Influence of nitrogen on deuterium retention in tungsten under sequential and simultaneous irradiation
Why this work is in the frame
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Bibliographic record
Abstract
Nitrogen is a candidate for impurity seeding to reduce the edge plasma temperature for ITER’s tungsten divertor. Radiation characteristics and plasma performance are improved with N compared to other candidates neon and argon, however questions remain in terms of how the introduction of N might impact deuterium retention in W. The current study compares the influence of N on D retention in W with sequential (SEQ) and simultaneous (SIM) irradiation of D-3%N at 300–700 K with energies 500 eV/D+ and 1000 eV/N+. Thermal desorption spectroscopy (TDS) is used to measure the D retained, and X-ray photoelectron spectroscopy (XPS) is used to investigate nitride formation at different implantation temperatures. The XPS results show that for the beam composition of this study, the removal of N by D is the dominant interaction, working against N retention in W. Differences found between the N layer with D/N co-bombardment vs. N pre-irradiation might be worth considering when extrapolating sequential experiments to reactor conditions. The observed effect of the N-containing layer on the temperature dependence of deuterium release during TDS supports the XPS findings, suggesting that the phases of the W:N layer produced are different at different temperatures. It is found that SIM irradiation resulted in an overall increase (up to a factor of ∼4) in total D retention compared to SEQ and D-only experiments above 500 K. At 300–500 K, the D retention was not significantly changed by nitrogen pre-, post- or simultaneous irradiation.
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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 | 0.000 |
| 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) | 0.000 | 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 it