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Record W2306951571 · doi:10.1149/ma2014-02/5/324

A Comparative Study of Sulphur-Containing Electrolyte Additives on the Reactivity Between Electrolytes and Charged Electrodes Using Accelerating Rate Calorimetry (ARC)

2014· article· en· W2306951571 on OpenAlexaff
Lin Ma, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldMaterials Science
TopicSolid-state spectroscopy and crystallography
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrolyteEthylene carbonateGraphiteElectrochemistryElectrodeInorganic chemistryFaraday efficiencyCalorimetryDiethyl carbonateChemistryMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Introduction Recently, electrolyte additives have attracted much attention because they can help improve the lifetime of lithium-ion batteries1,2. Among them, sulphur-containing electrolyte additives are very promising. For example, 1,3,2-dioxathiolane-2,2-dioxide (DTD)1 and prop-1-ene-1,3-sultone (PES)2 can help increase coulombic efficiency (CE) while 1,3,2-dioxathiane 2,2-dioxide (TMS)1 can limit gas production during formation. However, electrolyte additives may have an effect on Li-ion battery safety because these additives modify the interfaces between the electrode materials and the electrolyte. In this work, the reactivity of lithiated graphite or delithiated Li(Ni1/3Mn1/3Co1/3)O2 (NMC) with control electrolytes (1M LiPF6 ethylene carbonate (EC):ethyl methyl carbonate (EMC) 3:7 wt% ratio) or electrolytes containing several sulphur-containing additives was studied, respectively, using accelerating rate calorimetry (ARC). Experimental The ARC sample preparation process was similar to that reported before3. 2325 coin type pellet cells were made using control electrolyte and charged to 4.2 V for the NMC electrodes or discharged to 0.0 V for the graphite electrodes using the protocol described in Reference 3. The ratios between charged electrode materials and electrolyte were 94 mg:30 mg and 140 mg:140 mg for NMC electrodes and graphite electrodes, respectively. The single-point BET surface areas of the graphite and NMC powders were measured with a Micromeritics Flowsorb 2300 instrument. Results and Discussion Table 1 shows the specific surface area results for the NMC and graphite materials used in this experiment. Figure 1 shows the molecular structures of the electrolyte additives were used in this experiment. Figure 2 shows the self-heating rate (SHR) versus temperature for the reaction of lithiated graphite or delithiated NMC with different electrolyte additives. Although there is a short-lived exothermic observation at 50°C, 5% DTD decreases the SHR for lithiated graphite. TMS causes a small exothermic peak at around 75°C but the SHR is very small. Both 5% DTD and 5% TMS help eliminate the exothermic peak at around 100°C resulting from the decomposition of metastable solid electrolyte interface (SEI)4. Furthermore, 2% PES does not dramatically increase the reactivity of the delithiated NMC with electrolyte from the starting temperature to around 250°C and PES helps decrease the SHR compared with the control electrolyte after 250°C. Further experiments showing the impact of these additives in combination with other additives like VC will be reported. In summary, some sulphur-containing electrolyte additives which show good electrochemical performance, such as DTD, TMS etc., should not compromise the safety of lithium-ion batteries. References 1. J. Xia, N. N. Sinha, L. P. Chen, and J. R. Dahn, J. Electrochem. Soc., 161, A264–A274 (2014). 2. J. Xia, L. Ma, C. P. Aiken, K. J. Nelson, L. P. Chen and J. R. Dahn, submitted for publication. 3. J. Jiang, K. W. Eberman, L. J. Krause, and J. R. Dahn, J. Electrochem. Soc., 152, A1879–A1889 (2005). 4. M. N. Richard and J. R. Dahn, J. Electrochem. Soc., 146, 2068–2077 (1999).

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.299
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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