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2019· article· lv· W2898735983 on OpenAlexafffund
Aris Chatzichristos, Ryan M. L. McFadden, Martin H. Dehn, S. R. Dunsiger, Derek Fujimoto, Victoria L. Karner, Iain McKenzie, G. D. Morris, M. R. Pearson, Monika Stachura, Jun Sugiyama, John O. Ticknor, W. A. MacFarlane, R. F. Kiefl

Bibliographic record

VenuePhysical Review Letters · 2019
Typearticle
Languagelv
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsTRIUMFSimon Fraser UniversityUniversity of British Columbia
FundersJapan Society for the Promotion of ScienceNational Research Council CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsArrhenius equationDiffusionTrappingThermal diffusivityMaterials scienceRutileAnalytical Chemistry (journal)Surface (topology)PhysicsThermodynamicsPhysical chemistryActivation energyChemistryGeometry

Abstract

fetched live from OpenAlex

We report measurements of the diffusion rate of isolated ion-implanted ^{8}Li^{+} within ∼120 nm of the surface of oriented single-crystal rutile TiO_{2} using a radiotracer technique. The α particles from the ^{8}Li decay provide a sensitive monitor of the distance from the surface and how the depth profile of ^{8}Li evolves with time. The main findings are that the implanted Li^{+} diffuses and traps at the (001) surface. The T dependence of the diffusivity is described by a bi-Arrhenius expression with activation energies of 0.3341(21) eV above 200 K, whereas at lower temperatures it has a much smaller barrier of 0.0313(15) eV. We consider possible origins for the surface trapping, as well the nature of the low-T barrier.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.071
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0710.027

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 head0.017
GPT teacher head0.242
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 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
Published2019
Admission routes2
Has abstractyes

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Same venuePhysical Review Letters→Same topicAdvancements in Battery Materials→French-language works237,207→