MétaCan
Menu
Back to cohort
Record W2326019226 · doi:10.1021/jp408717x

Impact of Lithium Bis(oxalate)borate Electrolyte Additive on the Performance of High-Voltage Spinel/Graphite Li-Ion Batteries

2013· article· en· W2326019226 on OpenAlexafffund
Nicholas P. W. Pieczonka, Li Yang, Michael P. Balogh, Bob R. Powell, Katharine R. Chemelewski, Arumugam Manthiram, Sergey Krachkovskiy, Gillian R. Goward, Minghong Liu, Jung‐Hyun Kim

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Battery Materials
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaGeneral Motors of CanadaUniversity of Texas at AustinMcMaster UniversityU.S. Department of Energy
KeywordsElectrolyteGraphiteFaraday efficiencySpinelLithium (medication)DissolutionInorganic chemistryOxalateChemistryAnodeCathodeBoronElectrodeMaterials scienceMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

The impact of lithium bis(oxalate)borate (LiBOB) electrolyte additive on the performance of full lithium-ion cells pairing the high-voltage spinel cathode with the graphite anode was systematically investigated. Adding 1 wt % LiBOB to the electrolyte significantly improved the cycle life and Coulombic efficiency of the full-cells at 30 and 45 °C. As the LiBOB was preferentially oxidized and reduced compared with LiBOB-free electrolyte during cycling, their relative contributions to the improved capacity retention in full-cells was gauged by pairing fresh and LiBOB-treated electrodes with various combinations. The results indicated that a solid–electrolyte interphase (SEI) film on graphite produced by the reduction of the LiBOB additive is more robust and stable against Mn dissolution problem during cycling at 45 °C compared with the SEI formed by the reduction of the base (LiBOB-free) electrolyte. In addition, a 3 wt % LiBOB-added electrolyte showed reduced Mn dissolution compared with the base electrolyte after storing the fully charged Li 1– x Ni 0.42 Fe 0.08 Mn 1.5 O 4 (LNFMO) electrodes at 60 °C for one month. It is believed that LiBOB aids in stabilizing the electrolyte by trapping the PF 5, i.e., sequestering the radical which tends to oxidize EC and DEC electrolyte solvents. Thus, oxidation is suppressed on the carbon black particles in the positive electrode, as evidenced by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR) analyses. As a result, HF generation is suppressed, which in turn results in less Mn dissolution from the spinel cathode.

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 score0.012
Threshold uncertainty score0.449

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 head0.005
GPT teacher head0.220
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

Citations176
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry CSame topicAdvancements in Battery MaterialsFrench-language works237,207