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Record W4319996545 · doi:10.1016/j.isci.2023.105982

Anode-free sodium metal batteries as rising stars for lithium-ion alternatives

2023· review· en· W4319996545 on OpenAlexafffund
Tingzhou Yang, Dan Luo, Yizhou Liu, Aiping Yu, Zhongwei Chen

Bibliographic record

VenueiScience · 2023
Typereview
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsUniversity of Waterloo
FundersWaterloo Institute for Nanotechnology, University of WaterlooUniversity of WaterlooNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsAnodeCarbon footprintLithium (medication)SustainabilityEconomic shortageEnergy storageEnvironmental scienceMaterials scienceNanotechnologyNatural resource economicsGreenhouse gasEnvironmental economicsWaste managementProcess engineeringEngineeringChemistryEconomicsPhysicsGovernment (linguistics)

Abstract

fetched live from OpenAlex

With the impact of the COVID-19 lockdown, global supply chain crisis, and Russo-Ukrainian war, an energy-intensive society with sustainable, secure, affordable, and recyclable rechargeable batteries is increasingly out of reach. As demand soars, recent prototypes have shown that anode-free configurations, especially anode-free sodium metal batteries, offer realistic alternatives that are better than lithium-ion batteries in terms of energy density, cost, carbon footprint, and sustainability. This Perspective explores the current state of research on improving the performance of anode-free Na metal batteries from five key fields, as well as the impact on upstream industries compared to commercial 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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.071
GPT teacher head0.352
Teacher spread0.282 · 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 designNot applicable
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

Citations103
Published2023
Admission routes2
Has abstractyes

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