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Record W1964897738 · doi:10.1063/1.1819452

Simplified Besocke scanning tunneling microscope with linear approach geometry

2004· article· en· W1964897738 on OpenAlexafffund
S.J. Ball, G. E. Contant, A. B. McLean

Bibliographic record

VenueReview of Scientific Instruments · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCryostatMicroscopeScanning tunneling microscopeOpticsSample (material)Materials scienceScannerGeometryNanotechnologyPhysics

Abstract

fetched live from OpenAlex

Besocke-style scanning tunneling microscopes are used in low and variable temperature applications because they are compact and the tip-sample spacing is insensitive to thermal drift. It is demonstrated that the economical Besocke design can be simplified even further if a linear approach geometry is used. In this geometry, the sample has only to be moved along two orthogonal axes and just 11 wires are required to control both tip-sample approach and image acquisition. This simplifies the control electronics, increases the reliability of the microscope and, if the microscope is operated in a cryostat, it weakens the thermal link between low and room temperature. Nevertheless, all of the advantages of the Besocke design are retained including thermal compensation of the tip-sample spacing. A self-aligning mechanism is also described that automatically locates the sample relative to the scanner before tip-sample approach. This feature is particularly useful because the microscope is designed for remote operation in a cryostat where there is restricted visual access. Graphite was used as a test surface and images are presented of β-site corrugation and moiré supermeshes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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.

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

Citations8
Published2004
Admission routes2
Has abstractyes

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