Silicon carbide phase stability in a fusion environment
Bibliographic record
Abstract
Progress in developing fusion reactor concepts is constrained by materials technology.The materials selected for the first wall should be able to stand high thermal loading and high fast neutron fluence, in the presence of corrosive cooling environments.Materials near the area of the first wall will be exposed to high fast neutron fluence (-10 23 n/cm 2 ), accumulate a large dose (-100 dpa) and be subjected to large gas and solid transmutation effects.Silicon carbide ceramics and SiC/SiC composites are considered promising first wall materials in various fusion design concepts because of their excellent high-temperature properties, good corrosion resistance and low activation.However, the effect of solid trans mutants on SiC swelling and irradiation stability is a major concern.A recent review paper [1] shows that in either Inertial (IFE) or Magnetic (MFE) fusion reactor concepts, the percent burnup (atoms of Si and C in SiC) is high; up to 10% loss of atoms after reaching the end of the first wall expected 5-year lifetime.Transmutation reactions in SiC generate H, He and up to 1 % Mg after an exposure of 5 years from fast neutron (n,a) reactions in 28Si and 29Si leading to the formation of stable isotopes 25Mg and 26Mg, respectively.Following a path similar to that described in [2], we study the transmutation defect reactions in which the daughter product resides in the Si site, examine the evolving chemistry and investigate the effect of lattice stability of a large concentration of an insoluble solute looking for the formation of new/rare phases, in particular MgC, a crystalline structure with limited information available in the literature.In this work, we apply density functional theory (OFT) combined with the pseudo-potential approximation and a basis set of numerical atomic orbitals as implemented in the program SIESTA [3] to explore the presence of possible new phases, e.g.MgC, Mg 3 C 2 and MgC2.The USPEX code [4] is used in combination with SIESTA to predict crystal structures for MgC at several temperature conditions.We show that a phenomenon similar to that of radioparagenesis could lead to the formation of rare crystal structures in Si when exposed to the extreme solid transmutation conditions occurring at the first wall of the fusion power reactor.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".