Spontaneous Formation of Core/Shell Bimetallic Nanoparticles: A Calorimetric Study
Bibliographic record
Abstract
We showed recently that low entropy core/shell structured nanoparticles form spontaneously from the physical mixture of a dispersion of Ag nanoparticles and that of another noble metal (Rh, Pd, or Pt) at room temperature. Here we use isothermal titration calorimetry (ITC) and show that the initial step of such a spontaneous process is strongly exothermic. When the alcohol dispersion of poly(N-vinyl-2-pyrrolidone) (PVP)-protected Rh nanoparticles (average diameter 2.3 nm) was titrated into the alcoholic dispersion of PVP-protected Ag nanoparticles, a strong exothermic enthalpy change, DeltaH, was observed: DeltaH = -908 kJ/mol for Ag(S) nanoparticle (average diameter 10.8 nm) and -963 kJ/mol for Ag(L) nanoparticles (average diameter 22.5 nm). The strength of interaction increases in the order of Rh/Ag > Pd/Ag > Pt/Ag. This strong exothermic interaction is considered as a driving force to from low entropy bimetallic nanoparticles by simple mixing of two kinds of monometallic nanoparticles. We show also that exothermic interactions occur between a pair of noble metal nanoparticles themselves by using ITC.
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 | 0.001 |
| 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 | 0.001 |
| 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".