Microcantilevers Modified with Ferrocene-Terminated Self-Assembled Monolayers: Effect of Molecular Structure and Electrolyte Anion on the Redox-Induced Surface Stress
Bibliographic record
Abstract
The redox-activated deflection of microcantilevers has attracted interest for chemical sensing and nanoactuation. However, the development and optimization of this type of microcantilever transduction requires a better understanding of the effect of the particular system parameters on the surface stress changes that cause the measured bending response. We investigate here the effects of the adsorbate structure and electrolyte anion on the surface stress generated by the electrochemical oxidation of ferrocene-terminated self-assembled monolayers (SAMs) chemisorbed to the surface of gold-coated microcantilevers. Ferrocenylalkanethiolate-modified cantilevers are an interesting system for study as the electroactive monolayer can induce charge-normalized surface stress changes that are at least 10-fold greater than those generated by multilayers of the conducting polymers commonly used for electroactuation. The resonance angle shifts measured by surface plasmon resonance spectroscopy in the presence of ClO 4 − suggest that the extent of the oxidation-induced SAM reorganization is the same for short ( n = 6) and long ( n = 12) chain ferrocenylalkanethiolate (FcC n SAu) SAMs and for a long chain carbonyl derivative (Fc(CO)C 11 SAu). The magnitude of the measured cantilever deflection is however not the same for the different SAMs, reflecting differences in the tensile contributions to the overall surface stress of the SAM elasticity and wettability versus the compressive lateral pressure generated by the collective molecular reorientations induced by the pairing of anions to the surface-confined, oxidized ferrocenium cations. The hydrophobic anions PF 6 − and ClO 4 −, which form 1:1 contact ion pairs with the SAM-bound ferrocenium cations, give reversible cantilever deflections and the largest compressive surface stress changes. By contrast, oxidation of the FcC 11 SAu SAM in NO 3 − and F −, which exhibit the poorest ion-pairing abilities of the anions investigated, results in an irreversible deformation of the cantilever bending and smaller stress changes. The surface phenomena that give rise to the observed differences in the surface stress as a function of the ion pairing ability are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".