Determination of Metallic Impurities in Carbon Nanotubes by Glow Discharge Mass Spectrometry
Bibliographic record
Abstract
A method for the rapid assessment of metallic impurities in carbon nanotubes (CNTs) by pin-cell source geometry glow discharge mass spectrometry (GDMS) is presented. Pins were prepared by pressing CNT powder onto an indium substrate. GDMS analysis was performed using high-carbon-content nanotube and coal-certified reference materials for calibration purposes. This approach enables the calibrated measurement of 41 elemental impurities in CNTs. The method was validated by the analysis of NIST SRM 2483 single-wall CNTs (raw soot) with good agreement with the certified values. The proposed measurement approach could also be applied not only for CNTs but also for the assessment of precursor materials used in the synthesis of CNTs and for quality control during the entire manufacturing process. The ability to assess the presence of all metallic impurities in a simple, reliable, high-throughput manner will allow the industry to real-time monitor any changes in the product process, access its toxicity, and environmental impact. As sample preparation is maintained to a minimum, this allows the determination of metallic impurities at concentration levels that are usually not attainable by most techniques.
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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".