Nanoscale Lithium Quantification in LiXNiyCowMnZO2 as Cathode for Rechargeable Batteries

Bessette, Stéphanie; Paolella, Andrea; Kim, Chisu; Zhu, Wen; Hovington, Pierre; Gauvin, Raynald; Zaghib, Karim

doi:10.1038/s41598-018-33608-3

Cited by 37 publications

(27 citation statements)

References 27 publications

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“…SIMS is a powerful surface‐sensitive technique that allows the imaging of all chemical compositions covering Li, with sub‐100‐nm lateral and nanometer depth spatial resolution. [ 123 ] To date, one of the most popular SIMS instruments is the time‐of‐flight SIMS (TOF‐SIMS). TOF spectrometer separates secondary ions based on their mass‐to‐charge ratio ( m / z ) formed by the primary‐ion bombardment.…”

Section: Multiscale Characterizations Of Nrlo Degradationmentioning

confidence: 99%

“…By correlating with FIB‐SEM, TOF‐SIMS offers unique imaging and analytic capabilities of bulk LIB samples. [ 123,125 ] The nanoscale elemental distributions of the charged and discharged Li 1− x Mn 0.54 Ni 0.13 Co 0.13 O (2− x ) particles were mapped by TOF‐SIMS. In this work, non‐uniform elemental distribution and “trapped” Li‐ion sites at the grain boundaries were revealed (Figure 9b).…”

Section: Multiscale Characterizations Of Nrlo Degradationmentioning

confidence: 99%

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Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

et al. 2020

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though new energy storage devices such as lithium-sulfur batteries [2] and lithium-air batteries [3] have shown great promise due to large theoretical capacity, lithium ion batteries (LIBs) are still dominating in portable electronic devices, prevailing in electric vehicles, and gradually entering grid-energy storage markets. [4] The unsatisfactory energy density of cathodes is widely recognized as the critical bottleneck for higher-performance LIBs. [5] Among various cathodes, Ni-rich layered lithium transition-metal oxides possessing a larger reversible capacity (>180 mAh g −1) than LiCoO 2 (140 mAh g −1), LiNi 1/3 Co 1/3 Mn 1/3 O 2 (160 mAh g −1), LiMn 2 O 4 (120 mAh g −1), and LiFePO 4 (160 mAh g −1), are regarded as one of the most promising cathodes for the next-generation LIBs. [6] In 2016, American electric vehicle company Tesla launched Model 3 with LiNi 0.85 Co 0.10 Al 0.05 O 2 as the cathode for its electric vehicle battery, a testament to the huge potential of Ni-rich layered oxides (NRLOs) (Scheme 1). NRLO cathodes generally consist of two main categories-LiNi 1−x−y Co x Mn y O 2 (NMC) and LiNi 1−x−y Co x Al y O 2 (NCA). The evolution from LiCoO 2 /LiNiO 2 / LiMnO 2 to LiNi 1−x−y Co x Mn y O 2 has been introduced in previous reviews. [7] Briefly, synthesizing LiCoO 2 with the low-defect density was relatively accessible due to the large difference in ionic radius between Li + and Co 3+ , but the irreversible structural change takes place when more than half a fraction of Li + is extracted from its lattice, restricting the capacity. Stoichiometric LiNiO 2 is difficult to prepare due to the instability of trivalent Ni at high temperatures, and the cation mixing between Li and Ni weakens the cycling stability of LiNiO 2. [8] Synthesis of the layered LiMnO 2 phase is not straightforward either, and the capacity fades rapidly because the structural transformation from layered to spinel phase is inevitable upon cycling. [9] LiNi 1−x−y Co x Mn y O 2 combines the strengths of nickel (high capacity), cobalt (good rate capability), and manganese (benign stability). [7] The redox couples of Ni 2+ /Ni 3+ /Ni 4+ and Co 3+ /Co 4+ contribute to the majority of the capacity. The existence of cobalt suppresses the cation mixing during the synthesis of stoichiometric compounds, while manganese helps stabilize the Ni-rich layered oxides (NRLO) are widely considered among the most promising cathode materials for high energy-density lithium ion batteries. However, the high proportion of Ni content accelerates the cycling degradation that restricts their large-scale applications. The origins of degradation are indeed heterogeneous and thus there are tremendous efforts devoted to understanding the underlying mechanisms at multi-length scales spanning atom/lattice, particle, porous electrode, solid-electrolyte interface, and cell levels and mitigating the degradation of the NRLO. This review combines various advanced in situ/ex situ analysis techniques developed for resolving NRLO degradation at multi-length scales and aims...

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Section: Multiscale Characterizations Of Nrlo Degradationmentioning

confidence: 99%

Section: Multiscale Characterizations Of Nrlo Degradationmentioning

confidence: 99%

Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

et al. 2020

View full text Add to dashboard Cite

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“…TOF-SIMS has been applied to cross sections of lithium-ion battery electrodes to map elemental distributions of lithium and other metals within particles with resolutions of 10s of nanometers (Figure 2c). [39,40] The fields of view for these techniques are also variable depending on the time and data-storage capabilities available, but are generally applied with field of view of micrometers or 10s of micrometers. The techniques can be combined through correlative metrology due to the possibility of multiple electron measurement techniques being housed in a single laboratory system.…”

Section: Laboratory-based Techniquesmentioning

confidence: 99%

mentioning

confidence: 99%

Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning

Zhu

Finegan

et al. 2021

Advanced Energy Materials

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Electrochemical and mechanical properties of lithium‐ion battery materials are heavily dependent on their 3D microstructure characteristics. A quantitative understanding of the role played by stochastic microstructures is critical for the prediction of material properties and for guiding synthesis processes. Furthermore, tailoring microstructure morphology is also a viable way of achieving optimal electrochemical and mechanical performances of lithium‐ion cells. To facilitate the establishment of microstructure‐resolved modeling and design methods, a review covering spatially and temporally resolved imaging of microstructure and electrochemical phenomena, microstructure statistical characterization and stochastic reconstruction, microstructure‐resolved modeling for property prediction, and machine learning for microstructure design is presented here. The perspectives on the unresolved challenges and opportunities in applying experimental data, modeling, and machine learning to improve the understanding of materials and identify paths toward enhanced performance of lithium‐ion cells are presented.

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“…Yamagishi et al investigated and showed the Li distribution in NCA LPS ASSB using the same approach but with operando ToF-SIMS. 58,59 For coating identification, surface spectra of coated and uncoated NCM particles could be measured and the signal intensities of the coating layer mass fragments can be compared. If the sample surface is covered with contaminations, sputter cleaning must be performed in advance, ideally with an argon cluster gun to enable a gentle cleaning process and to avoid ablation of the coating layer.…”

Section: Acs Appliedmentioning

confidence: 99%

Analyzing Nanometer-Thin Cathode Particle Coatings for Lithium-Ion Batteries—The Example of TiO₂ on NCM622

Moryson

Walther

Sann

et al. 2021

ACS Appl. Energy Mater.

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Cathode active materials (CAMs) in state-of-the-art lithium-ion batteries are mostly lithium-transition-metal oxides such as Li(Ni x Co y Mn z )O 2 (x + y + z = 1). To achieve optimum cycling stability and performance of the cathode, the extent of degradation processes and side reactions between CAMs and liquid or solid electrolytes has to be minimized. For this purpose, various coating strategies for CAMs have been developed in recent years. The underlying mechanism of the protective function of nanoscale coatings and their role for the enhanced cycling performance are mostly unclear, which is often based on incomplete characterization of the coating. Only a few analytical methods, such as X-ray diffraction, scanning electron microscopy/energy-dispersive X-ray analysis, or X-ray photoelectron spectroscopy, have frequently been used in recent years, which often cannot provide enough information for a reliable and consistent picture of the very thin coating. For this reason, we demonstrate a systematic study on the analytical characterization of coated CAM using additional analytical methods. NCM622 coated with TiO 2 by atomic layer deposition is used as a model system and analyzed with SEM/EDX, focused ion beam scanning electron microscopy, scanning transmission electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, low-energy ion scattering, and time-of-flight secondary ion mass spectrometry. The results highlight the advantages and disadvantages of each analytical method for the analysis of typical CAM coatings. The results demonstrate that a combination of the different methods is essential to understand CAM coatings and their properties in full detail.

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Nanoscale Lithium Quantification in LiXNiyCowMnZO2 as Cathode for Rechargeable Batteries

Cited by 37 publications

References 27 publications

Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning

Analyzing Nanometer-Thin Cathode Particle Coatings for Lithium-Ion Batteries—The Example of TiO₂ on NCM622

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Nanoscale Lithium Quantification in LiXNiyCowMnZO2 as Cathode for Rechargeable Batteries

Cited by 37 publications

References 27 publications

Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

Probing and Resolving the Heterogeneous Degradation of Nickel‐Rich Layered Oxide Cathodes across Multi‐Length Scales

Guiding the Design of Heterogeneous Electrode Microstructures for Li‐Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning

Analyzing Nanometer-Thin Cathode Particle Coatings for Lithium-Ion Batteries—The Example of TiO2 on NCM622

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Product

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Analyzing Nanometer-Thin Cathode Particle Coatings for Lithium-Ion Batteries—The Example of TiO₂ on NCM622