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Record W3186970387 · doi:10.1149/ma2021-012149mtgabs

Reactivity and Evolution of Ionic Solid-Electrolyte-Interphases in Battery Electrolytes

2021· article· en· W3186970387 on OpenAlexaff
Rui Guo, Dongniu Wang, Lucia Zuin, Betar M. Gallant

Bibliographic record

VenueECS Meeting Abstracts · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Materials and Technologies
Canadian institutionsCanadian Light Source (Canada)
Fundersnot available
KeywordsElectrolyteX-ray photoelectron spectroscopyReactivity (psychology)Ionic bondingChemistryLithium (medication)ElectrochemistryXANESDielectric spectroscopyFaraday efficiencyInorganic chemistryChemical engineeringMaterials scienceSpectroscopyIonPhysical chemistryElectrodeOrganic chemistry

Abstract

fetched live from OpenAlex

The instability of the solid electrolyte interphase (SEI) on the lithium (Li) metal anode is a major challenge towards improving the Coulombic efficiency (CE) and cycle life of Li batteries. In classical SEI models with mosaic and layered structures, ionic phases (e.g., Li2O and LiF) are enriched closest to the Li|SEI interface, while the outer SEI are highly dependent on electrolytes and typically assigned to less-reduced species, such as semi-carbonates and organic Li salts.1, 2 The formation of SEI on Li is often interpreted as a consequence of reactivity between Li metal and electrolytes; however, there remains a lack of understanding about the interplay between electrolytes and specific SEI phases once they are formed. Some recent computational studies have shed light on the chemical reactivity between thin (~1 nm) single-phase inorganic SEI (Li2O, LiOH, and Li2CO3) on Li metal and DME electrolytes containing LiTFSI or LiFSI salts, using ab initio molecular dynamics (AIMD) calculations;3, 4 experimental insights are still much-needed. Herein, we study two ionic SEI phases, Li2O (Fig. 1a-b) and LiF (Fig. 1c-d), that are nearly ubiquitously found across many native SEIs, and investigate their stability at the SEI|electrolyte interface. We find, by using a combination of electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS) and non-destructive X-ray absorption near-edge spectroscopy (XANES), that the ionic SEI|electrolyte interfaces can undergo significant chemical evolution as a function of electrolyte. As shown in Fig. 1a, distinctive lower-frequency semicircles emerged in the Nyquist plots of EIS when 1 M LiTFSI EC/DEC and 1 M LiPF6 EC/DEC were used, indicating significant changes at the interface between the ionic Li2O SEI and carbonate-based electrolytes, especially in the presence of LiPF6 salt. The surface atomic concentration of F also increased significantly from 4 at.% in 1 M LiTFSI DOL/DME to 44 at.% in 1 M LiPF6 EC/DEC, suggesting that a F-rich Li2O|electrolyte interface leads to an additional charge transfer barrier. Non-destructive Li K-edge XANES of the Li2O SEI soaked in 1 M LiPF6 EC/DEC electrolyte displayed a dominant LiF peak at 62.3 eV with an evident blue shift compared with the standard LiF peak at 62.0 eV (Fig. 1b),5 which could be attributed to the solvation of F-rich species at the interface by organic phases from carbonates decomposition, forming an “organic/F-rich” outer SEI layer. Similar organic/F-rich outer SEI was also observed on the LiF SEI soaked in 1 M LiPF6EC/DEC electrolyte, as evidenced by EIS (Fig. 1c), XPS (Fig. 1d) and XANES results. The organic/F-rich outer SEI induced by reactivity between ionic SEI phases and carbonate-based electrolytes can significantly exacerbate the subsequent plating overpotentials. Our experimental results suggest that electrolyte solvent and salt selection is of great importance to optimize transport in ionic-rich Li interfaces, which can have important implications ultimately for SEI stability and thus CE. Figure 1. (a) Nyquist plot of EIS spectra of Li|Li2O SEI in the three different electrolytes, where the thickness L and conductivity σ of the Li2O SEI were acquired by fitting the higher-frequency semi-circle (or the sole semi-circle in the case of DOL/DME).6 (b) Li K-edge XANES fluorescence yield (FLY) of Li|Li2O interface after soaking in EC/DEC solvent or 1 M LiPF6 EC/DEC electrolyte for 20 hours. (c) Nyquist plot of EIS spectra of Li|LiF SEI in the three different electrolytes. (d) C1s and F1s XPS of the surface layer on Li|LiF SEI after soaking in each electrolyte. References: 1. E. Peled, D. Golodnitsky, and G. Ardel, J. Electrochem. Soc., 144 (8), L208-L210 (1997). 2. A. Schechter, D. Aurbach, and H. Cohen Langmuir, 15 (9), 3334-3342 (1999). 3. E. P. Kamphaus, S. Angarita-Gomez, X. P. Qin, M. H. Shao, M. Engelhard, K. T. Mueller, V. Murugesan, and P. B. Balbuena, ACS Appl. Mater. Interfaces, 11 (34), 31467-31476 (2019). 4. E. P. Kamphaus, S. A. Gomez, X. Qin, M. Shao, and P. B. Balbuena, ChemPhysChem, 21 (12), 1310-1317 (2020). 5. D. Wang and L. Zuin, J. Power Sources, 337, 100-109 (2017). 6. R. Guo and B. M. Gallant, Chem. Mater., 32 (13), 5525-5533 (2020). Figure 1

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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)0.000
metaresearch head score (Gemma)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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 communication0.0010.001
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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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Citations1
Published2021
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