Room-Temperature Reduction of Graphene Oxide in Water by Metal Chloride Hydrates: A Cleaner Approach for the Preparation of Graphene@Metal Hybrids
Bibliographic record
Abstract
Headed for developing minimalistic strategies to produce graphene@metal hybrids for electronics on a larger scale, we discovered that graphene oxide (GO)-metal oxide (MO) hybrids are formed spontaneously in water at room temperature in the presence of nothing else than graphene oxide itself and metal ions. Our observations show metal oxide nanoparticles decorating the surface of graphene oxide with particle diameter in the range of 10-40 nm after only 1 h of mixing. Their load ranged from 0.2% to 6.3% depending on the nature of the selected metal. To show the generality of the reactivity of GO with different ions in standard conditions, we prepared common hybrids with GO and tin, iron, zinc, aluminum and magnesium. By means of carbon-13 solid-state nuclear magnetic resonance using magic angle spinning, we have found that graphene oxide is also moderately reduced at the same time. Our method is powerful and unique because it avoids the use of chemicals and heat to promote the coprecipitation and the reduction of GO. This advantage allows synthesizing GO@MO hybrids with higher structural integrity and purity with a tunable level of oxidization, in a faster and greener way.
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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 | 0.001 | 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) | 0.000 | 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".