Structural Transformation and Physicochemical Properties of Environmental Nanoparticles by Comparison of Various Particle‐Size Fractions
Bibliographic record
Abstract
Information on the nature, physicochemical properties, and environmental fate of nanoparticles is severely lacking. Zeolite A was used to demonstrate its structural transformation from well crystalline to short‐range‐ordered (SRO) particles, including nanoparticles with size fractions in the range of 450 to 2000, 100 to 450, 25 to 100, and 1 to 25 nm. The chemical properties of a zeolite are dependent on its framework structure, which is formed by connecting truncated octahedra (sodalite) through the simple double four rings (D4‐R) with external linkage in each sodalite. With decreasing particle size, the T(Si, Al)‐O asymmetric and symmetric stretching vibrations shifted toward higher frequencies and the Si to Al molar ratio increased consistently from 1.8 to 5.2. The chemical shift of 27 Al and 29 Si magic‐angle spinning (MAS) nuclear magnetic resonance (NMR) spectra was related to its structural transformation from well crystalline to SRO particles, which was attributed to the loss of external linkage D4‐R units in the structure. Comparing the various particle‐size fractions (PSFs) showed significant differences in surface area, Si/Al molar ratio, morphology, crystallinity, framework structure, and surface atomic structure of nanoparticles from those of the bulk sample (i.e.,<2000 nm) before particle‐size fractionations. Formation of these most reactive nanoparticles were caused by physicochemical weathering merits increasing attention with reference to their nature and properties, and their importance in ecosystem integrity.
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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) | 0.000 | 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".