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Record W2073001815 · doi:10.1093/jmicro/dfr087

Electron interference from an amorphous thin film on a crystal transmission electron microscopy specimen

2011· article· en· W2073001815 on OpenAlexaff
Rodney Herring, Koh Saitoh, Takayoshi Tanji, Nobuo Tanaka

Bibliographic record

VenueJournal of Electron Microscopy · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsOpticsAmorphous solidCrystal (programming language)Transmission electron microscopyElectron diffractionMaterials scienceDiffractionBragg's lawInterference (communication)Reflection high-energy electron diffractionPhysicsChemistryCrystallography

Abstract

fetched live from OpenAlex

The electron intensity of a beam from an amorphous surface layer on a crystal transmission electron microscopy (TEM) specimen has been found to have sufficient coherence to produce fringes in interferograms, created by interfering two electron diffracted beams from the crystal, using a method of electron interference referred to as diffracted beam interferometry. This interference method involves amplitude splitting of the electron beam by means of a crystal with a thin amorphous layer on its surface. The amorphous intensity is transferred along with the crystal's Bragg diffracted beams and is then self-interfered when the crystal's Bragg diffracted beams are interfered by an electron biprism. The interference fringes in the interferograms exist in low to high electron scattering angles. The spatial frequency of the amorphous intensity fringes depends on the Bragg angle of the crystal's interfered diffracted beams. It is shown that the absolute phase of the amorphous intensity is possibly obtained using a Cs-corrected TEM and two interfering diffracted beams having equal but opposite phases. This method of interference is a good step towards measuring the phase of amorphous materials that is useful in determining their complex atomic structures.

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 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 categoriesMeta-epidemiology (narrow)
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 score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.325
Teacher spread0.315 · 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 teacher head, not a consensus.

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

Citations6
Published2011
Admission routes1
Has abstractyes

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