ToF-SIMS study of selective anchoring of Ru(tpy)2 complexes on zirconium-phosphate functionalized oxide surfaces
Bibliographic record
Abstract
Polypyridine-based ruthenium complexes are among the most interesting photoactive molecular systems, in virtue of a number of outstanding (photo)physicochemical properties. To exploit such properties in solid-state applications, such as molecular electronics, optoelectronics, and photovoltaics, tailored experimental strategies are needed for the anchoring of such complexes on surfaces. At the same time, these strategies need to be investigated and validated through precise monitoring of the surface composition. In this contribution, the authors report on the application of time-of-flight secondary ion mass spectrometry (ToF-SIMS) for studying the anchoring onto transparent (semi)conducting fluorine tin-doped oxide of the polypyridinic photoactive RuDT2. This molecule is characterized by an Ru(tpy)2 core and two free terpyridinic units. The authors’ approach involves the use of a surface priming strategy based on the chemistry of zirconium phosphates and phosphonates (ZP-priming) to provide a platform for direct anchoring of RuDT2 molecules at the oxide surface. Onto patterned ZP-fluorine-doped tin oxide (FTO), the authors report selective anchoring of RuDT2 only onto ZP domains, while no binding occurs onto bare FTO areas. The latter were shown to remain available for further functionalization using functional molecules containing phosphonic moieties, and in the authors’ case, a phosphonic derivative of rhodamine B (RhB-P) was used. ToF-SIMS imaging was intensively used to monitor each reaction step and confirm the successful laterally resolved and selective adsorption of RuDT2 and RhB-P onto ZP and bare FTO domains, respectively.
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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) | 0.002 | 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".