Quantitative Evaluation of Radiation Damage to Polyethylene Terephthalate by Soft X-rays and High-energy Electrons
Bibliographic record
Abstract
The chemical changes and absolute rates in radiation damage to polyethylene terephthalate (PET) caused by soft X-rays and energetic electrons have been measured using a scanning transmission X-ray microscope (STXM). Electron beam damage at two different dose rates and a range of doses was performed in an 80 keV transmission electron microscope (TEM). The STXM beam was used to create damage patterns with systematically varied doses of monochromatic soft X-rays on an adjacent piece of the same PET sample. NEXAFS spectroscopy at the C 1s and O 1s edges was used to study the chemistry of the radiation damage and to determine quantitative critical doses for PET damage by both types of radiation. The spectral changes were similar for damage by electrons and X-rays, indicating the radiation chemistry is dominated by secondary processes, not the primary event. The critical dose for chemical changes determined from C 1s spectral features is 4.2(6) x 10(8) Gy and was the same for soft X-rays and electrons within measurement uncertainties. The critical dose for specific damage processes (as defined by changes in several different, bond-specific spectral features) was found to be similar in the C 1s region and was comparable between C 1s and O 1s edges for electron beam damage. There were statistically different critical doses for soft X-ray damage as probed by changes in O 1s spectral features related to carbonyl and ester bonds.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".