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Research Papers

Analysis of Long-Range Interaction in Lithium-Ion Battery Electrodes

[+] Author and Article Information
Aashutosh Mistry

Mem. ASME
Department of Mechanical Engineering,
Texas A&M University,
College Station, TX 77843
e-mail: aashutoshmistry91@tamu.edu

Daniel Juarez-Robles

Mem. ASME
Department of Mechanical Engineering,
Texas A&M University,
College Station, TX 77843
e-mail: juarezrd@tamu.edu

Malcolm Stein, IV

Department of Mechanical Engineering,
Texas A&M University,
College Station, TX 77843
e-mail: mtsteiniv@gmail.com

Kandler Smith

National Renewable Energy Laboratory,
Golden, CO 80401
e-mail: Kandler.Smith@nrel.gov

Partha P. Mukherjee

Mem. ASME
Department of Mechanical Engineering,
Texas A&M University,
College Station, TX 77843
e-mail: pmukherjee@tamu.edu

1Corresponding author.

Manuscript received June 10, 2016; final manuscript received November 7, 2016; published online December 1, 2016. Assoc. Editor: George Nelson.The United States Government retains, and by accepting the article for publication, the publisher acknowledges that the United States Government retains, a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for United States government purposes.

J. Electrochem. En. Conv. Stor. 13(3), 031006 (Dec 01, 2016) (13 pages) Paper No: JEECS-16-1077; doi: 10.1115/1.4035198 History: Received June 10, 2016; Revised November 07, 2016

The lithium-ion battery (LIB) electrode represents a complex porous composite, consisting of multiple phases including active material (AM), conductive additive, and polymeric binder. This study proposes a mesoscale model to probe the effects of the cathode composition, e.g., the ratio of active material, conductive additive, and binder content, on the electrochemical properties and performance. The results reveal a complex nonmonotonic behavior in the effective electrical conductivity as the amount of conductive additive is increased. Insufficient electronic conductivity of the electrode limits the cell operation to lower currents. Once sufficient electron conduction (i.e., percolation) is achieved, the rate performance can be a strong function of ion-blockage effect and pore phase transport resistance. Even for the same porosity, different arrangements of the solid phases may lead to notable difference in the cell performance, which highlights the need for accurate microstructural characterization and composite electrode preparation strategies.

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Figures

Grahic Jump Location
Fig. 1

(a) Schematic representation of a Li-ion battery half cell. Half cells are prepared with lithium counter electrode and test electrode to characterize electrochemical performance of the electrode under investigation and (b) a pore-scale view of local arrangement of different phases in composite Li-ion battery electrode. The electrochemical reaction—intercalation takes place at active material–electrolyte interface. This interfacial area gets covered due to the addition of electrochemically inactive species like conductive additive and binder, which are quite essential for overall cell performance and stability. Active material irreversibly reacts with electrolyte to form solid electrolyte interphase (SEI), which is not shown on the figure.

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Fig. 2

(a) Electrochemical properties of cathode active material (LiyNi1/3Mn1/3Co1/3O2), adapted from Ref. [35] and (b) electrolyte (LiPF6 in PC/EC/DMC) adapted from Ref. [36] for the present study. Here “y” in NMC corresponds to ratio (Cc/Ccmax).

Grahic Jump Location
Fig. 4

Effect of acetylene black: PVDF weight ratio on internal structure of AB + PVDF phase as hypothesized and justified by conductivity values by Liu et al. [9]. This figure schematically explains the hypothesis of nonmonotonic conductivity variation with increase in conductive additives. (a) Pure binder (PVDF) (b) at low weight fraction of conductive additive, the effective conductivity increase is not significant (c) at a threshold value, the conductive additives form percolation pathways and effective conductivity boosts up significantly (d) and (e) for higher ratios, more and more conducive pathways are formed, still the amount of acetylene black is low enough to form agglomerates (f) as amount of conductive additives is increased further beyond second critical value, agglomeration takes place. Also, the conductive additives form blind chains. Either of these does not sufficiently contribute to effective electron conduction and the electrical conductivity starts decreasing despite addition of more conductive additives. Subfigure (g) show variation in conductivity of NCAO electrodes with 30% porosity and 0.8:1 AB:PVDF composition, as predicted by computations. These simulated trends match well with the experimental conductivity values (dots) reported for NCAO electrodes having similar AB:PVDF composition by Liu et al. [9]. The discrepancy can be attributed to stochastic reconstruction of secondary phases but the values are quite close. Figure (h) displays the conductivity variation of NMC electrodes with different AB:PVDF composition and 30% porosity. These electrodes are further used for electrochemical simulations.

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Fig. 5

(a) Comparison of model predictions against experiments of Zheng et al. [13]. The cells are first charged at C/10 rate till 4.5 V voltage cutoff. After rest period, these half cells are discharged at different rates. The simulated half cells have the identical active material loading, conductive additive and binder composition, electrode thickness, and porosity as experimental electrodes. The slight mismatch for capacity values is attributed to active particle agglomeration. (b) For this 25 μm electrode with 85% NMC, 7% acetylene black, 8% PVDF binder by wt. and 35% porosity, performance at different rates of discharge is simulated. Higher discharge rates give rise to more overpotential and reduced capacity.

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Fig. 6

Effect of AB + PVDF phase composition on discharge performance of Li-NMC half cells at (a) 0.5 C discharge rate (b) 2 C discharge rate. For the same amount of active material, lower conductivity AB + PVDF phase (0.2:1 AB:PVDF by wt.) leads to increased potential drop due to electron conduction and exhibits consistently lower cell voltage compared to higher conductive counterpart (i.e., 0.8:1 AB:PVDF by wt.). As active material weight is reduced and AB + PVDF phase amount is increased, electrochemically active area reduces and gives rise to greater kinetic losses. For 65% active material, AB + PVDF phase amount (35%) is sufficient to provide percolation pathways for electron conduction and hence corresponding limitation vanishes. Thus, varying binder composition at 65% active material loading does not lead to striking difference in performance.

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Fig. 7

Effect of active material loading on electrochemical performance of Li-NMC half cells (a) 0.2:1 AB:PVDF composition (b) 0.8:1 AB:PVDF composition. The upper family of curves corresponds to 0.5 C discharge while the lower set corresponds to 2 C discharge. Decreasing active material loading gives reduced electrochemically active area and hence greater kinetic overpotential. For sufficiently conductive electrodes, this effect is a dominant factor for performance limitation. For lower electronic conductivity, potential drop due to electron conduction can counter the active area increase as reflected on subfigure (a). This would become more apparent at higher rates of operation.

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Fig. 8

Grid independence test is performed to justify numerical resolution of the simulation. The plots show discharge behavior of 85% NMC, 7% acetylene black and 8% PVDF electrodes of 25 μm thickness, and 35% porosity. 10 μm separator is used. The simulations exhibit grid convergence and M = 21 cells discretization is chosen for further simulations.

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