Low‐lying energy isomers and global minima of aqueous nanoclusters: Structures and spectroscopic features of the pentagonal dodecahedron (H<sub>2</sub>O)<sub>20</sub> and (H<sub>3</sub>O)<sup>+</sup>(H<sub>2</sub>O)<sub>20</sub>
Bibliographic record
Abstract
Abstract We rely on a hierarchical approach to identify the low‐lying isomers and corresponding global minima of the pentagonal dodecahedron (H2O)20 and the H3O+(H2O)20 nanoclusters. Initial screening of the isomers is performed using classical interaction potentials, namely the Transferable Interaction 4‐site Potential (TIP4P), the Thole‐Type Flexible Model, versions 2.0 (TTM2‐F) and 2.1 (TTM2.1‐F) for (H2O)20 and the Anisotropic Site Potential (ASP) for H3O+(H2O)20. The nano‐networks obtained with those potentials were subsequently refined at the density functional theory (DFT) with the Becke‐3‐parameter Lee–Yang–Parr (B3LYP) functional and at the second order Møller–Plesset perturbation (MP2) levels of theory. For the pentagonal dodecahedron (H2O)20 it was found that DFT (B3LYP) and MP2 produced the same global minimum. However, this was not the case for the H3O+(H2O)20 cluster, for which MP2 produced a different network for the global minimum when compared to DFT (B3LYP). The low‐lying networks of H3O+(H2O)20 correspond to structures having 9 ‘free’ OH bonds and the hydronium ion on the surface of the nanocluster. The IR spectra of the various networks are further analysed in the OH stretching (‘fingerprint’) region and the various bands are assigned to structural arrangements of the underlying hydrogen bonding network. © 2012 Canadian Society for Chemical Engineering
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 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 | 0.000 |
| 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) | 0.002 | 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".