Coordination Number Dependence of Cysteine Binding to Nanostructured Gold
Bibliographic record
Abstract
The interaction of cysteine and related aminoacids with metal substrates has applications in several fields of science, technology and health. Despite widespread interest in these systems, the relationship between thiol adsorption and surface coarsening, including the effects of sur- face adatoms and other defect sites, has not been systematically addressed. Here, the effect of binding site unsaturation on the adsorption strength of cysteine on gold substrates is examined using density functional theory. Adsorption sites with a full range of in-surface coordination numbers are generated using surface adatoms or pitting structure. The configurational space of the adsorbate on the nanostructured surface is sampled extensively using Born-Oppenheimer molecular dynamics simulation. Our results indicate that binding strength is primarily deter- mined by a combination of surface site reactivity to the mercapto group and the availablity of additional sites for amino group coordination. The study aims to further our understanding of mercapto-aminoacid binding to defect substrates and low-coordinated nanoparticle sites, and to provide a basis for the development of coordination-dependent force fields that may be used in classical simulations of these systems.
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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 | 0.001 |
| 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".