Structures, Electronic States, and Reactions at Interfaces between LiNi0.5Mn1.5O4 Cathode and Ethylene Carbonate Electrolyte: A First-Principles Study

Okuno, Yukihiro; Ushirogata, Keisuke; Sodeyama, Keitaro; Shukri, Ganes; Tateyama, Yoshitaka

doi:10.1021/acs.jpcc.8b10625

Cited by 35 publications

(42 citation statements)

References 68 publications

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“…The reaction energy was calculated to be −2.67 on the pristine surface and 1.53 eV on the S-deposited surface using the SCAN functional, indicating that the onset of EC degradation is exothermic on the S-free surface of delithiated Li 2 MnO 3 , but energetically prohibitive after forming the polyanionic configuration. This is in agreement with previous reports that surface oxygen of charged layered oxides can attack carbonate solvents and catalyze electrolyte decomposition 42,46 . It can therefore be concluded that the polyanionic (SO 4 ) 2− species could stabilize the surface of Li 2 MnO 3 not only by preventing gas releasing in solution, but also by inhibiting reactions with the electrolyte.…”

Section: Resultssupporting

confidence: 94%

“…Referring to previous reports on the reaction between Li transition-metal oxides and conventional electrolytes, EC has been found to preferentially adsorb and react with the electrodes 40,41 . In general, EC reaction/decomposition initiates by breaking one of the two C-O bond in the ring on the cathode surfaces 42,43 , and finally evolves to CO 2 and various other organic species 44,45 . Therefore, our calculations focus on the first step of EC decomposition, the ring opening of cyclic carbonate after EC molecular adsorption on the delithiated (010) surface, as shown in Fig.…”

Section: Resultsmentioning

confidence: 99%

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Highly reversible oxygen redox in layered compounds enabled by surface polyanions

et al. 2020

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Oxygen-anion redox in lithium-rich layered oxides can boost the capacity of lithium-ion battery cathodes. However, the over-oxidation of oxygen at highly charged states aggravates irreversible structure changes and deteriorates cycle performance. Here, we investigate the mechanism of surface degradation caused by oxygen oxidation and the kinetics of surface reconstruction. Considering Li 2 MnO 3 , we show through density functional theory calculations that a high energy orbital (lO 2p') at under-coordinated surface oxygen prefers over-oxidation over bulk oxygen, and that surface oxygen release is then kinetically favored during charging. We use a simple strategy of turning under-coordinated surface oxygen into polyanionic (SO 4) 2− , and show that these groups stabilize the surface of Li 2 MnO 3 by depressing gas release and side reactions with the electrolyte. Experimental validation on Li 1.2 Ni 0.2 Mn 0.6 O 2 shows that sulfur deposition enhances stability of the cathode with 99.0% capacity remaining (194 mA h g −1) after 100 cycles at 1 C. Our work reveals a promising surface treatment to address the instability of highly charged layered cathode materials.

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Section: Resultssupporting

confidence: 94%

Section: Resultsmentioning

confidence: 99%

Highly reversible oxygen redox in layered compounds enabled by surface polyanions

et al. 2020

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“…Reaction barrier calculations like umbrella sampling and metadynamics bypass trajectory length limits at the cost of having to choose pathways. 18,[82][83][84] In purely solid state calculations, zero-temperature nudged-elastic-band (NEB) calculations have become standard. 85 From barrier calculations, we estimate mean reaction rates using the standard transition state theory expression…”

Section: I-equilibriummentioning

confidence: 99%

DFT modelling of explicit solid–solid interfaces in batteries: methods and challenges

Leung

2020

Phys. Chem. Chem. Phys.

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Density Functional Theory (DFT) calculations of electrode material properties in high energy density storage devices like lithium batteries have been standard practice for decades. In contrast, DFT modelling of explicit interfaces in batteries arguably lacks universally adopted methodology and needs further conceptual development. In this paper, we focus on solid-solid interfaces, which are ubiquitous not just in all-solid state batteries; liquid-electrolyte-based batteries often rely on thin, solid passivating films on electrode surfaces to function. We use metal anode calculations to illustrate that explicit interface models are critical for elucidating contact potentials, electric fields at interfaces, and kinetic stability with respect to parasitic reactions. The examples emphasize three key challenges: (1) the "dirty" nature of most battery electrode surfaces; (2) voltage calibration and control; and (3) the fact that interfacial structures are governed by kinetics, not thermodynamics.To meet these challenges, developing new computational techniques and importing insights from other electrochemical disciplines will be beneficial.High energy density batteries are instrumental to vehicle electrification and to grid storage which helps alleviate intermittency in solar and wind energy generation. Deeper understanding of existing materials and the search of new electrode and electrolyte materials are crucial for developing higher capacity, faster-charging, safer, and longer-lasting batteries. 1 Battery interfaces are also universally acknowledged to be critical for governing battery rate capability and stability. 2 Charge/discharge processes, as well as many side reactions that lead to degradation, self-discharge, and thermal runaway, initiate at interfaces.Electronic structure Density Functional Theory (DFT) modelling of the crystalline interior of electrodes, for the purpose of predictng phase stability, equilibrium voltages, and lithium diffusion kinetics, has been widely practised for decades. 3-7 It provides important guidance to experiments. In contrast, DFT modelling of explicit battery interfaces arguably needs further conceptual development and systematization. Here we distinguish explicit interfaces where two phases are in contact in the same simulation cell, from single-phase DFT calculations used to infer interfacial properties indirectly. 8 The present work focuses on modelling methods, offers somewhat pedagogical discussions on the rationale behind the DFT approaches used in our group, and examines future directions and improvements.Simple material interfaces, mainly involving lithium metal, are used as illustrations, but the principles involved should be broadly applicable to other electrodes. Even simple materials exhibit complex interfaces that require substantial approximations; the nature and consequences of some key implicit approximations are highlighted. We restrict ourselves to vanishing current densities. 9 This paper is intended to be a topical, critical overview, not a comprehensive revi...

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“…41 However, up to now ab initio molecular dynamics simulations using GGA+U or hybrid DFT functionals could only be performed for rather small Li x Mn 2 O 4 -water model systems containing a few hundred atoms on picosecond time scales due to the large computational effort. [42][43][44][45][46] To consider the interplay of a variety of different structural motifs with a liquid solvent picosecond time scales are not sufficient. For instance, for the equilibration of Li x Mn 2 O 4 -water interfaces including the formation of hydroxide layers, electrical double layers, and/or pseudo-crystalline water at the interface as well as to obtain reliable statistics for elementary steps of proton transfer (PT) reactions and hydrogen bond networks significantly larger length and time scales are required.…”

mentioning

confidence: 99%

Insights into lithium manganese oxide-water interfaces using machine learning potentials

Eckhoff,

Behler

2021

Preprint

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Unraveling the atomistic and the electronic structure of solid-liquid interfaces is the key to the design of new materials for many important applications, from heterogeneous catalysis to battery technology. Density functional theory (DFT) calculations can in principle provide a reliable description of such interfaces, but the high computational costs severely restrict the accessible time and length scales. Here, we report machine learning-driven simulations of various interfaces between water and lithium manganese oxide (Li x Mn 2 O 4 ), an important electrode material in lithium ion batteries and a catalyst for the oxygen evolution reaction. We employ a high-dimensional neural network potential (HDNNP) to compute the energies and forces several orders of magnitude faster than DFT without loss in accuracy. In addition, a high-dimensional neural network for spin prediction (HDNNS) is utilized to analyze the electronic structure of the manganese ions. Combining these methods, a series of interfaces is investigated by large-scale molecular dynamics. The simulations allow us to gain insights into a variety of properties like the dissociation of water molecules, proton transfer processes, and hydrogen bonds, as well as the geometric and electronic structure of the solid surfaces including the manganese oxidation state distribution, Jahn-Teller distortions, and electron hopping.

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Structures, Electronic States, and Reactions at Interfaces between LiNi_0.5Mn_1.5O₄ Cathode and Ethylene Carbonate Electrolyte: A First-Principles Study

Cited by 35 publications

References 68 publications

Highly reversible oxygen redox in layered compounds enabled by surface polyanions

Highly reversible oxygen redox in layered compounds enabled by surface polyanions

DFT modelling of explicit solid–solid interfaces in batteries: methods and challenges

Insights into lithium manganese oxide-water interfaces using machine learning potentials

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