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Record W2770596809 · doi:10.1116/1.5010814

Batch fabrication of AFM probes with direct positioning capability

2017· article· en· W2770596809 on OpenAlexaff
Shuo Zheng, Chenxu Zhu, Ripon Kumar Dey, Bo Cui

Bibliographic record

VenueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCantileverWaferShadow maskFabricationPyramid (geometry)Etching (microfabrication)Materials scienceOpticsAtomic force microscopyNanotechnologyOptoelectronicsSiliconScanning probe microscopyLayer (electronics)PhysicsComposite material

Abstract

fetched live from OpenAlex

One major problem for most commercial atomic force microscope (AFM) probes is the uncertainty of the tip location relative to its cantilever. In most scenarios, AFM probes have tips 5–25 μm away from the very end of the cantilever, and it is thus impossible to know where exactly the tip is because the camera in an AFM system shows only the backside of the AFM cantilever. This uncertainty of the tip location has raised some major problems, e.g., the initial scanning area must be set very large to ensure that the area of interest is within the scanning field. Here, the authors will show a straightforward fabrication method that can convert a wafer of regular pyramidal-shaped probes into direct positioning probes, for which the tip is located either at the very end of its cantilever or next to a through-cantilever hole that is visible when viewed from the backside of the cantilever. Our method involves angle evaporation of a hard mask layer onto the AFM probe, followed by dry etching of silicon that etches the area not covered by the metal layer, i.e., the shadow area of the pyramid-shaped tip. As an additional benefit, because our process etched away half of the tip pyramid, the resulting tip is sharper with a smaller half cone angle than the original one, leading to higher resolution imaging.

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)0.001
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 score0.025
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and PhenomenaSame topicForce Microscopy Techniques and ApplicationsFrench-language works237,207