High flow rate nanofluidics for <i>in-liquid</i> electron microscopy and diffraction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract We introduce a nanofluidic platform that can be used to carry out femtosecond electron diffraction (FED) and transmission electron microscopy (TEM) measurements in liquid samples or in-liquid specimens, respectively. The nanofluidic cell (NFC) system presented herein has been designed to withstand high sample refreshing rates (over one kilohertz), a prerequisite to succeed with FED experiments in our lab. Short beam paths, below 1 μ m, in combination with ultrathin membranes (less than 100 nm thick) are necessary conditions for in-liquid FED and TEM studies due to the strongly interacting nature of electrons. Depending on the application, the beam path in our NFC can be tuned between 50 nm and 10 μ m with ultrathin stoichiometric silicon nitride (Si 3 N 4 ) windows as thin as 20 nm. Stoichiometric Si 3 N 4 has been selected to reduce membrane bulging owing to its higher tensile stress and transparency in the UV–vis–NIR region to allow for laser excitation in FED experiments. Key design parameters and improvements made over previous NFC systems are discussed, and some preliminary electron images obtained by 200 kV scanning TEM are presented.
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.
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 | 0.000 | 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) | 0.000 | 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 it