MétaCan
Menu
Back to cohort
Record W2060579551 · doi:10.1103/physrevb.70.085415

<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mi mathvariant="normal">Sr</mml:mi><mml:mi mathvariant="normal">Ti</mml:mi><mml:msub><mml:mi mathvariant="normal">O</mml:mi><mml:mn>3</mml:mn></mml:msub><mml:mrow><mml:mo>(</mml:mo><mml:mn>001</mml:mn><mml:mo>)</mml:mo></mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mn>2</mml:mn><mml:mo>×</mml:mo><mml:mn>1</mml:mn><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math>reconstructions: First-principles calculations of surface energy and atomic structure compared with scanning tunneling microscopy images

2004· article· lv· W2060579551 on OpenAlexfundno aff
Karen Johnston, Martin R. Castell, A. T. Paxton, Michael W. Finnis

Bibliographic record

VenuePhysical Review B · 2004
Typearticle
Languagelv
FieldMaterials Science
TopicElectronic and Structural Properties of Oxides
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilQueen's UniversityDepartment for Employment and Learning, Northern Ireland
KeywordsPhysicsCrystallographyCombinatoricsMathematicsChemistry

Abstract

fetched live from OpenAlex

$(1\ifmmode\times\else\texttimes\fi{}1)$ and $(2\ifmmode\times\else\texttimes\fi{}1)$ reconstructions of the (001) $\mathrm{Sr}\mathrm{Ti}{\mathrm{O}}_{3}$ surface were studied using the first-principles full-potential linear muffin-tin orbital method. Surface energies were calculated as a function of $\mathrm{Ti}{\mathrm{O}}_{2}$ chemical potential, oxygen partial pressure ${p}_{{\mathrm{O}}_{}2}$and temperature. The $(1\ifmmode\times\else\texttimes\fi{}1)$ unreconstructed surfaces were found to be energetically stable for many of the conditions considered. Under conditions of very low oxygen partial pressure the $(2\ifmmode\times\else\texttimes\fi{}1)$ ${\mathrm{Ti}}_{2}{\mathrm{O}}_{3}$ reconstruction [Martin R. Castell, Surf. Sci. 505, 1 (2002)] is stable. The question as to why STM images of the $(1\ifmmode\times\else\texttimes\fi{}1)$ surfaces have not been obtained was addressed by calculating charge densities for each surface. These suggest that the $(2\ifmmode\times\else\texttimes\fi{}1)$ reconstructions would be easier to image than the $(1\ifmmode\times\else\texttimes\fi{}1)$ surfaces. The possibility that the presence of oxygen vacancies would destabilise the $(1\ifmmode\times\else\texttimes\fi{}1)$ surfaces was also investigated. If the $(1\ifmmode\times\else\texttimes\fi{}1)$ surfaces are unstable then there exists the further possibility that the $(2\ifmmode\times\else\texttimes\fi{}1)$ DL-$\mathrm{Ti}{\mathrm{O}}_{2}$ reconstruction [Natasha Erdman et al. Nature (London) 419, 55 (2002)] is stable in a $\mathrm{Ti}{\mathrm{O}}_{2}$-rich environment and for ${p}_{{\mathrm{O}}_{2}}>{10}^{\ensuremath{-}18}$ atm.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.581
Threshold uncertainty score0.598

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.5810.387

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 head0.016
GPT teacher head0.243
Teacher spread0.227 · 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.

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

Citations167
Published2004
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Review BSame topicElectronic and Structural Properties of OxidesFrench-language works237,207