Mechanical and irradiation behavior of SiC polytypes: Atomistic insights on plastic deformation, damage resistance, and unified performance metric
Bibliographic record
Abstract
Silicon carbide (SiC) is a critical material in advanced nuclear energy systems due to its excellent mechanical strength and radiation resistance under extreme reactor conditions. Understanding its deformation mechanisms and radiation tolerance at the atomic scale is essential for ensuring long-term reliability under extreme conditions. This study employs large-scale molecular dynamics (MD) simulations to investigate both irradiation-induced defect evolution and dislocation-mediated plasticity in three SiC polytypes (3C, 4H, and 6H) under mechanical and radiation environments. Under indentation, 3C-SiC accommodates plasticity primarily by ½<110> glide on {111} systems, forming dense dislocation networks and prismatic loops, whereas hexagonal 4H and 6H favor basal slip, extensive stacking faults. All polytypes show localized amorphization under the indenter, with 6H exhibiting the largest lateral amorphous zones. Irradiation cascades produce an interstitial-carbon dominated defect and nearly linear defect accumulation with sequential PKAs. 3C-SiC retains the most surviving defects and forms the largest defect clusters, while 4H/6H produce smaller, more localized clusters A unified analysis of mechanical and irradiation responses, based on dislocation density, shear modulus, surviving defect counts, clustering fraction, and amorphous volume fraction, reveals that 3C-SiC surpasses hexagonal polytypes by accommodating stress more effectively despite generating more defects. These parameters are synthesized into a novel Radiation Tolerance Index (RTI) to quantify this performance.
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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 | 0.000 |
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".