Metal oxide encapsulated nanoparticles
Bibliographic record
Abstract
Atomistic computer simulation techniques have been employed to generate a model for a 25 nm3 CaO nanoparticle, encapsulated within the near surface region of an MgO lattice. We find that the ‘internal’ morphology of the resulting encapsulated CaO nanoparticle is ‘pseudo-spherical’ and exhibits {100}, {110} and {111} facets. The encapsulated nanoparticle suffers significant structural changes in comparison to the bulk parent oxide: Regions within the CaO nanoparticle are identified to suffer both tension and compression together with plane curvature. In addition a wealth of defects (isolated vacancies, interstitials and substitutionals including complex clustering) evolve within the near (1–2 atomic planes) interfacial regions of the CaO nanoparticle and surrounding MgO lattice. The CaO nanoparticle is observed to lie epitaxially with respect to the host MgO lattice with CaO{100} and MgO{100} planes aligned; dislocations evolve to accommodate the +13% bulk lattice misfit associated with the system, the core structures of which are localised at regions of poor registry between the {100} planes. The CaO nanoparticle is observed to rotate by about 6° with respect to the encapsulating MgO matrix, which results in some anisotropy in structure. Comprehensive depictions of the atomistic structure and morphology of the encapsulated CaO nanoparticle and surrounding MgO lattice are presented using molecular graphical techniques.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".