Rapidly convergent cluster expansion and application to lithium ion battery materials

Lee, Eunseok; Iddir, Hakim; Benedek, R.

doi:10.1103/physrevb.95.085134

Cited by 8 publications

(16 citation statements)

References 53 publications

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“…Computationally, there have been a number of firstprinciples studies of doping in LiMO 2 using densityfunctional theory (DFT) within the standard localdensity approximation or generalized-gradient approximation or the DFT+U extension (where U is the on-site Hubbard correction). [20][21][22][23][24][25][26][27] These studies have provided useful information on several aspects of the doped materials, including their atomic and electronic structure and the solubility of the dopants. However, the methods used in these previous studies are known to have limited predictive power in complex transition-metal oxides.…”

Section: Introductionmentioning

confidence: 99%

First-principles theory of doping in layered oxide electrode materials

Hoang

2017

Phys. Rev. Materials

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Doping lithium-ion battery electrode materials LiMO 2 (M = Co, Ni, Mn) with impurities has been shown to be an effective way to optimize their electrochemical properties. Here, we report a detailed first-principles study of layered oxides LiCoO 2 , LiNiO 2 , and LiMnO 2 lightly doped with transitionmetal (Fe, Co, Ni, Mn) and non-transition-metal (Mg, Al) impurities using hybrid-density-functional defect calculations. We find that the lattice site preference is dependent on both the dopant's charge and spin states, which are coupled strongly to the local lattice environment and can be affected by the presence of co-dopant(s), and the relative abundance of the host compound's constituting elements in the synthesis environment. On the basis of the structure and energetics of the impurities and their complexes with intrinsic point defects, we determine all possible low-energy impurity-related defect complexes, thus providing defect models for further analyses of the materials. From a materials modeling perspective, these lightly doped compounds also serve as model systems for understanding the more complex, mixed-metal, LiMO 2 -based battery cathode materials.

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Section: Introductionmentioning

confidence: 99%

First-principles theory of doping in layered oxide electrode materials

Hoang

2017

Phys. Rev. Materials

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“…These computational methods are becoming increasingly useful for identifying larger-scale combinations of atomic orderings for a variety of materials systems. 1,41 In fact, our prior work employed such computational models for identifying new atomic configurations 7 such as patterns of Va-Va. 6 Although powerful, many computational methods require significant research effort and time in order to devise appropriate algorithms for understanding different materials systems. In addition, such research will often require high performance computing (HPC) resources.…”

Section: Discussionmentioning

confidence: 99%

“…Accordingly, these 2D representations are broadly used in materials science publications to show important atomic patterns in the layered materials. 5–7…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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GoCrystal: A gamified visual analytics tool for analysis and visualization of atomic configurations and thermodynamic energy models

Chung

Nandhakumar

Vasu

et al. 2020

Information Visualization

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In this article, we present GoCrystal, a new visual analytics tool for analysis and visualization of atomic configurations and thermodynamic energy models. GoCrystal’s primary objective is to support the visual analytics tasks for finding and understanding favorable atomic patterns in a lattice using gamification. We believe the performance of visual analytics tasks can be improved by employing gamification features. Careful research was conducted in an effort to determine which gamification features would be more applicable for analyzing and exploring atomic configurations and their associated thermodynamic free energy. In addition, we conducted a user study to determine the effectiveness of GoCrystal and its gamification features in achieving this goal, comparing with a conventional visual analytics model without gamification as a control group. Finally, we report the results of the user study and demonstrate the impact that gamification features have on the performance and time necessary to understand atomic configurations.

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“…By treating the lithium and oxygen atoms as a constant background, we create a model lattice containing the relevant cations and only consider the energetics and interactions related to the proportions and orderings of the transition metal ions. This type of consideration of only specific interaction terms while leaving other atoms as a constant background term has been used sucessfully in other cluster expansion studies of transition metal oxide materials [28][29][30] . We assume a triangle lattice where at each site on the lattice, one of the three metal cations (Ni, Mn, Co) is present as seen in Figure 1.…”

Section: B Reduced Order Modelmentioning

confidence: 99%

Towards Ultra Low Cobalt Cathodes: A High Fidelity Computational Phase Search of Layered Li-Ni-Mn-Co Oxides

Houchins

Viswanathan

2019

J. Electrochem. Soc.

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Layered Li(Ni,Mn,Co,)O2 (NMC) presents an intriguing ternary alloy design space for the optimization of performance as a cathode material in Li-ion batteries. In the case of NMC, however, only a select few proportions of transition metal cations have been attempted and even fewer show promise. Recently, due to cost and resource limitations of Co, high Ni-containing NMC alloys have gained enormous attention. Here, we present a high fidelity computational search of the ternary phase diagram with an emphasis on high-Ni containing compositional phases. This is done through the use of density functional theory training data fed into a reduced order model Hamiltonian that accounts for effective electronic and spin interactions of neighboring transition metal atoms at various lengths in a background of fixed lithium and oxygen atoms. This model can then be solved to include finite temperature thermodynamics into a convex hull analysis. We also provide a method to propagate the uncertainty at every level of the analysis to the final prediction of thermodynamically favorable compositional phases thus providing a quantitative measure of confidence for each prediction made. Due to the complexity of the three component system, as well as the intrinsic error of density functional theory, we argue that this propagation of uncertainty, particularly the uncertainty due to exchange-correlation functional choice is necessary to have reliable and interpretable results. With our final result, we recover the prediction of already known phases such as LiNi0.33Mn0.33Co0.33O2 (111) and LiNi0.8Mn0.1Co0.1O2 (811) in exact proportion while finding other proportions very close to the experimentally claimed LiNi0.6Mn0.2Co0.2O2 (622) and LiNi0.5Mn0.3Co0.2O2 (532) phases, and overall predict a total of 37 phases with reasonable confidence and 69 more phases with a lower level of confidence. Through our analysis, we also can identify the phases with the highest average operational voltage at a given Co composition. Our method presents a framework that can be extended to searches for other high Ni cathode materials by substituting other transition metal atoms into the lattice such as aluminum and magnesium, which have already shown promise. arXiv:1805.08171v1 [cond-mat.mtrl-sci]

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Rapidly convergent cluster expansion and application to lithium ion battery materials

Cited by 8 publications

References 53 publications

First-principles theory of doping in layered oxide electrode materials

First-principles theory of doping in layered oxide electrode materials

GoCrystal: A gamified visual analytics tool for analysis and visualization of atomic configurations and thermodynamic energy models

Towards Ultra Low Cobalt Cathodes: A High Fidelity Computational Phase Search of Layered Li-Ni-Mn-Co Oxides

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