Environmental Liquid Cell Technique for Improved Electron Microscopic Imaging of Soft Matter in Solution
Bibliographic record
Abstract
Liquid-phase transmission electron microscopy is a technique for simultaneous imaging of the structure and dynamics of specimens in a liquid environment. The conventional sample geometry consists of a liquid layer tightly sandwiched between two Si3N4 windows with a nominal spacing on the order of 0.5 μm. We describe a variation of the conventional approach, wherein the Si3N4 windows are separated by a 10-μm-thick spacer, thus providing room for gas flow inside the liquid specimen enclosure. Adjusting the pressure and flow speed of humid air inside this environmental liquid cell (ELC) creates a stable liquid layer of controllable thickness on the bottom window, thus facilitating high-resolution observations of low mass-thickness contrast objects at low electron doses. We demonstrate controllable liquid thicknesses in the range 160 ± 34 to 340 ± 71 nm resulting in corresponding edge resolutions of 0.8 ± 0.06 to 1.7 ± 0.8 nm as measured for immersed gold nanoparticles. Liquid layer thickness 40 ± 8 nm allowed imaging of low-contrast polystyrene particles. Hydration effects in the ELC have been studied using poly-N-isopropylacrylamide nanogels with a silica core. Therefore, ELC can be a suitable tool for in situ investigations of liquid specimens.
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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) | 0.001 | 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 | 0.001 | 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".