Ptychography at the carbon K-edge
Bibliographic record
Abstract
Abstract Ptychography is a coherent diffraction imaging technique that measures diffraction patterns at many overlapping points on a sample and then uses an algorithm to reconstruct amplitude and phase images of the object and probe. Here, we report imaging, spectroscopy and linear dichroism ptychographic measurements at the carbon K-edge. This progress was achieved with a new generation of scientific Complementary Metal Oxide Semiconductor (sCMOS) X-ray cameras with an uncoated image sensor which has fast image transfer and high quantum efficiency at the carbon K-edge. Reconstructed amplitude and phase contrast images, C 1s spectral stacks, and X-ray linear dichroism of carbon nanotubes at the carbon K-edge were measured with ptychography. Ptychography and conventional Scanning Transmission X-ray Microscopy (STXM) are compared using results acquired from the same area. Relative to STXM, ptychography provides both improved spatial resolution and improved image quality. We used defocus ptychography, with an X-ray beam spot size of 1.0 micron, in order to reduce radiation damage and carbon deposition. Comparable spatial resolution was achieved to that of ptychography performed with a focused beam. Ptychography at the carbon K-edge offers unique opportunities to perform high resolution spectromicroscopy on organic materials important in medicine, biology, environmental science and energy materials.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".