Theoretical study of the adsorption of aromatic amino acids on a single-wall boron nitride nanotube with empirical dispersion correction
Bibliographic record
Abstract
In the present study, the adsorption and properties of three popularly studied aromatic amino acids, namely phenylalanine, tyrosine, and tryptophan, on the surface of the single-wall boron nitride nanotubes (BNNTs) have been explored with an empirical dispersion corrected density functional tight-binding method. A serials of armchair BNNTs (n = 4–12) and zigzag BNNTs (n = 8–18) with the aromatic amino acid adsorbed on the surface are investigated. With the dispersion correction explicitly considered in the density functional tight-binding method, the adsorption properties between amino acids and BNNTs are described by including long-range van der Waals interactions. It is found that the π–π and H–π stacking interactions are the main forces stabilizing the system. Based on the evidence of adsorption energy, charge density plots, and density of states analysis, the study concludes that the BNNT adsorbs the amino acids with no bonded interactions between the two parts. The interactions of amino with the BNNT were further studied by analyzing molecular orbitals and excited state absorption spectrum of the stable complexes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".