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Record W4404297894 · doi:10.1002/anie.202413591

Engineering Stable Decomposition Products on Cathode Surfaces to Enable High Voltage All‐Solid‐State Batteries

2024· article· en· W4404297894 on OpenAlexafffund
Lanting Qian, Yangyang Huang, Ivan Kochetkov, Baltej Singh, Linda F. Nazar

Bibliographic record

VenueAngewandte Chemie International Edition · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaBASFBar Association of San Francisco
KeywordsElectrolyteCathodeMaterials scienceCoatingSulfideChemical engineeringConformal coatingAmorphous solidDecompositionNanotechnologyElectrodeMetallurgyChemistryOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Sulfide solid electrolytes such as Li 6 PS 5 Cl hold high promise for solid‐state batteries due to their high ionic conductivity; however, their oxidation potential of ~2.5 V is not compatible with high voltage Ni‐rich cathodes such as LiNi x Co y Mn 1−x−y O 2 (x≥0.8). Using guidance from density functional theory, we devise an effective, conformal, and thin coating on the cathode active material, which suppresses the oxidative decomposition of Li 6 PS 5 Cl as shown by experiment. The nanometric coating on nickel‐rich NMC85 enabled capacity retention of 82 % after 200 cycles (2.8–4.3 V vs Li + /Li) using Li 6 PS 5 Cl as the solid electrolyte. In comparison, cells with an uncoated CAM only displayed 56 % capacity retention. The coated‐NCM85 cells also demonstrate much better rate performance and higher capacity. The enhanced performance is due to the formation of a stable amorphous cathode‐electrolyte interphase accruing from the decomposition products of the LiPO 2 F 2 precursor (as predicted by DFT), which protect the sulfide electrolyte from oxidation. The coating fabricated in this cost‐effective process showed superior performance to state‐of‐the‐art coatings such as LiNbO 3 . This work highlights the importance of rationally designing stable coating materials based on their potential decomposition products and confirms the suitability of a low‐cost and conformal coating to enable sulfide electrolyte‐based all‐solid‐state 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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.010
GPT teacher head0.248
Teacher spread0.238 · 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 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

Citations16
Published2024
Admission routes2
Has abstractyes

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