Analysis of a silicon comb structure using an inverse Talbot–Lau neutron grating interferometer
Bibliographic record
Abstract
We describe an inverse Talbot-Lau neutron grating interferometer that provides an extended autocorrelation length range for quantitative dark-field imaging. To our knowledge, this is the first report of a Talbot-Lau neutron grating interferometer (nTLI) with inverse geometry. We demonstrate a range of autocorrelation lengths (ACL) starting at low tens of nanometers, which is significantly extended compared to the ranges of conventional and symmetric setups. ACLs from a minimum of 44 nm to the maximum of 3.5 μm were presented for the designed wavelength of 4.4 Å in experiments. Additionally, the inverse nTLI has neutron-absorbing gratings with an optically thick gadolinium oxysulfide (Gadox) structure, allowing it to provide a visibility of up to 52% while maintaining a large field of view of approximately 100 mm × 100 mm. We demonstrate the application of our interferometer to quantitative dark-field imaging by using diluted polystyrene particles in an aqueous solution and silicon comb structures. We obtain quantitative structural information of the sphere size and concentration of diluted polystyrene particles and the period, height, and duty cycle of the silicon comb structures. The optically thick Gadox structure of the analyzer grating also provides improved characteristics for the correction of incoherent neutron scattering in an aqueous solution compared to the symmetric nTLI.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".