First principles computational materials design for energy storage materials in lithium ion batteries

Meng, Ying Shirley; Dompablo, M. Elena Arroyo-de

doi:10.1039/b901825e

Cited by 496 publications

(405 citation statements)

References 202 publications

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“…The generalized gradient approximation þ U formalism developed by Dudarev et al 51 was employed for the 3d electrons of each transition metal cation species. The values of these Hubbard-U parameters for Ni, Mn and Co were initially determined from previous computational work on Li intercalation compounds 52 , and subsequently optimized by iteratively calculating the voltage profile as described by Meng and Dompablo 53 , to the values of 5.5 eV, 7.0 eV and 5.0 eV, respectively.…”

Section: Methodsmentioning

confidence: 99%

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

et al. 2014

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The present study sheds light on the long-standing challenges associated with high-voltage operation of LiNi x Mn x Co 1 À 2x O 2 cathode materials for lithium-ion batteries. Using correlated ensemble-averaged high-throughput X-ray absorption spectroscopy and spatially resolved electron microscopy and spectroscopy, here we report structural reconstruction (formation of a surface reduced layer, R 3m to Fm 3m transition) and chemical evolution (formation of a surface reaction layer) at the surface of LiNi x Mn x Co 1 À 2x O 2 particles. These are primarily responsible for the prevailing capacity fading and impedance buildup under high-voltage cycling conditions, as well as the first-cycle coulombic inefficiency. It was found that the surface reconstruction exhibits a strong anisotropic characteristic, which predominantly occurs along lithium diffusion channels. Furthermore, the surface reaction layer is composed of lithium fluoride embedded in a complex organic matrix. This work sets a refined example for the study of surface reconstruction and chemical evolution in battery materials using combined diagnostic tools at complementary length scales. C hemical evolution and structural transformations at the surface of a material directly influence characteristics relevant to a wide range of prominent applications including heterogeneous catalysis 1-3 and energy storage 4,5 . Structural and/or chemical rearrangements at surfaces determine the way a material interacts with its surrounding environment, thus controlling the functionalities of the material [6][7][8][9][10] . Specifically, the surfaces of lithium-ion battery electrodes evolve simultaneously with charge-discharge cycling (that is, in situ surface reconstruction and formation of a surface reaction layer (SRL)) that can lead to deterioration of performance 4,5,11 . An improved understanding of in situ surface reconstruction phenomena imparts knowledge not only for understanding degradation mechanisms for battery electrodes but also to provide insights into the surface functionalization for enhanced cyclability 12,13 .The investigation of in situ surface reconstruction of layered cathode materials, such as stoichiometric LiNi x Mn x Co 1 À 2x O 2 (that is, NMC), lithium-rich Li(Li y Ni x À y Mn x Co 1 À 2x )O 2 , lithium-rich/ manganese-rich (composite layered-layered) xLi 2 MnO 3 Á (1 À x) LiMO 2 (M ¼ Mn, Ni, Co, and so on) materials, is technologically significant as they represent a group of materials with the potential to improve energy densities and reduce costs for plug-in hybrid electric vehicles and electric vehicles [14][15][16][17] . Practical implementation of some of these materials is thwarted by their high first-cycle coulombic inefficiencies [17][18][19][20] , capacity fading 18,21 and voltage instability [20][21][22] , especially during high-voltage operation. Specifically, high-voltage charge capacities achieved in lithiumrich/manganese-rich layered cathodes are directly associated with various irreversible electrochemical processes including o...

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Section: Methodsmentioning

confidence: 99%

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

et al. 2014

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“…The strategy we use here for studying incorporated cations expands upon existing techniques for calculating equilibrium potentials in battery materials 31,32 by evaluating multiple possible charge states for a given cation incorporated into the host electrode material.…”

Section: Cation Induced Electronic Charge-switching Statesmentioning

confidence: 99%

Charge Storage in Cation Incorporated α-MnO₂

et al. 2015

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Electrochemical supercapacitors utilizing α-MnO 2 offer the possibility of both high power density and high energy density. Unfortunately, the mechanism of electrochemical charge storage in α-MnO 2 and the effect of operating conditions on the charge storage mechanism are generally not well understood. Here, we present the first detailed charge storage mechanism of α-MnO 2 and explain the capacity differences between α-and β-MnO 2 using a combined theoretical electrochemical and band structure analysis. We identify the importance of the band gap, work function, the point of zero charge, and the tunnel sizes of the electrode material, as well as the pH and stability window of the electrolyte in determining the viability of a given electrode material. The high capacity of α-MnO 2 results from cation induced charge-switching states in the band gap that overlap with the scanned potential allowed by the electrolyte. The charge-switching states originate from interstitial and substitutional cations (H + , Li + , Na + , and K + ) incorporated into the material. Interstitial cations are found to induce chargeswitching states by stabilizing Mn-O antibonding orbitals from the conduction band. Substitutional cations interact with O[2p] dangling bonds that are destabilized from the valence band by Mn vacancies to induce charge-switching states. We calculate the equilibrium electrochemical potentials at which these states are reduced and predict the effect of the electrochemical operating conditions on their contribution to charge storage. The mechanism and theoretical approach we report is general and can be used to computationally screen new materials for improved charge storage via ion incorporation.

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“…This definition is widely used as the sole voltage estimate in the LIB theory literature. [56][57][58][59] At equilibrium, when the voltage is pinned at the redox potential of Li-insertion reactions, V e must be equal to V i . Thus V i should be considered a self-consistent criterion at interfaces.…”

Section: Introductionmentioning

confidence: 99%

How Voltage Drops Are Manifested by Lithium Ion Configurations at Interfaces and in Thin Films on Battery Electrodes

Leung

Leenheer

2015

J. Phys. Chem. C

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Battery electrode surfaces are generally coated with electronically insulating solid films of thickness 1-50 nm. Both electrons and Li + can move at the electrode-surface film interface in response to the voltage, which adds complexity to the "electric double layer" (EDL). We apply Density Functional Theory (DFT) to investigate how the applied voltage is manifested as changes in the EDL at atomic lengthscales, including charge separation and interfacial dipole moments. Illustrating examples include Li 3 PO 4 , Li 2 CO 3 , and Li x Mn 2 O 4 thin-films on Au(111) surfaces under ultrahigh vacuum conditions. Adsorbed organic solvent molecules can strongly reduce voltages predicted in vacuum. We propose that manipulating surface dipoles, seldom discussed in battery studies, may be a viable strategy to improve electrode passivation. We also distinguish the computed potential governing electrons, which is the actual or instantaneous voltage, and the "lithium cohesive energy"-based voltage governing Li content widely reported in DFT calculations, which is a slower-responding self-consistency criterion at interfaces. This distinction is critical for a comprehensive description of electrochemical activities on electrode surfaces, including Li + insertion dynamics, parasitic electrolyte decomposition, and electrodeposition at overpotentials. keywords: lithium ion batteries; voltage prediction; density functional theory; computational electrochemistry

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First principles computational materials design for energy storage materials in lithium ion batteries

Cited by 496 publications

References 202 publications

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

Charge Storage in Cation Incorporated α-MnO₂

How Voltage Drops Are Manifested by Lithium Ion Configurations at Interfaces and in Thin Films on Battery Electrodes

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First principles computational materials design for energy storage materials in lithium ion batteries

Cited by 496 publications

References 202 publications

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

Surface reconstruction and chemical evolution of stoichiometric layered cathode materials for lithium-ion batteries

Charge Storage in Cation Incorporated α-MnO2

How Voltage Drops Are Manifested by Lithium Ion Configurations at Interfaces and in Thin Films on Battery Electrodes

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Charge Storage in Cation Incorporated α-MnO₂