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Record W1579824169 · doi:10.1063/1.4926489

Field evaporation of ZnO: A first-principles study

2015· article· en· W1579824169 on OpenAlexafffund
Yu Xia, Markus Karahka, H. J. Kreuzer

Bibliographic record

VenueJournal of Applied Physics · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Materials Characterization Techniques
Canadian institutionsDalhousie University
FundersOffice of Naval ResearchCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsAtom probePolarizabilityDielectricField strengthElectric fieldField (mathematics)EvaporationCluster (spacecraft)SemiconductorAtom (system on chip)Materials scienceField electron emissionDensity functional theoryInsulator (electricity)Condensed matter physicsChemical physicsChemistryAtomic physicsNanotechnologyComputational chemistryPhysicsMoleculeOptoelectronicsThermodynamicsElectron

Abstract

fetched live from OpenAlex

With recent advances in atom probe tomography of insulators and semiconductors, there is a need to understand high electrostatic field effects in these materials as well as the details of field evaporation. We use density functional theory to study field effects in ZnO clusters calculating the potential energy curves, the local field distribution, the polarizability, and the dielectric constant as a function of field strength. We confirm that, as in MgO, the HOMO-LUMO gap of a ZnO cluster closes at the evaporation field strength signaling field-induced metallization of the insulator. Following the structural changes in the cluster at the evaporation field strength, we can identify the field evaporated species, in particular, we show that the most abundant ion, Zn2+, is NOT post-ionized but leaves the surface as 2+ largely confirming the experimental observations. Our results also help to explain problems related to stoichiometry in the mass spectra measured in atom probe tomography.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.256
Teacher spread0.225 · 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 designSimulation or modeling
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

Citations33
Published2015
Admission routes2
Has abstractyes

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