The impact of fabrication conditions on the quality of Au nanoparticle arrays on dimpled Ta templates
Bibliographic record
Abstract
Highly ordered dimpled Ta (DT) nanotemplates, prepared by electrochemical anodization of Ta, were recently reported to be ideally suited for the fabrication of a Au nanoparticle (NP) array using a Au thin film dewetting method. Here, we provide guidance and understanding of the effect of the DT fabrication and Au film deposition steps on the characteristics of the resulting NP array. Specifically, the optimum anodization time, voltage and solution composition are established, and the thickness of the sputter-deposited metal film is shown to be a very important parameter in achieving the desired single Au NP per dimple. The resulting high quality Au NP arrays are demonstrated to be electrochemically addressable, with the total Au surface area, measured electrochemically for large-scale samples, agreeing with the calculated area, based on scanning electron microscope determination of average particle shape and distribution. As the NP formation process proceeds via confined thin film dewetting, the protocol developed here should be applicable to the formation of NP arrays of a range of other metals and alloys.
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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".