Studying Nanomaterial Transformations in the Movie-Mode Dynamic Transmission Electron Microscope at INRS
Bibliographic record
Abstract
The dynamic transmission electron microscope (DTEM) belongs to the class of high-speed pulsed beam electron microscopes that have been developed to study phase transformations materials at the nanoscale [1]. The DTEM stands out from other instruments in its capability to capture nanosecond single-shot images, which has allowed for studies of irreversible transformations like rapid crystallization [2-4], transitent structural ordering [5] and photoreduction. [6] Furthermore, the movie-mode DTEM (MM-DTEM) has been developed to capture a series of images at megahertz framerates for insights into the kinetics of such stochastic events [7, 8]. The MM-DTEM at INRS is based on a JEOL® 2100Plus electron microscope that was modified to couple in the fourth harmonic of a Nd:YAG IDES® cathode laser ( λ = 266nm ) to generate high-charge electron pulses via photoemission. This design is different than other DTEMs, which oftern use the fifth harmonic. Furthermore, this instrument consists of a Northurp Grumann Nd:YAG nanosecond pump laser and a Gatan Image Filter (GIF) system, enabling the full characterization of laser induced transformations by combining nanosecond time-resolved imaging, diffraction, and electron energy loss spectroscopy measurements. This work will give a survey of the operational performance of this novel instrument including trends in photoemission yield, electron energy distribution and imaging resolution as a function of cathode laser pulse energy. Furthermore, a demonstration of the movie-mode capabilities studying laser sintering of nanoparticles is planned. Finally, future experimental studies of nanomaterial transformations in different environments, such as temperature or applied electric field, by coupling this system with available in situ sample holders will be discussed.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".