Detailed in situ TEM/EELS analysis of laser-induced reduction of graphene oxide
Bibliographic record
Abstract
Laser-induced reduction of graphene oxide (GO) represents a highly promising approach to graphene synthesis due to local control of the treated area, avoidance of hazardous chemical reagents, and environmentally benign ambient conditions. In this study, we present a comprehensive investigation of the reduction of GO induced by multiple laser pulses at a wavelength of 532 nm by in situ transmission electron microscopy. By systematically varying the laser fluence from 6.36 mJ/cm 2 to 15.88 mJ/cm 2 and employing electron energy loss spectroscopy (EELS), we achieved precise quantification and identification of the removal of distinct oxygen functional groups. The kinetics of the process are modelled using a double-exponential function to determine photoreduction rates as a function of laser fluence. We estimate laser fluences in this range raise the film temperature from 342 °C to 823 °C, and correlate this with observed functional group removal and established thermal decomposition thresholds. Our work offers a detailed understanding of the laser-induced reduction process and highlights the potential for tailoring the chemical composition of graphitic oxides through controlled laser processing.
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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".