Thermal Stability of Metal Nanocrystals: An Investigation of the Surface and Bulk Reconstructions of Pd Concave Icosahedra
Bibliographic record
Abstract
Despite the remarkable success in controlling the synthesis of metal nanocrystals, it still remains a grand challenge to stabilize and preserve the shapes or internal structures of metastable kinetic products. In this work, we address this issue by systematically investigating the surface and bulk reconstructions experienced by a Pd concave icosahedron when subjected to heating up to 600 °C in vacuum. We used in situ high-resolution transmission electron microscopy to identify the equilibration pathways of this far-from-equilibrium structure. We were able to capture key structural transformations occurring during the thermal annealing process, which were mechanistically rationalized by implementing self-consistent plane-wave density functional theory (DFT) calculations. Specifically, the concave icosahedron was found to evolve into a regular icosahedron via surface reconstruction in the range of 200-400 °C, and then transform into a pseudospherical crystalline structure through bulk reconstruction when further heated to 600 °C. The mechanistic understanding may lead to the development of strategies for enhancing the thermal stability of metal nanocrystals.
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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 | 0.000 |
| 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) | 0.001 | 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".