Plasmonic engineering of metal-oxide nanowire heterojunctions in integrated nanowire rectification units
Bibliographic record
Abstract
We show that irradiation with femtosecond laser pulses can produce robust nanowire heterojunctions in coupled non-wetting metal-oxide Ag-TiO2 structures. Simulations indicate that joining arises from the effect of strong plasmonic localization in the region of the junction. Strong electric field effects occur in both Ag and TiO2 resulting in the modification of both surfaces and an increase in wettability of TiO2, facilitating the interconnection of Ag and TiO2 nanowires. Irradiation leads to the creation of a thin layer of highly defected TiO2 in the contact region between the Ag and TiO2 nanowires. The presence of this layer allows the formation of a heterojunction and offers the possibility of engineering the electronic characteristics of interfacial structures. Rectifying junctions with single and bipolar properties have been generated in Ag-TiO2 nanowire circuits incorporating asymmetrical and symmetrical interfacial structures, respectively. This fabrication technique should be applicable for the interconnection of other heterogeneous metal-oxide nanowire components and demonstrates that femtosecond laser irradiation enables interfacial engineering for electronic applications of integrated nanowire structures.
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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) | 0.001 | 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 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".