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Record W3130328214 · doi:10.1139/cjp-2020-0433

Adsorption and diffusion of Li/Na atom on blue phosphorene with defects by first-principles calculations

2021· article· en· W3130328214 on OpenAlexvenueno aff
Ji Zhang, Daojun Liu

Bibliographic record

VenueCanadian Journal of Physics · 2021
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsPhosphoreneIonDiffusionAdsorptionLithium (medication)AnodeAtom (system on chip)Chemical physicsPhysicsAtomic physicsMolecular physicsBand gapOptoelectronicsPhysical chemistryChemistryThermodynamicsElectrode

Abstract

fetched live from OpenAlex

Two-dimensional materials such as blue phosphorene (BlueP) as a substitute for conventional anode materials in lithium-ion batteries (LIBs) and sodium-ion batteries (SIBs) have garnered significant attention recently because of their large surface areas, ultrafast intrinsic carrier mobilities, and shorter ion diffusion paths. In this study, the adsorption and diffusion properties of Li and Na ions on BlueP with defects are investigated through first-principles calculations. The calculations show that the adsorption energy increased from −0.64 to −1.50 eV for Li and from −0.72 to −1.61 eV for Na because of defects. Moreover, the defects resulted in middle bands in the density of states of BlueP, indicating enhanced electron localization. This may contribute to an increase in binding energies. However, it is discovered that Li and Na ion diffusion on the surface of BlueP with defects involves a larger migration energy barrier than Li and Na on pristine BlueP, which is disadvantageous to BlueP as a battery anode.

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 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 score0.011
Threshold uncertainty score0.258

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)0.0000.000

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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