An integrated and multi-technique approach to characterize airborne graphene flakes in the workplace during production phases
Bibliographic record
Abstract
Graphene is a one-atom-thick sheet of carbon atoms arranged in a honeycomb pattern and its unique and amazing properties make it suitable for a wide range of applications ranging from electronic devices to food packaging. However, the biocompatibility of graphene is dependent on the complex interplay of its several physical and chemical properties. The main aim of the present study is to highlight the importance of integrating different characterization techniques to describe the potential release of airborne graphene flakes in a graphene processing and production research laboratory. Specifically, the production and processing (i.e., drying) of few-layer graphene (FLG) through liquid-phase exfoliation of graphite are analysed by integrated characterization techniques. For this purpose, the exposure measurement strategy was based on the multi-metric tiered approach proposed by the Organization for Economic Cooperation and Development (OECD) via integrating high-frequency real-time measurements and personal sampling. Particle number concentration, average diameter and lung deposition surface area time series acquired in the worker's personal breathing zone (PBZ) were compared simultaneously to background measurements, showing the potential release of FLG. Then, electron microscopy techniques and Raman spectroscopy were applied to characterize particles collected by personal inertial impactors to investigate the morphology, chemical composition and crystal structure of rare airborne graphene flakes. The gathered information provides a valuable basis for improving risk management strategies in research and industrial laboratories.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".