Helium plasma immersion ion implantation studies of tungsten and tungsten heavy alloys for fusion plasma facing components
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Bibliographic record
Abstract
Plasma fusion devices will require plasma-facing components (PFCs) which can withstand the extreme environment at the edge of a hot fusion plasma. Despite the excellent properties of tungsten(W) as a hard refractory metal, adverse effects such as embrittlement, melting, and morphological evolution have been observed in W when it is bombarded by a high-fluence of low-energy ions including helium. This study investigates the effect of helium ion bombardment on pure tungsten and a tungsten heavy alloy (W-HA)(NAECOMET 1000). Pure tungsten and NAECOMET 1000 samples were implanted with 3 keV helium ions with fluences ranging from 1.15×1021m−2 to 2.21×1022m−2, using Plasma Immersion Ion Implantation (PIII). After PIII treatment, samples were analysed using scanning electron microscopy (SEM) and atomic force microscopy (AFM), which revealed differences in surface morphology and topography. Although the melting and cracking of the Ni/Cu binder phase in the NAECOMET 1000 samples was seen under all implantation conditions, the Ni/Cu presence did somewhat slow the formation of W fuzz in comparison to pure tungsten. X-ray diffraction (XRD) studies showed peak shifts increasing with helium ion fluence for both the pure W and NAECOMET 1000 samples, as well as increase in mean crystallite size, confirming the distortion of the lattice. XPS compositional analysis showed a strong oxidation (>97%) near the metal surface, after helium PIII treatment, for both pure W and NAECOMET 1000 W-HA samples. Some conclusions about the potential suitability of W-HA materials for fusion plasma PFCs are drawn.
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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 | 0.001 | 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