From Spheres to Cones: Structural Instabilities and Acidity at Conical Regions in Trivalent Metal Ion Nano-clusters
Bibliographic record
Abstract
Sub-nanometer aqueous clusters containing a single trivalent metal cation can exhibit charge-induced structural instabilities. Here, we present computational evidence that clusters containing a single \ce{Fe^{3+}}, \ce{Lu^{3+}}, or \ce{La^{3+}} ion undergo continuous geometric transformations as a consequence of this instability. These clusters dynamically evolve across their potential energy landscape, adopting triangular, elongated two-point, single-point, and more spherical configurations often with distinct conical surface protrusions. The manifestation of this instability differs from that observed in mesoscopic and microscopic droplets containing macroions, where stable ``star-like'' structures form, characterized by a specific number of conical protrusions that varies with the droplet size. In the present study, we find that the orientation of the \ce{H2O} molecules surrounding the metal ion is influenced not only by the electric field of the trivalent ion but also by the local conical protrusions. To further investigate the local acidity in the conical protrusions, we employ a proxy model system consisting of an aqueous nano-cluster containing three \ce{H3O+} ions, simulated using ab initio molecular dynamics. Within the conical regions of the cluster, protons exhibit diffusion across several water molecules, in contrast to the more localized proton delocalization observed in the compact body of the cluster. These findings suggest that local geometry can significantly modulate acidity in highly charged nano-clusters, with potential implications for understanding charge-transfer and ionization mechanisms in techniques such as electrospray ionization mass spectrometry. Additionally, the structural motifs and solvent organization reported here provide a molecular-level framework that can complement interpretations from infrared spectroscopic data.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 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".