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Record W4400780521 · doi:10.1088/1361-648x/ad61af

Strain-induced enhancement of surface self-diffusion on strontium titanate (001) surfaces

2024· article· en· W4400780521 on OpenAlexafffund
Daniel Gueckelhorn, Alfred Kersch, Andreas Ruëdiger

Bibliographic record

VenueJournal of Physics Condensed Matter · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStrontium titanateDiffusionMaterials scienceSelf-diffusionStrontiumSurface diffusionUltimate tensile strengthActivation energyStrain (injury)Density functional theoryDiffusion barrierChemical physicsComposite materialCondensed matter physicsNanotechnologyThin filmPhysical chemistryThermodynamicsChemistryComputational chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract We present a numerical investigation of self-diffusion on strontium titanate TiO 2 -terminated (001) surfaces via density functional theory. Our calculations first indicate that Ti has the highest diffusion barrier with approximately 2.20 eV, thus representing the rate-limiting step for surface self-diffusion. Furthermore, the higher energy barriers of O and Ti in comparison to O 2 and TiO 2 indicate electronic activity with the surface atoms. Under the consideration of equi-biaxial strain as it would be encountered in e.g. heteroepitaxial thin films, the diffusion barriers for surface self-diffusion decrease for both compressive and tensile strains between −6% and 2%. For larger strains, we observe plastic deformations. This possibility to lower the energy barrier paves the way for accelerated and possible new mechanisms of surface diffusion and reconstruction of strontium titanate structures in a wide range of applications.

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 categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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