Structure and Chirality in Sulfur-Containing Amino Acids Adsorbed on Au(111) Surfaces
Bibliographic record
Abstract
Chiral self-assembly is governed by a complex interplay between molecular asymmetry and intermolecular and molecule–substrate interactions. In this work, we examined extended systems of enantiomerically pure and racemic cysteine, homocysteine, and methionine and their self-assembly on Au(111), using a classical parallel tempering Monte Carlo approach. We found that, for all of the amino acids considered here, the Au(111) substrate provided insufficient configurational restriction to promote chiral recognition upon adsorption. Molecules tethered to the surface were able to sample a broad range of configurations, and form complex networks of hydrogen bonds. Upon dissociative adsorption, rosette structures and chains with small local enantiomeric excess were observed, while nondissociative processes led to formation of solution-type racemic aggregates. Given the important role played by the surface in the chiral recognition process, we propose that a four-step interaction model (Booth et al. Chirality 1997, 9, 96) is more appropriate for such systems than the more traditional three-point contact model.
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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".