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Record W2129429806 · doi:10.1039/c4nr00804a

Aluminum based sulfide solid lithium ionic conductors for all solid state batteries

2014· article· en· W2129429806 on OpenAlexaff
K. Karthikeyan, K. J. Kim, Y. G. Lee, Y. S. Lee

Bibliographic record

VenueNanoscale · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsWestern University
Fundersnot available
KeywordsIonic conductivityElectrolyteLithium (medication)Materials scienceFast ion conductorElectrochemistryIonic bondingCyclic voltammetryConductivityActivation energyInorganic chemistrySulfideAnalytical Chemistry (journal)Chemical engineeringIonChemistryElectrodePhysical chemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

The present work focuses on the synthesis of lithium ionic conductors based on a Li2S-Al2S3-GeS-P2S5 system due to the high ionic conductivity exhibited by the constituents of this system. Mechanical milling for a short duration and a single step heat treatment at a moderate temperature of 550 °C resulted in crystalline powders with high lithium ionic conductivity at room temperature that are comparable to the organic liquid electrolytes. The effect of various aluminum to germanium ratios was studied. Among the samples containing Al : Ge, the ratio of 30 : 70 was found to show high ionic conductivities of 1.7 × 10(-3) S cm(-1) at 25 °C and ∼ 6 × 10(-3) S cm(-1) at 100 °C equivalent. The activation energy of this material was significantly less (Ea = 17 kJ mol(-1)), which can be considered to be the best value among solid electrolytes. The electrochemical stability was analyzed using cyclic voltammetry between -0.3 and 5.0 V and it was found that the voltammetric profile was smooth without any additional current response, due to electrolyte decomposition, or any other side reaction, except a pair of lithium deposition and stripping peaks.

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 score0.065
Threshold uncertainty score0.859

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 communication0.0000.000
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 head0.014
GPT teacher head0.246
Teacher spread0.232 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

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