Investigation of the morphology and optical properties of graphene oxide for online diagnostics
Bibliographic record
Abstract
Graphene oxide (GO) particles have a wide and growing range of applications. They may also be converted to reduced graphene oxide (rGO) particles, which are increasingly used in energy storage devices like batteries and supercapacitors. However, the downstream functionality of GO and rGO particles depends strongly on their morphology, which is highly variable depending on the synthesis process. Here, we report GO-particle morphological and optical properties for GO particles in the aerosol phase. These include the mobility diameter, effective density (0.93 ± 0.06 g cm -3 ), mass–mobility exponent (2.97 ± 0.06), Angstrom absorption exponent (2.48 between 370 nm and 950 nm), mass absorption cross-section (0.99 ± 0.22 m 2 g −1 ), and mass scattering cross-section. Although this study reports measurements on re-aerosolized GO powder, the demonstrated techniques and measured properties serve as a foundation for in-reactor optical diagnostics that may allow for online control of the synthesis processes enabling the ability to control and characterize the functionality of downstream particles.
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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) | 0.001 | 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".