High-temperature radiation resistance of NiCoFe medium-entropy alloy enabled by stable nanostructures and defect evolution mechanisms
Bibliographic record
Abstract
The study innovatively examined a nano oxide dispersion-strengthened (ODS) NiCoFe medium-entropy alloy with nanosized grains to address the challenge of discovering structural materials for high-temperature irradiation applications, such as in advanced nuclear reactors. The ODS-NiCoFe alloy exhibited a nanoindentation hardness of 4.3 ± 0.9 GPa, representing a two-fold enhancement over the 2.0 ± 0.1 GPa of single-crystal NiCoFe. Dislocations were identified as the primary defect structures. Following irradiation (Ni 2+ , 580 °C), the average dislocation length density increased from ∼2.6 × 10 13 m −2 to ∼6.1 × 10 13 m −2 , while the mean dislocation length decreased from 249 nm to 104 nm, contributing to a relative irradiation hardening of 25 %. Additionally, the study demonstrated the stability of various nanostructures, with only minor changes in the average sizes of nanoprecipitates and grains—from 6.7 ± 1.7 nm to 6.4 ± 1.7 nm, and from 73 ± 2 nm to 76 ± 2 nm, respectively, upon irradiation, suggesting effective defect annihilation at interfaces and grain boundaries. The alloy exhibited no observable irradiation-induced voids. Molecular dynamics simulations revealed irradiation resistance of the alloy through the absorption of vacancy clusters at grain boundaries and Shockley-dominant-dislocation chains and the absorption of interstitial clusters at grain boundaries, aided by the high mobility and three-dimensional motion of interstitial clusters. Thus, the findings demonstrate the high-temperature radiation resistance of the novel ODS-NiCoFe alloy, surpassing that of well-known ODS steels, using a correlative approach that combines experiments and simulations.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".