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Record W2110416771 · doi:10.1002/anie.201410376

The Emerging Chemistry of Sodium Ion Batteries for Electrochemical Energy Storage

2015· article· en· W2110416771 on OpenAlexaff
Dipan Kundu, Elahe Talaie, Victor Duffort, Linda F. Nazar

Bibliographic record

VenueAngewandte Chemie International Edition · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsEnergy storageRenewable energyLithium (medication)ElectricityElectrochemistryEnvironmental scienceProcess engineeringNanotechnologyEngineeringPower (physics)Materials scienceElectrical engineeringChemistryPhysics

Abstract

fetched live from OpenAlex

Energy storage technology has received significant attention for portable electronic devices, electric vehicle propulsion, bulk electricity storage at power stations, and load leveling of renewable sources, such as solar energy and wind power. Lithium ion batteries have dominated most of the first two applications. For the last two cases, however, moving beyond lithium batteries to the element that lies below-sodium-is a sensible step that offers sustainability and cost-effectiveness. This requires an evaluation of the science underpinning these devices, including the discovery of new materials, their electrochemistry, and an increased understanding of ion mobility based on computational methods. The Review considers some of the current scientific issues underpinning sodium ion batteries.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.003

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 head0.247
Teacher spread0.235 · 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
GenreReview

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

Citations2,054
Published2015
Admission routes1
Has abstractyes

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