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Record W2594565882 · doi:10.1021/acs.jpcc.7b01922

In Situ NMR Observation of the Temporal Speciation of Lithium Sulfur Batteries during Electrochemical Cycling

2017· article· en· W2594565882 on OpenAlexaff
Hao Wang, Niya Sa, Meinan He, Xiao Liang, Linda F. Nazar, Mahalingam Balasubramanian, Kevin G. Gallagher, Baris Key

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsUniversity of Waterloo
FundersBasic Energy SciencesU.S. Department of Energy
KeywordsPolysulfideDisproportionationSulfurElectrochemistryLithium (medication)DissolutionElectrolyteAnodeInorganic chemistryChemistryIn situPrecipitationElectrodeMaterials scienceOrganic chemistryCatalysisPhysical chemistry

Abstract

fetched live from OpenAlex

The understanding of the reaction mechanism and temporal speciation of the lithium–sulfur batteries is challenged by complex polysulfide disproportionation chemistry coupled with the precipitation and dissolution of species. In this report, for the first time, we present a comprehensive method to investigate lithium sulfur electrochemistry using in situ 7 Li NMR spectroscopy, a technique that is capable of quantitatively capturing the evolution of the soluble and precipitated lithium (poly)sulfides during electrochemical cycling. Through deconvolution and quantification, every lithium-bearing species was closely tracked and four-step soluble lithium polysulfide-mediated lithium sulfur electrochemistry was demonstrated in never before seen detail. Significant irreversible accumulation of Li 2 S is observed on the Li metal anode after four cycles because of sulfur shuttling. The application of the method presented here to study electrolyte/additive development and lithium protection research can be readily envisaged.

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 score0.016
Threshold uncertainty score0.191

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 head0.009
GPT teacher head0.224
Teacher spread0.214 · 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

Citations56
Published2017
Admission routes1
Has abstractyes

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