Determination of Agglomeration Kinetics in Nanoparticle Dispersions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The direct application of nanoparticles as nonsupported adsorbents and catalysts is of high interest since they offer high surface areas with reduced mass transfer limitations. However, the natural tendency of these materials to aggregate, even faster when at high temperatures, makes the agglomeration process an important phenomenon to be studied, understood and, eventually controlled. A method to obtain the kinetics of nanoparticle agglomeration processes is presented in this paper. This analysis was based on the change of particle diameter during aggregation. The kinetic expression was validated with a series of experiments where the growth of Fe 2 O 3 nanoparticles immersed in base oil was followed at different times, temperatures, and particle concentrations. Results revealed the nature of the particle agglomeration process in the ranges of the experimental conditions; they indicated that physical adhesion, more than chemical binding, is the determining mechanism for agglomeration of Fe 2 O 3 nanoparticles immersed in base oil.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 it