Article pubs.acs.org/cm
Characterization of Disordered Li(1+x)Ti2xFe(1−3x)O2 as Positive Electrode Materials in Li-Ion Batteries Using Percolation Theory Stephen L. Glazier,† Jing Li,‡ Jigang Zhou,§ Toby Bond,§ and J. R. Dahn*,†,‡,∥ †
Department of Physics and Atmosphere Science, ∥Department of Chemistry, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 4R2 ‡ Department of Process Engineering and Applied Science, Dalhousie University, Halifax, Nova Scotia, Canada, B3H 3J5 § Canadian Light Source, Saskatoon, Saskatchewan, Canada, S7N 2V3 ABSTRACT: Recent theoretical and experimental works have shown that disordered positive electrode materials can function well in lithium cells. This work explores the solid solution series Li(1+x)Ti2xFe(1−3x)O2 (0 ≤ x ≤ 0.333) and compares the measured specific capacity variation with x to a recent theoretical model. The samples have varying degrees of cation disordering between lithium and transition metal layers that is dependent on x. The materials were characterized using induced coupled plasma optical emission spectroscopy, scanning electron microscopy, X-ray diffraction, and X-ray absorption spectroscopy (XAS) to quantify the degree of disorder and predict electrochemical performance. The specific capacities of lithium-limited samples (0 ≤ x ≤ 0.13) were found to agree very well with the recently proposed percolation theory model, whereas redox-limited samples (0.13 ≤ x ≤ 0.29) yielded slightly higher than expected capacities due to oxygen redox compensation characterized by oxygen K-edge XAS studies. Capacity retention was found to increase with lithium content. The voltage vs specific capacity relations for this set of materials do not suggest practicality, so this work is primarily of academic interest, but it suggests that more disordered materials should be explored.
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INTRODUCTION Large-scale lithium-ion batteries are becoming more in demand for use in automotive and energy storage applications. In order to fulfill these demands, new materials must be cheaper and have high energy density, long life, and good safety. New positive electrode materials are, therefore, of interest for their potential to reduce cost and affect the overall capacity and performance of a lithium ion battery. Positive electrode material research in oxides has been focused on materials with ordered-layered (LiMO2, M = Co, Mn, Ni, etc.) and spinel (Li2MO4 or LiM2O4) structures. These materials generally exhibit good electrochemical performance and structural stability due to favorable and reversible lithium migration through networks of sites spanning the structures. Until recently, disordered-layered oxides have not been studied in detail due to their poor performance, such as in the case of LiFeO2.1−3 This poor performance is due to Li being distributed in the cation sites in such a way that no structurespanning paths for facile Li migration are formed. However, recent works implementing Monte Carlo simulations on percolation theory have shown that sufficiently Li-rich compounds can form paths for Li migration that percolate through the entire structure, enabling lithium diffusion even in materials where Li and transition metals are randomly distributed in cation sites of the rock-salt structure.4−6 In the disordered rocksalt (α-LiFeO2) structure, Li and transition metal (TM) atoms occupy octahedral sites and migration occurs through oxygen tetrahedral sites or, as they are referred © 2015 American Chemical Society
to in the literature, channels, defined by Lee et al. as n-TM, where n is the number of transition metals around the tetrahedral sites (n = 0−4).4 The word channel may misrepresent the geometry and path of Li through these tetrahedra; therefore, the term site will be used in this work in place of channel. In traditional ordered-layered structures, like LiCoO2, only 1-TM and 3-TM sites are present and Li migrates through 1-TM sites (between the 2D CoO2 slabs). In disordered materials, all n-TM sites are present in populations dependent on Li content. For example, in disordered rock-salt structure Li(1+x)My(1−x)N(1−y)(1−x)O2, the probability of any site being 0-TM is given by p0 ‐ TM =
⎛ 1 + x ⎞4 ⎜ ⎟ ⎝ 2 ⎠
(1)
The probability of each n-TM site can be found as a function of x and is shown in Figure 1a. The probability starts as a normal distribution about 2-TM at stoichiometric disordered LiMO2 and is weighted toward 0-TM and 1-TM sites at higher Li content. Lee et al. found using density functional theory that in the disordered rock-salt structure typically only 0-TM sites are favorable for Li migration.4,5 Figure 1a shows that the statistical amount of 0-TM lithium, without even considering a percolating path to the particle surface, is severely limited at Received: September 9, 2015 Revised: October 21, 2015 Published: October 21, 2015 7751
DOI: 10.1021/acs.chemmater.5b03530 Chem. Mater. 2015, 27, 7751−7756
Article
Chemistry of Materials
Figure 1. (a) Probability of n-TM sites in a disordered rock-salt (α-LiFeO2) structure. At x = 0.00, the distribution is normal about 2-TM. As x is increased, the distribution is weighted toward lower n, increasing the chances of 0-TM networks spanning the structure. (b) Theoretical accessible lithium content based on lithium in 0-TM sites (solid line) (adapted from ref 5) and examples of lithium available from redox reactions due to different combinations of M and N (dashed lines) in a solid solution Li(1+x)M2xN(1−3x)O2 (0 ≤ x ≤ 1/3).
low values of x. Figure 1b shows recent Monte Carlo simulations that predict the amount of Li in 0-TM site networks that percolate to the surface of the particle.4,5 Due to increasing Li content, another limiting factor for the amount of lithium that can contribute to capacity is the TM redox species used. Typical TM species used in positive electrodes involve 3+/4+ redox species, limiting the theoretical capacity further since the average oxidation state of the TM must increase in Li(1+x)My(1−x)N(1−y)(1−x)O2 as x increases, limiting theoretical capacity. The current works on percolation models have shown that Li1.211Mo0.467Cr0.3O2 (which disorders during charge−discharge cycling) agrees very well with theory, yielding very close to predicted performance from the percolation simulations. However, only the single composition mentioned above was reported to correlate with simulations, and no work to date has shown multiple compositions in a Li(1+x)My(1−x)N(1−y)(1−x)O2 solid solution agreeing with this theory. Figure 1b demonstrates the available lithium in 0-TM networks (black line) as well as the theoretical amount of redox availability from various TM systems. Once the redox lines intersect the 0-TM line, performance may be limited by redox capabilities. Therefore, for very few choices of M species with 4+/6+ (Mo) and N with 3+/4+ (Cr among others) will the disordered system be able to percolate all 0-TM accessible Li at high levels of x, meaning that very few chemistries may yield such high capacity, as shown by the red dashed line in Figure 1b. Other possibilities could include inactive 4+ M ions (such as Ti4+) and 3+/4+ N ions (such as Fe3+, Mn3+, Co3+, etc.). Previous studies of disordered Li(1+x)Ti2xFe(1−3x)O2 found improved capacities at some values of x, but they could not describe the trend suggested by the combined 0-TM and 3+/4+ models in Figure 1b.1,2 In those studies, Ti was found to be electrochemically inactive through the charge/discharge process, whereas first charge capacity was due to Fe3+/4+ oxidation. During discharge, only some Fe4+/3+ reduction was reported, whereas reversible Fe3+/2+ occurred at low potentials around 2 V.1,2 Fe-containing materials such as Li(1+x)Ti2xFe(1−3x)O2 and LiFePO4 are of interest due to their low materials cost, safety, and ease of synthesis. By synthesizing Li(1+x)Ti2xFe(1−3x)O2 at different values of x, the ability of percolation simulations, coupled with maximum capacities available from TM redox, to predict the performance of disordered rock-salt type Li-rich
materials can be probed and previously unexplained trends in such disordered materials may be explained.
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EXPERIMENTAL SECTION
Materials used in this work were lithium carbonate (Li2CO3) (Chemetall, ≥99%), iron (iii) oxide (Fe2O3) (Sigma-Aldrich, ≥99%), titanium dioxide (TiO2) (Fisher, ≥99%), N-methylpyrrolidone (NMP, 99.5%, Sigma-Aldrich), poly(vinylidene) fluoride (PVDF, Kynar 301F, Arkema), super-S carbon black (Timcal), 1:2 v/v ethylene carbonate/diethyl carbonate (EC/DEC) (BASF, 99.99%, 99.99%), and lithium hexafluorophosphate (LiPF6) (BASF, 99.9%). Synthesis. Li(1+x)Ti2xFe(1−3x)O2 was synthesized by hand grinding appropriate amounts of Li2CO3, Fe2O3, and TiO2 for 5 min at target values of x = 0.00, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30 with 5 or 10% excess Li over the target composition to account for Li loss during heating. 5 and 10% excess samples were heated at 700 and 800 °C in an alumina crucible in air, respectively, for 20 h (10 °C min−1 heat and cool). Characterization. X-ray diffraction (XRD) measurements were made using a Siemens D-5000 X-ray diffractometer equipped with a copper target X-ray tube and a diffracted-beam monochromator in the range 10° ≤ 2θ ≤ 85° with a 0.05° step size and a dwell time of 3s. Data were fitted using Rietveld refinement using cubic Fm3̅m and rhombohedral R3̅m space groups in order to determine lattice constants and cation mixing between Li and TM layers. When no cation mixing was observed (absence of (003) peak), Fm3̅m was used. Cation mixing was calculated in accordance with Lee et al. as the population ratio of TM in the Li layer to the TM occupying the TM layer.4 Li and TM species were constrained to mix between layers according to their relative compositions (assuming that all sites were occupied). Values of c/3a were calculated from fitted lattice parameters to check proximity to a perfect cubic close-packed (ccp) structure. A ccp structure should have c/3a = 1.633, and an ordered layered structure generally has a larger value. Therefore, the proximity to 1.633 is a direct measurement of the amount of transition metals in the Li layer and should correlate with the XRD refinement.7 Inductively coupled plasma optical emission spectroscopy (ICPOES) was used to compare final compositions to target values at each x, with a measurement uncertainty of 2%. Measurements were performed on a PerkinElmer Optima 8000 at Dalhousie University. Li, Ti, and Fe standards (1000 ppm, Sigma-Aldrich) and blanks were made to 0.5 and 1 ppm for Li and 1 and 2 ppm for Ti and Fe. Samples were dissolved in 2 mL of aqua regia and diluted in 2% HNO3 to fit within the standard concentration window. 7752
DOI: 10.1021/acs.chemmater.5b03530 Chem. Mater. 2015, 27, 7751−7756
Article
Chemistry of Materials Scanning electron microscopy (SEM) was performed with a Hitachi S-4700 SEM equipped with an Oxford Instruments 80 mm2 silicon drift detector. Electrochemical Measurements. 2325 type coin cells were prepared using standard procedures.8 Positive electrodes were prepared using 85 wt % active material, 10 wt % super-S carbon black, and 5 wt % PVDF coated on Al foil at approximately 15 mg/ cm 2 . All cells contained one Celgard 2320 (Celgard), one polypropylene blown microfiber separator (3M), 1 M LiPF6 in 1:2 v/v EC/DEC electrolyte, and a Li metal negative electrode. Cells were cycled using an E-One Moli Energy Canada battery testing system. Current densities of C/60 were calculated using theoretical capacity values from the 0-TM and 3+/4+ model (black and green lines) in Figure 1b. Cells were tested between 2.2 and 4.5 V (vs Li/Li+) at 40 °C. X-ray Absorption Spectroscopy. X-ray absorption spectroscopy data was collected at the REIXS beamline at the Canadian Light Source Synchrotron facility in Saskatoon, Canada. Coin cells were fabricated from the 800 °C x = 0.19 material and charged to 30, 60, 100, and 120% state of charge (SOC) at a rate of C/60 with respect to the observed capacity at 4.5 V for that material and disassembled under argon by staff. The electrodes were rinsed twice using DEC to remove electrolyte and salts and the then dried under argon. Samples were mounted and transferred into the beamline vacuum chamber (
