Surfactant Controlled Growth of Niobium Oxide Nanorods
Bibliographic record
Abstract
This paper describes a solution-phase hydrothermal synthesis of crystalline niobium pentoxide (Nb 2 O 5 ) nanorods. The methods reported herein yield uniform Nb 2 O 5 nanorods with average diameters of 6 nm and lengths of 38 nm, which are directly synthesized from niobic acid by a hydrothermal process. The formation of Nb 2 O 5 nanorods from niobic acid was studied in the presence of surfactants that stabilize the nanostructures. The crystalline Nb 2 O 5 nanorods were relatively uniform in size and shape. The size of the Nb 2 O 5 nanorods could be tuned through the choice of surfactant even in the absence of a worm-like micellar morphology. Amine, amide, ammonium, carboxylate, sulfonate, and sulfate containing surfactants were systematically evaluated for their influence on the ability to form uniform Nb 2 O 5 nanorods. The surfactants in this study had hydrophobic tails that were either straight or branched, such as a polymer, and contained either a single or multiple head groups. The nanorods grew by a process of oriented attachment of nanoparticles that was regulated by the surfactants added into the reaction mixture. The results of these studies indicate that this synthetic approach serves as a tunable platform to prepare single crystalline niobium oxide based nanostructures with well-defined morphologies and dimensions. This surfactant assisted formation of crystalline Nb 2 O 5 nanorods could also have important implications in the design of other transition metal oxide based nanomaterials.
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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".