In situ Electron Energy Loss Spectroscopy (EELS) Studies of Laser-induced Graphene Oxide Reduction in a Dynamic Transmission Electron Microscope (DTEM)
Bibliographic record
Abstract
Graphene is a single layer of sp2 hybridized carbon atoms and is widely applied in electronics, photonics, and energy-based industries because of its exceptional physical and chemical properties [1]. Graphene-based materials for large-scale production can be obtained from graphene oxide (GO) through effective treatments to reduce the number of oxygen functional groups. GO conversion to reduced GO (rGO) can be done by many methods, including wet chemical reduction, thermal reduction, and photoreduction. Chemical reduction of GO requires hydrazine, sodium borohydride, and other potent reducing agents, limiting this method’s applicability in large-scale production [2]. Further, graphene is a potential candidate for biomedical applications, including drug delivery, cancer therapy, and antimicrobials, but chemically reduced GO has shown potential toxicity to normal cells [3]. Similarly, thermal heating requires temperatures exceeding 1000 °C and complex procedures for the high-quality production of graphene [4]. Photoreduction of GO with a laser is fast and avoids the use of toxic chemicals. Furthermore, the ability to pattern the illumination and raster the target in the beam allows the capability to write rGO circuits in films of GO. To prepare high-quality graphene requires understanding the detailed photoreduction mechanism. We conducted in situ experiments using a dynamic transmission electron microscope (DTEM) watching the photoreduction process of GO sheets. The DTEM at INRS-EMT is based on a JEOL 2100Plus and has been modified to couple laser light into the column through an optical port and focus it onto the sample. We used this configuration to track the reduction in oxygen concentration in the sample upon irradiation by nanosecond laser light pulses. The GO sample was prepared using a modified Hummer’s method [5] and drop cast on a lacey carbon grid. The second harmonic from a Nd:YAG nanosecond pulsed laser (wavelength = 532 nm, repetition rate = 10 Hz, pulse duration = 11 ns) was aligned into the microscope and focused to a spot size of 100 μm on the sample. Laser pulse energy densities ranging from 3.18 to 15.9 mJ/cm² were systematically applied to investigate their impact on the reduction process. We utilized electron energy loss spectroscopy (EELS) to quantify the change in oxygen reduction with a collection angle of 12.7 mrad. The EELS acquisition time was 0.01 s for low-loss spectra and 5 s for the core-loss spectra. Multiple EELS spectra of Carbon and Oxygen K-edges were collected before and after laser irradiation to determine relative composition atomic percentages. Further, the log ratio method was used to determine the changes in the thickness of graphene oxide. Results from the experiments indicated a direct correlation between laser fluence and the reduction of oxygen atomic composition in GO. Higher laser fluence led to higher removal of oxygen, suggesting the importance of controlling this parameter for tailored graphene production. Further studies will be required to identify an optimal laser fluence for substantially reducing oxygen content in GO sheets without inducing ablation. In this presentation, we will showcase the trends observed while measuring the reduction of oxygen concentration and sample thickness as a function of laser fluence. We will also demonstrate how these quantities evolve as a function of laser exposure time which allows us to measure the kinetics of the GO photoreduction process. We will discuss the optimal laser parameters to produce high-quality rGO by photoreduction while minimizing material ablation. This information is important for the growing graphene manufacturing and application industries. Furthermore, this presentation exemplifies the kind of information that can be obtained by in situ laser irradiation TEM experiments.
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 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".