A Study on the Stoichiometry of One-Dimensional Nanostructures
Bibliographic record
Abstract
While attributes such as small dimensions, low power consumption, fast sensor response, and a wide range of detection give one-dimensional nanostructures excellent potential to revolutionize sensor and detector industries, challenges to achieving uniform stoichiometry pose significant obstacles to their commercial use. Diverse characteristics arise from nanostructures with variable compositions and morphologies. Thus, investigation of physical properties of nanostructures would be pointless if one cannot assure the exact stoichiometry of the material. We studied the stoichiometry of ZnTe nanowires grown via the vapor-liquid-solid method. Different microscopy and composition analysis methods were exploited to study the stoichiometry of the nanowires. It was observed that nonstoichiometric wires had relatively higher defect concentrations. The temperature profile along the substrate during nanowire growth was found to be the reason for the formation of nanowires with different stoichiometries.
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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".