Nanojoining and tailoring of current–voltage characteristics of metal-P type semiconductor nanowire heterojunction by femtosecond laser irradiation
Bibliographic record
Abstract
Selective engineering of the interface between nanoscale components and the electrical properties of heterojunctions is key to the development of next-generation nanoscale circuit elements. In this paper, we show how laser processing of a metal-P type semiconductor nanoscale heterojunction between Ag and CuO nanowires can be used to control the nature of the electrical contact by reducing the Schottky barrier at the Ag–CuO interface to Ohmic contact. Elimination of the Schottky barriers occurs in response to lattice matching of Ag(111)∥CuO(111) planes at the interface induced by controlled irradiation with femtosecond (fs) laser pulses. An interdiffusion region with a mixed Ag/CuO composition is also present over a localized area of the interface between the Ag and CuO nanowires after fs laser processing, but both Ag and CuO nanowires remain crystalline away from the heterojunction. In addition, the Ag nanowire becomes totally embedded in the larger CuO nanowire after irradiation. Fabricated nanowire devices from Ag–CuO nanowire heterojunctions transition from a double-Schottky contact configuration prior to laser processing to a rectifying behavior as irradiation time increases. This study illustrates that fs laser processing can be highly effective in the engineering of electrical performance in metal–semiconductor nanoscale heterojunction devices.
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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".