New Dihexadecyldithiophosphate SAMs on Gold Provide Insight into the Unusual Dependence of Adsorbate Chelation on Substrate Morphology in SAMs of Dialkyldithiophosphinic Acids
Bibliographic record
Abstract
We report the formation and characterization of new self-assembled monolayers (SAMs) formed from dihexadecyldithiophosphate (C16)2DDP and compare their properties with those of SAMs formed from the structurally similar adsorbate dihexadecyldithiophosphinic acid (C16)2DTPA. The new (C16)2DDP SAMs were characterized using X-ray photoelectron spectroscopy, reflection-absorption infrared spectroscopy, contact angle measurements, and electrochemical impedance spectroscopy. The data indicate that (C16)2DDP forms SAMs on gold films formed by e-beam evaporation in which all adsorbates chelate to gold, in contrast to (C16)2DTPA SAMs, in which 40% of the adsorbates are monodentate. The alkyl chains of the (C16)2DDP SAM are also less densely packed and ordered than those of the (C16)2DTPA SAM. To understand these differences, we present density functional theory calculations that show that there are only minimal differences between the geometric and electronic structures of the two adsorbates and that the energetic difference between monodentate and bidentate binding of a gold(I) ion are surprisingly small for both adsorbates. This study leads to the conclusion that differences in intermolecular interactions within the SAM are the driving force for the difference in chelation between the two adsorbates.
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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".