Critical discussion of light scattering and microscopy techniques for CNC particle sizing
Bibliographic record
Abstract
The determination of particle length and aspect ratio of acicular cellulose nanocrystals (CNCs) becomes crucial when CNCs are used as a catalyst or as a reinforcement additive or when their size is used as a quality control parameter for production.We measured particle dimensions and particle size distribution of CNCs using several experimental techniques based on electron and optical microscopy as well as static and dynamic light scattering.Electron microscopy can easily reveal the real dimensions (i.e.length and cross-section) of nonsymmetrical particles like CNCs while the lightscattering derived techniques cannot.With the latter, it is however possible to approximate the real dimensions using the appropriate theory.The different aspects of light scattering techniques and types of data that can be obtained are presented and detailed.For each technique used, measurements done with CNCs are compared to those obtained with spherical standard latex particles.The accuracy of the final data was also related to the time necessary to obtain it.This "accuracy over time" ratio is of importance when specific applications such as on-line quality control are targeted.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".