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Record W4294897884 · doi:10.1126/sciadv.adc9516

Prospects of halide-based all-solid-state batteries: From material design to practical application

2022· review· en· W4294897884 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience Advances · 2022
Typereview
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsHalideMaterials scienceBattery (electricity)NanotechnologyLithium (medication)Ionic conductivityFast ion conductorElectrolyteChemistryPhysicsElectrodeInorganic chemistry

Abstract

fetched live from OpenAlex

The safety of lithium-ion batteries has caused notable concerns about their widespread adoption in electric vehicles. A nascent but promising approach to enhancing battery safety is using solid-state electrolytes (SSEs) to develop all-solid-state batteries, which exhibit unrivaled safety and superior energy density. A new family of SSEs based on halogen chemistry has recently gained renewed interest because of their high ionic conductivity, high-voltage stability, good deformability, and cost-effective and scalable synthesis routes. Here, we provide a comprehensive review of halide SSEs concerning their crystal structures, ion transport kinetics, and viability for mass production. Furthermore, their moisture sensitivity and interfacial challenges are summarized with corresponding effective strategies. Last, halide-based all-solid-state Li-ion and Li-S pouch cells with energy density targets of 400 and 500 Wh kg −1 are projected to guide future endeavors. This work serves as a comprehensive guideline for developing halide SSEs from material design to practical application.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.052
GPT teacher head0.353
Teacher spread0.301 · 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