Biofunctionalization of Si(111)7×7 by “Renewable” <scp>l</scp>-Cysteine Transitional Layer
Bibliographic record
Abstract
Surface functionalization of an inorganic surface with bio-organic molecules is often aimed at creating a "permanent" bio-organic surface with receptor functional groups. We show here that L-cysteine can be used to transform a highly reactive Si(111)7×7 surface to not just a permanent bio-organic surface but also a semipermanent (or renewable) and a temporary bio-organic surfaces by manipulating the exposure. In the early growth stage, the strong bonding between the first cysteine adlayer and the Si substrate through Si-N or Si-S linkages in unidentate or bidentate arrangement provides permanent biofunctionalization by this interfacial layer. This interfacial layer can be used to build a transitional layer (second adlayer) mediated by interlayer vertical hydrogen bonding between an amino group and a carboxylic acid group. Further exposure of cysteine eventually leads to a zwitterionic multilayer film involving electrostatic interactions between cation (-NH3(+)) and anion moieties (-COO(-)). The interlayer hydrogen bonding therefore provides temporary trapping of bio-organic molecules as the second transitional layer that is stable up to 175 °C. This transitional layer can be easily removed by annealing above this temperature and then regenerated with the same molecular layer or a different one by "renewing" the interlayer hydrogen bonds. We also illustrate coverage-dependent adsorption structures of cysteine, from bidentate to unidentate attachments and to self-assembled multimers, involving formation of intralayer horizontal N···H-O hydrogen bonds, by combining our X-ray photoemission data with the local density-of-state images obtained by scanning tunnelling microscopy.
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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 | 0.000 |
| 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".