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Record W4411874622 · doi:10.1038/s41467-025-60711-7

The urgent electrolyte sustainability challenges for electric vehicle batteries

2025· review· en· W4411874622 on OpenAlexafffund
Tobias Burton, Juan Luis Gómez‐Urbano, Yachao Zhu, Andrea Balducci, Olivier Fontaine

Bibliographic record

VenueNature Communications · 2025
Typereview
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversité de Montréal
FundersUniversité de MontréalEuropean CommissionVidyasirimedhi Institute of Science and Technology
KeywordsSustainabilityElectric vehicleElectrolyteBusinessComputer scienceChemistryBiologyPhysicsEcology

Abstract

fetched live from OpenAlex

At a time when society is moving towards electric transport to replace gasoline-powered cars, lithium-ion battery electrolytes are a black box in terms of their production and the raw materials they are made from. This article puts into perspective the urgent need to find alternatives to conventional electrolytes based on fluorinated salts in carbonate solvents. As the adoption of electric vehicles continues to grow, the production and raw materials of lithium-ion battery electrolytes deserve further scrutiny. Here, authors share their perspective on the need to find alternatives to traditional carbonate solvent and fluorinated salt-based electrolytes.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0010.003
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 head0.037
GPT teacher head0.375
Teacher spread0.338 · 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.

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

Citations21
Published2025
Admission routes2
Has abstractyes

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