nm. The monochromatic features of PG crystal is detailed in terms of the optimum mosaic spread, crystal thickness and reactor moderating temperature for efficient integrated neutron reflectivity within the wavelength band. A computer code Mono-PG has been developed to carry out the required calculations for the PG hexagonal close-packed structure. Calculation shows that, 2 mm thick of PG crystal having 0.30 FWHM on mosaic spread are the optimum parameters of PG crystal as a monochromator at selected neutron wavelength shorter than 0.2 nm. However, the integrated neutron intensity of 2nd and 3rd orders from a thermal reactor flux is even higher than that of the 1st order one at neutron wavelengths longer than 0.2 nm. While, from a cold reactor flux, the integrated neutron intensity of the 1st order within the wavelength band from 0.25 up to 0.5 nm is higher than the 2nd and 3rd ones.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".