100-fold improvement in carrier drift mobilities in alkanephosphonate-passivated monocrystalline TiO<sub>2</sub> nanowire arrays
Bibliographic record
Abstract
Abstract Single crystal rutile titania nanowires grown by solvothermal synthesis are actively being researched for use as electron transporting scaffolds in perovskite solar cells, in low detection limit ultraviolet photodetectors, in photoelectrochemical water-splitting, and in chemiresistive and electrochemical sensing. The electron drift mobility ( μ n ) in solution-grown TiO 2 nanowires is very low due to a high density of deep traps, and reduces performance in optoelectronic devices. In this study, the effects of molecular passivation of the nanowire surface by octadecylphosphonic acid (ODPA), on carrier transport in TiO 2 nanowire ensembles, were investigated using transient space charge limited current measurements. Infrared spectroscopy indicated the formation of a highly ordered phosphonate monolayer with a high likelihood of bidentate binding of ODPA to the rutile surface. We report the hole drift mobility ( μ p ) for the first time in unpassivated solvothermal rutile nanowires to be 8.2 × 10 −5 cm 2 V −1 s −1 and the use of ODPA passivation resulted in μ p improving by nearly two orders of magnitude to 7.1 × 10 −3 cm 2 V −1 s −1 . Likewise, ODPA passivation produced between a 2 and 3 order of magnitude improvement in μ n from ∼10 −5 –10 −6 cm 2 V −1 s −1 to ∼10 −3 cm 2 V −1 s −1 . The bias dependence of the post-transit photocurrent decays in ODPA-passivated nanowires indicated that minority carriers were lost to trapping and/or monomolecular recombination for small values of bias (<5 V). Bimolecular recombination was indicated to be the dominant recombination mechanism at higher bias values.
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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) | 0.003 | 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".