Influence of high-energy particles on copper and stainless steel in fusion reactor materials
Bibliographic record
Abstract
Many studies have focused on the effect of fusion plasma particles onto the structural materials of future nuclear fusion reactors. In this paper, the effect of the products of the first-generation fuel reaction on structural fusion materials, such as copper and 316-stainless steel target materials, was studied. Firstly, the effect of 14.1 MeV neutrons produced from D–T neutron generator for different irradiation times, 10, 20, 30, 50, and 60 min, was investigated. Hence, this effect was analyzed and characterized by X-ray diffraction analysis, surface roughness test, scanning electron microscope, and Vickers hardness. Secondly, the effect of 3.5 MeV α-particles on these target materials by different incident angles, 0°, 30°, 45°, 60° and 85°, using SRIM code was studied. Also, SRIM code was used to calculate α-particles’ trajectories, projected and straggle ranges, skewness, kurtosis, target ionization/phonons, and total displacements for copper and 316-stainless steel target 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".