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Record W3083991890 · doi:10.1039/d0cp02946g

Materials perspective on new lithium chlorides and bromides: insights into thermo-physical properties

2020· article· en· W3083991890 on OpenAlexafffund
Ming Jiang, Sankha Mukherjee, Zhiwen Chen, Li Xin Chen, Meng Lu Li, Hai Yan Xiao, Chan Gao, Chandra Veer Singh

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsHalideElectrolyteCompatibility (geochemistry)Materials scienceElectrodeLithium (medication)Shear (geology)Composite materialInorganic chemistryChemical engineeringNanotechnologyChemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Recently, a new class of lithium chlorides and bromides (e.g., Li3YCl6 and Li3YBr6) were reported to be promising solid-state electrolytes with high ionic conductivity in all-solid-state battery cells. However, their response under mechanical loading is not known which is critical as mechanical properties can play a pivotal role in reducing interfacing resistance between electrolytes and electrodes. To address this issue, herein, we report the thermo-physical properties of these lithium chlorides and bromides using density functional theory calculations. It was found that the new structures possess relatively larger shear moduli than those of thio-phosphate-type solid-state electrolytes and smaller Young's moduli than those of Garnet-type solid-state electrolytes. This suggests that the new halide materials can be more effective in suppressing the formation of lithium dendrites, accommodating volumetric changes of electrode materials and preventing their own degradation. Meanwhile, Poisson's ratio and Pugh's indicator calculations showed that Li3YCl6 and Li3ScCl6 possess improved ductility than other halide candidates, and thus hold promise as solid-state electrolytes. On the other hand, owing to their relatively high thermal conductivities, lithium bromides were found to be more advantageous in conducting heat which is important to ensure safety. These results provide fundamental insights into the mechanical properties of lithium chlorides and bromides and contribute to the rational mechanical design of solid-state electrolytes and the development advanced 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 categoriesMeta-epidemiology (narrow)
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 score0.052
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
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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 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

Citations33
Published2020
Admission routes2
Has abstractyes

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