Non‐Lithography Hydrodynamic Printing of Micro/Nanostructures on Curved Surfaces
Bibliographic record
Abstract
Abstract A key issue of micro/nano devices is how to integrate micro/nanostructures with specified chemical components onto various curved surfaces. Hydrodynamic printing of micro/nanostructures on three‐dimensional curved surfaces is achieved with a strategy that combines template‐induced hydrodynamic printing and self‐assembly of nanoparticles (NPs). Non‐lithography flexible wall‐shaped templates are replicated with microscale features by dicing a trench‐shaped silicon wafer. Arising from the capillary pumped function between the template and curved substrates, NPs in the colloidal suspension self‐assemble into close‐packed micro/nanostructures without a gravity effect. Theoretical analysis with the lattice Boltzmann model reveals the fundamental principles of the hydrodynamic assembly process. Spiral linear structures achieved by two kinds of fluorescent NPs show non‐interfering photoluminescence properties, while the waveguide and photoluminescence are confirmed in 3D curved space. The printed multiconstituent micro/nanostructures with single‐NP resolution may serve as a general platform for optoelectronics beyond flat surfaces.
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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) | 0.000 | 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) | 0.002 | 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".