Large-Area Monocrystalline Copper Microflake Synthesis
Bibliographic record
Abstract
Copper is one of the most extensively studied materials for energy conversion and catalytic systems, with a wide range of other applications, from nanophotonics to biotechnology. However, existing synthesis methods are limited with many undesirable byproducts and poorly defined morphologies. Here, we report an on-substrate wet synthesis approach that yields purely metallic and monocrystalline Cu microflakes with an exposed (111) crystalline surface. By systematically studying the growth mechanism, we achieve unprecedented sizes of more than 130 μm, which is 2 orders of magnitude larger than reported in most previous studies, along with high aspect ratios of over 400. Furthermore, we show significantly higher stability against oxidation provided by the halide adlayer, which also eliminates the need for any organic surfactants in the synthesis. Overall, our facile synthesis approach delivers an exciting avenue for the emerging fields of catalysis and nanophotonics.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".