On the nature and importance of the transition between molecules and nanocrystals: towards a chemistry of “nanoscale perfection”
Bibliographic record
Abstract
This paper discusses the importance of the transition between molecular compounds and nanocrystals. The boundary between molecular and nanocrystals/nanoclusters can be defined by the emergence of the bulk phase; atoms in the core of the nanoclusters that are not bound to ligands. This transition in dimensions and structural organization is important because it overlaps with the boundary between atomically defined moieties (molecules can be isolated with increasing purity) and mixtures (nanocrystals have a distribution of sizes, shapes, and defects; they cannot be easily separated into batches of structurally identical species). Passing through this boundary, as the size of a structure increases beyond a few nanometres, the information about the position of each atom gradually disappears. This loss of structural information about a chemical structure fundamentally compromises our ability to use it as a part of a complex chemical system. If we are to engineer complex functions encoded in a chemical language, we will need pure batches of atomically defined (truly monodisperse) nanoscale compounds, and we will need to understand how to make them and preserve them over a broad range of length scales, compositions, and timeframes. In this review we survey most classes of monodisperse nanomaterials (mostly nanoclusters) and highlight the recent breakthroughs in this area which might be spearheading the development of a chemistry of "nanoscale perfection".
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".