Element-Specific Local Chemical Order of High-Entropy Nanoalloys
Bibliographic record
Abstract
Multielemental nanoalloys have shown significant promise in applications like catalysis, due to the structural features that arise from their complex structure. A key feature of particular interest is local chemical order (LCO) at the scale of a single neighboring bond length. LCO has proven challenging and inconclusive to identify and assess in these materials, particularly in samples containing elements with similar atomic numbers. Herein, we apply a methodology combining experimental X-ray absorption spectroscopy and computational simulations, allowing for the reliable verification and quantification of LCO in a five-element high-entropy alloy (HEA-5) on an element-specific basis. The analysis identifies the Ru-Ir bonding pair as a significant component of LCO, which correlates with HEA-5's established high catalytic performance in ammonia decomposition. The methodology is further applied to a complex 15-element HEA sample, where consistent LCO trends are observed. These results support an element-specific approach for investigating LCO, structural analysis, and the catalytic design of high-entropy nanoalloys.
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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 | 0.000 | 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) | 0.000 | 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".