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Record W2301156041 · doi:10.1149/ma2014-02/5/441

The Effect of Intentionally Added Water on Gas Evolution in Li-Ion Pouch Cells

2014· article· en· W2301156041 on OpenAlexaff
Deijun Xiong, Rémi Petibon, John C. Burns, J. R. Dahn

Bibliographic record

VenueECS Meeting Abstracts · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsElectrolyteChemistryVolume (thermodynamics)Chemical engineeringMaterials scienceElectrode

Abstract

fetched live from OpenAlex

Introduction Water is widely regarded as having a detrimental effect on cell performance so Li-ion battery electrolyte normally has a water content below 50 ppm (1). This stringent water content specification results in increasing manufacturing cost. Burns et al . found that prismatic cells with intentionally added water function well and, in fact, sometimes better than cells without added water (2, 3). However, the added water caused cell swelling. In this study, pouch cells were been chosen to study gas evolution from intentionally added water. Experimental 323036-size LiCoO 2 (LCO)/graphite (nominal 300 mAh) pouch cells were received from BAK Co. (Shenzhen, China). 1 M LiPF 6 in EC:DEC (BASF, USA) (1:2 v/v) was used as control electrolyte. 2 wt % vinylene carbonate (VC) (99.97% BASF, USA) and/or 2 wt % HQ115 (99.9% purity, 3M, USA) were used as additives. About 1 g of electrolyte was added to the pouch cells. The first charge-discharge cycle (called the formation cycle here) was: hold at 1.5 V for 24 h, charge at 2 mA for 10 h and then at 15 mA (corresponding to C/20) to 4.2 V followed by a discharge to 3.8 V at 15 mA. The total volume of gas generated in the cells after the formation cycle was measured using Archimedes’ principle by weighing the cells while submerged in nano-pure water (18 MΩ) and comparing the weight before and after formation. Two cells with 0.84 g of control electrolyte + 1750 ppm water and 0.79 g of control electrolyte + 1750 ppm water + 2% VC were held at 1.5 V for 45 h and 1.9 V for 10 h and measured by in-situ gas equipment (4). Results and discussion Figure 1 shows the gas volume evolved during formation as a function of the amount of added water. The slope of the gas volume versus water content curve for cells without VC is roughly the same as that for cells with VC. This may suggest that the gas generation mechanism due to added water is the same whether the cells contain VC or not. VC has been shown to limit gas generation in cells without water (4) by presumably changing the distribution of products of electrolyte reduction from gases to liquids or polymers. Figure 2 shows gas evolution versus time for cells with and without VC in the presence of added water. It shows that the gas volume gradually increases during the two-step potential hold at 1.5 V and 1.9 V where no electrolyte reduction or oxidation occur. After the two-step potential hold, the gas volume from added water in both electrolytes roughly match the theoretical calculation that one mole of water produces one mole of hydrogen. This may suggest that added water first reacts with LiPF 6 to produce HF and then the HF reacts with lithium and produces hydrogen. The above results show that more gas is generated when more water is added to the electrolytes. At both 1.5 V and 1.9 V potential holds, water, or HF derived from water, can react with lithiated graphite and can be eliminated, which may be the reason why added water does not have a detrimental effect on cell performance as shown in references 2 and 3. References [1]http://www.targray.com/documents/DMMP-Electrolyte-Solution.pdf, last accessed Feb. 11th, 2014. [2] J. C. Burns et al . J. Electrochem. Soc. , 160, A2281-A2287 (2013) [3] J. C. Burns et al . J. Electrochem. Soc. , 161 A247-A255 (2014) [4] C. P. Aiken, J. Xia, David Yaohui Wang, D.A. Stevens, S. Trussler and J. R. Dahn, An apparatus for the study of in situ gas evolution in Li-ion pouch cells, submitted to J. Electrochem. Soc ., Feb. 14, 2014.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.390
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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".

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Citations1
Published2014
Admission routes1
Has abstractyes

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