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Record W4413325432 · doi:10.1016/j.micron.2025.103896

Study of gas-based charge compensation in an open-cell environmental TEM by off-axis electron holography

2025· article· en· W4413325432 on OpenAlexaff
Makoto Schreiber, Cathal Cassidy

Bibliographic record

VenueMicron · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersOkinawa Institute of Science and Technology Graduate University
KeywordsElectron holographyMaterials scienceCompensation (psychology)Charge (physics)HolographyOptoelectronicsOpticsNanotechnologyTransmission electron microscopyPhysicsPsychology

Abstract

fetched live from OpenAlex

Under electron bombardment, electrically insulating samples accumulate a net charge which can adversely affect measurements in electron microscopy. Here, we present a preliminary study on gas-based charge compensation in TEM quantified through off-axis electron holography. Based on the present data, it appears that the introduction of a gas flow reversibly reduces the degree of charge buildup and fluctuations on a dielectric sample. The use of gas may thus allow for the study of samples which would normally be strongly distorted, unstable, or damaged by the charging process; as well as further studies of the charging process itself. However, as the present results were obtained with low spatial resolution Lorentz optics and second-scale time resolutions, we caution that the effectiveness of gas-based charge compensation for high spatial and temporal resolutions is not yet demonstrated.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.302
Teacher spread0.297 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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