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Record W4404412707 · doi:10.26434/chemrxiv-2024-q6h89

A facile route to plastic inorganic electrolytes for all-solid state batteries based on molecular design

2024· preprint· en· W4404412707 on OpenAlexaff
Insang You, Baltej Singh, Mengyang Cui, Gillian R. Goward, Lanting Qian, Zachary Arthur, Graham King, Linda F. Nazar

Bibliographic record

VenueChemRxiv · 2024
Typepreprint
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsCanadian Light Source (Canada)McMaster UniversityUniversity of Waterloo
FundersBASF
KeywordsSolid-stateElectrolyteQuasi-solidMaterials scienceNanotechnologyFast ion conductorState (computer science)Chemical engineeringComputer scienceChemistryEngineeringEngineering physicsElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Solid-state lithium batteries are on the threshold of commercialization as an alternative to liquid electrolyte batteries. Glassy or amorphous solid electrolytes could bring crucial benefits, but their lack of periodicity impedes structure-derived material design. Here, we report an approach for glassy electrolyte design based on well-defined lithium metal oxychloride linear oligomers. By packing these oligomers formed by oxygen-bridged chloroaluminates, a glassy solid model is constructed. Li ions in mixed-anion coordination with distorted polyhedra favor good lithium conductivity (1.3 mS.cm-1 at 30 °C). The frustrated Li-ion geometry and non-crystallinity promote conformational dynamics of the oligomer backbone that generates mechanical plasticity. Ab-initio molecular dynamics simulations depict the conformational motion that resembles that of organic molecules. Our all-solid-state battery based on this solid electrolyte shows exceptional long term electrochemical stability with a high-nickel NCM cathode. This work shows the impact of targeted structure models for rational design of glassy plastic 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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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