Atomic pair distribution function research on Li2MnO3 electrode structure evolution

Yang, Yubo; Su, Heng; Wu, Tianhao; Jiang, Yongping; Liu, Danmin; Yan, Pengfei; Tian, H. L.; Yu, Haijun

doi:10.1016/j.scib.2019.03.019

Cited by 22 publications

(14 citation statements)

References 31 publications

(35 reference statements)

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“…Although XRD and STEM techniques are powerful for identifying and monitoring CDBMs, advanced characterizations such as PDF and solid-state nuclear magnetic resonance (ss-NMR) are still urgently needed, especially for short-range ordered or even disordered structures. , PDF can analyze the average atomic arrangement in local regions based on high-throughput signal acquisition by X-ray or neutron sources, specifically powerful for CDBMs possessing abundant crystal domains (Figure a). A primary study on the identification and evolution of Li 2 MnO 3 by ex-situ PDF has been reported . As shown in Figure b,c, different bonds can be identified based on characteristic peaks at certain distances, and their changes can be monitored at different discharge/charge states.…”

Section: Crystalline Domain Battery Materialsmentioning

confidence: 99%

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Crystalline Domain Battery Materials

Zhang

2019

Acc. Chem. Res.

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The development of next-generation energy storage materials for secondary batteries relies more and more on the delicate design and tailoring of their local structures and properties. Crystalline domain battery materials (CDBMs) are defined as a family of materials that are hierarchically engineered primarily by bonding selective atoms in certain space groups with short-range order to form nanoscale crystal domains as fundamental constructive and functional units, secondarily by integrating these interactive crystal domains under certain configurations into grains to implement electrochemical synergy, and finally by optimizing grains through nanoengineering toward advanced electrode materials. In CDBMs, adjacent crystal domains can undergo structural co-transformations with noticeable interrelationships, and the overall electrochemical performance is determined not only by the intrinsic structure of each crystal domain (element, bonding, valence, stacking, orientation, etc.) but also by the configuration of crystal domains (size, ratio, interface, distribution, interaction, etc.). Pioneering studies have shown significant enhancement of electrochemical performance by controlling crystal domains, suggesting the prospect of developing novel electrode materials through crystal-domain engineering. However, fundamental understanding and delicate fabrication of this material family, in terms of structural identification, electrochemical structure evolution, reaction mechanism, design and adjustment, and structure−performance relationship, among others, still face great challenges to meet the compelling requirements of highperformance electrode materials for secondary batteries. This Account systematically introduces the structure and electrochemistry of CDBMs. The efficient structural identification of crystal domains, which is still challenging due to their structural complexity, is demonstrated using prototype materials by advanced characterization techniques such as high-energy X-ray diffraction combined with Rietveld refinement and spherical aberration-corrected transmission electron microscopy. Investigations on the structural evolution of CDBMs in electrochemical reactions by ex-situ and in-situ techniques provide insights into reaction scenarios such as how ions migrate in and across crystal domains and how these crystal domains transform synergistically. A crystal-domain reaction mechanism is thus proposed to explain the electrochemistry of these materials. Design principles and adjustment strategies for designated crystal-domain structures including their components, ratios, distributions, and interfaces are deduced from the structural identification, evolution and reaction mechanism. The relationship between crystal-domain structures and electrochemical performance can further be elucidated, inspiring us to explore efficient strategies for optimizing the electrochemical performance, as validated by examples of high-performance batteries using materials with controlled crystal-domain structures. Based on these...

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Section: Crystalline Domain Battery Materialsmentioning

confidence: 99%

“…(b, c) PDF evolution of Li 2 MnO 3 at different charge (C)/discharge (D) states in the first cycle (b) and at 2 V-discharge states in different cycles (c). Reproduced with permission from ref . Copyright 2019 Elsevier.…”

Section: Crystalline Domain Battery Materialsmentioning

confidence: 99%

Crystalline Domain Battery Materials

Zhang

2019

Acc. Chem. Res.

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“…Three materials emerge in the families of the layered compounds that represent the most typical Li-rich configurations, Li 2 MnO 3 , Li 2 RuO 3 , and Li 2 IrO 3 . They represent Li-rich systems based on 3d, 4d, and 5d TMs with different cationic d levels and hybridization effects that are important for ARR behaviors. , Other than some detailed structural differences that have been reported before, ,− all these three materials are layered compounds with a significant amount of Li occupying about 1/3 of the TM sites forming a honeycomb structure, i.e., the typical Li-rich configuration. In the early stage of the study of ARR, all three systems were considered systems with reversible lattice ARR, mostly based on O -K X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS) studies. ,,,− However, these conclusions have later been challenged due to the technical reliability issues of the entangled O -K XAS signals with significant TM characters and the shallow probe depths of both soft and hard XPS. , Indeed, advances in O -K spectroscopy based on high-efficiency mapping of resonant inelastic X-ray scattering (mRIXS), , together with differential electrochemical mass spectroscopy (DEMS), have clarified that no lattice ARR is involved in the cycling of Li 2 MnO 3 and Li 2 IrO 3 . ,, Recent experimental results conclusively show that oxygen oxidation during the initial charging of Li 2 MnO 3 is only in the form of irreversible oxygen release and surface reactions, , consistent with some earlier theoretical analysis, and fully charged Li 2 IrO 3 displays only multivalent Ir redox reactions .…”

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confidence: 96%

Distinct Oxygen Redox Activities in Li₂MO₃ (M = Mn, Ru, Ir)

Zhuo

Dai

et al. 2021

ACS Energy Lett.

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Li 2 MO 3 (M = transition metal) systems are parent compounds of Li-rich materials and widely considered to offer oxygen redox for high-energy batteries. However, recent clarifications have revealed that, among the three representative Li 2 MO 3 (M = Mn, Ru, Ir) compounds, no reversible oxygen redox takes place in the Mn and Ir systems. Here, we reevaluate the redox reactions in Li 2 RuO 3 through advanced spectroscopy, which shows both Ru redox and highly reversible O redox (96% initial-cycle reversibility, 80% retained after 10 cycles, and 77% after 50 cycles). This is in sharp contrast with the Li 2 MnO 3 and Li 2 IrO 3 systems and concludes the three distinct oxygen behaviors in the Li 2 MO 3 systems during charging: (i) only irreversible oxygen oxidation in Li 2 MnO 3 ; (ii) reversible Ru and O redox in Li 2 RuO 3 ; (iii) only cationic redox in Li 2 IrO 3 . This work suggests the critical role of transition metals and their coupling to oxygen for maintaining reversible oxygen redox activities for high-energy batteries.

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“…10), a collaborative work between SNEM and EXELFS should expand the flexibility and richness in collecting spatially-resolved local order information in materials. Considering the richness of information SNEM provides, especially in augmentation with other spatially-resolved methods, the growing automation and autonomation efforts of in situ PDF experimentation [62,63,64], including in electron microscopes [56], we find SNEM as a strong candidate for taking the lead in data-driven exploration of local order in materials in advanced metallurgy, energy materials [54,55], and bio-mineralization [56]. In parallel, it will also allow us to ask new questions on more classical materials that are yet to be answered and relate to the local order and its evolution in time and space.…”

Section: Discussionmentioning

confidence: 99%

“…Visualizing and understanding the chemistry-structure-process relations have immediate implication on understanding formation of shear-bands in metallic glasses. The link between chemistry and structural order is an important tier to the ongoing studies in metallic glasses [34,35,36,37,38], but also in other fields, such as structure evolution in batteries [54,55], and biomineralization [56].…”

Section: Relation Between Order and Compositionmentioning

confidence: 99%

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

Rakita¹,

Hart²,

Das³

et al. 2021

Preprint

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Here we explore the use of scanning diffraction electron microscopy (4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local structure and chemistry in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass, as a function of position with 3 nm spatial resolution. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. This gives critical insights into the formation mechanism of these features. Unsupervised machine learning was used to extract partial PDFs from the material, modeled as quasi-binary alloy, and map them in space allowing key insights not only into the local average composition but also any chemical short-range ordering tendency in that region of the sample. The experiments are straightforward and rapid and unlike spectroscopic measurements don't require energy filters on the instrument. We spatially map different quantities of interest (QoI's), defined as scalars that can be computed directly from an analysis of the data such as positions and widths of PDF peaks or parameters refined from fits to the patterns, and have developed a flexible and rapid data analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI's. The power and flexibility of this approach is explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from PDFs we call this approach scanning nano-structure electron microscopy (SNEM). We believe that it will be powerful and useful extension of current 4D-STEM methods.

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Atomic pair distribution function research on Li2MnO3 electrode structure evolution

Cited by 22 publications

References 31 publications

Crystalline Domain Battery Materials

Crystalline Domain Battery Materials

Distinct Oxygen Redox Activities in Li₂MO₃ (M = Mn, Ru, Ir)

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

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Atomic pair distribution function research on Li2MnO3 electrode structure evolution

Cited by 22 publications

References 31 publications

Crystalline Domain Battery Materials

Crystalline Domain Battery Materials

Distinct Oxygen Redox Activities in Li2MO3 (M = Mn, Ru, Ir)

Mapping Structural Heterogeneity at the Nanoscale with Scanning Nano-structure Electron Microscopy (SNEM)

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About

Distinct Oxygen Redox Activities in Li₂MO₃ (M = Mn, Ru, Ir)