Exploring graphene oxide in environmentally altered graphite: a link between chemistry and archaeology.
Bibliographic record
Abstract
Graphene oxide (GO) has drawn a great deal of attention, in a laboratory setting, due to its ability to stay suspended in water more easily for solution processing of graphene. In an outdoor setting, it is possible that GO is formed as graphite degrades over time in charred carbon-rich materials such as archaeological charcoal. This GO could be used as a valuable source for radiocarbon dating because its carbon would have the same age as the graphitic carbon that is traditionally extracted for dating. Before radiocarbon dating, graphitic samples are cleaned using a series of strong acid and base treatments to remove contaminants. However, this cleaning procedure can break down some graphite-based samples, leaving no graphite for ¹⁴C dating. In those situations, we suspect that GO is cleaned away along with the unwanted contaminants. Our studies are the first to consider whether GO exists in archaeological charcoal and if it can be separated effectively from carbon-containing contaminants. These findings will be particularly useful for chemists and environmental scientists who work with natural sources of graphite in which oxidized graphenic materials may be present. Here, we show that a mixture of oxidized graphenic material with different degrees of oxidation, and fluorescent carbon-based materials, can be present in archaeological charcoal. We also develop a straightforward protocol that separates a simple test case of a lab-prepared mixture of these components. Our results help to explain why a significant amount of archaeological charcoal is sometimes lost during aqueous cleaning treatments at different pH values. The fluorescent carbon-based materials described above could originate from either the original graphite (in the form of highly oxidized pieces, called oxidative debris (OD)) or from contaminants (such as humic acid (HA)). The fluorescent materials stay suspended in alkaline aqueous solutions. Although UV-Vis data of base-treated archaeological charcoal shows evidence of oxidized carbon, it is not informative enough to study a mixture of oxidized graphite, OD, and HA. Therefore, we monitor UV absorption at specific wavelengths as a function of retention time using size exclusion chromatography (SEC). Our results demonstrate that distinguishing oxidized graphite, OD, and HA from each other is very challenging. Based on SEC results, we identify materials in archaeological charcoal that have similar UV excitation responses and similar retention time (size) to a common HA standard, as well as other components with similar UV excitation responses at longer retention times (smaller sizes).
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".