Controllable positioning and alignment of silver nanowires by tunable hydrodynamic focusing
Bibliographic record
Abstract
Assembly and alignment of nanowires or nanotubes are critical steps for integrating functional nanodevices by the bottom-up strategy. However, it is still challenging to manipulate either an array of nanowires or individual nanowires in a controllable manner. Here we present a simple but versatile method of positioning and aligning nanowires by hydrodynamic focusing that functions as 'hydro-tweezers'. By adjusting the flow duration and flow rates of the sheath flows and sample flow, the density, width and position of the nanowire arrays, as building blocks of nanodevices, can be readily tuned in the hydrodynamic focusing process. This approach exhibits great potentials in the assembly of an array of functional nanodevices. With this method, multiple nanowire arrays can be positioned and aligned on predefined locations. Further focusing the sample flow, nanowires flow in single file. Thus single nanowires can also be lined up and located to desired positions.
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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".