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Record W3112130757 · doi:10.1017/s1431927620024654

Environmental Liquid Cell Technique for Improved Electron Microscopic Imaging of Soft Matter in Solution

2020· article· en· W3112130757 on OpenAlex
Sana Azim, Lindsey A. Bultema, Michiel B. De Kock, Ernesto Rafael Osorio‐Blanco, Marcelo Calderón, Josef Gonschior, Jan-Philipp Leimkohl, Friedjof Tellkamp, Robert Bücker, Eike C. Schulz, Sercan Keskin, Niels de Jonge, Günther Kassier, R. J. Dwayne Miller

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicroscopy and Microanalysis · 2020
Typearticle
Languageen
FieldEngineering
TopicCharacterization and Applications of Magnetic Nanoparticles
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceTransmission electron microscopyPolystyreneLayer (electronics)Soft matterElectronScanning electron microscopeAnalytical Chemistry (journal)Composite materialOpticsNanotechnologyChemistryChromatography

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.199
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it