MétaCan
Menu
Back to cohort

Review on Air Cathode in Li-Air Batteries

2013· article· en· W3141886651 on OpenAlexvenueno aff
Zhaoru Zha, Cai Shen, Deyu Wang, Wei‐Qiang Han

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsnot available
FundersNingbo Institute of Materials Technology and Engineering, Chinese Academy of SciencesRecruitment Program of Global ExpertsNational Natural Science Foundation of China
KeywordsCathodeElectrical engineeringAutomotive engineeringEnvironmental scienceMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Lithium-air (Li-air) battery is a promising electrochemical system with unprecedented high energy density. However, many problems and challenges prevent its wide scale application and commercialization. Low oxygen diffusion rates and large voltage gap are two of the main problems in Li-air battery. These two problems are related to the materials used in the air cathode such as porous carbon materials and metallic catalysts. This review seeks to discuss various materials used in the air cathode for Li air batteries. Mechanism of reaction in air cathode will be elucidated and discussed.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.011
GPT teacher head0.251
Teacher spread0.241 · 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 designNot applicable
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

Citations3
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Technology Innovations in Renewable EnergySame topicRecycling and Waste Management TechniquesFrench-language works237,207