Browsing by Author "Zhang, WQ"

Now showing 1 - 5 of 5
  • No Thumbnail Available
    Item
    Ab initio thermodynamic optimization of Ni-rich Ni–Co–Mn oxide cathode coatings
    (Elsevier, 2020-02-29) Liu, B; Liu, JH; Yang, J; Wang, D; Ye, CC; Wang, DY; Avdeev, M; Shi, S; Yang, JH; Zhang, WQ
    The effectiveness of surface coatings in improving the stability and cycling performance of cathodes has been demonstrated since they are first proposed in the 1990's. However, the progress since then is made mostly using the trial-and-error method. Herein, an automated electrochemical-chemical stability design scheme based on first-principles thermodynamics calculations of reaction models is presented to optimize coatings for Ni-rich nickel–cobalt–manganese oxide (NCM) cathodes. Given that the coating must possess a wider electrochemical window than the cathode without the occurrence of Li-ion redistribution at the cathode/coating interface, the reaction energies of both lithium insertion/extraction and decomposition process associated with the coating are used as one of the two screening criteria. As the coating is also required to be chemically stable in Li residues and hydrofluoric-acid containing liquid environment, the positive reaction energy achieved by adjusting molar ratio of the components is used as another criterion. Using these two screening criteria, we demonstrate that lithium-containing metal phosphates, rather than previously suggested Li-containing metal oxides, are the optimal coatings for Ni-rich NCM cathodes, which is confirmed experimentally. The proposed approach is general and can be used to find optimal coating materials for any other cathodes. © 2020 Elsevier B.V.
  • Thumbnail Image
    Item
    CAVD, towards better characterization of void space for ionic transport analysis
    (Springer Nature, 2020-05-22) He, B; Ye, AJ; Chi, ST; Mi, PH; Ran, YB; Zhang, LW; Zou, XX; Pu, BW; Zhao, Q; Zou, Z; Wang, D; Zhang, WQ; Zhao, JT; Avdeev, M; Shi, S
    Geometric crystal structure analysis using three-dimensional Voronoi tessellation provides intuitive insights into the ionic transport behavior of metal-ion electrode materials or solid electrolytes by mapping the void space in a framework onto a network. The existing tools typically consider only the local voids by mapping them with Voronoi polyhedra vertices and then define the mobile ions pathways using the Voronoi edges connecting these vertices. We show that in some structures mobile ions are located on Voronoi polyhedra faces and thus cannot be located by a standard approach. To address this deficiency, we extend the method to include Voronoi faces in the constructed network. This method has been implemented in the CAVD python package. Its effectiveness is demonstrated by 99% recovery rate for the lattice sites of mobile ions in 6,955 Li-, Na-, Mg- and Al-containing ionic compounds extracted from the Inorganic Crystal Structure Database. In addition, various quantitative descriptors of the network can be used to identify and rank the materials and further used in materials databases for machine learning. © 2020, The Author(s)
  • No Thumbnail Available
    Item
    High-throughput computational screening of Li-containing fluorides for battery cathode coatings
    (American Chemical Society, 2020-12-16) Liu, B; Wang, D; Avdeev, M; Shi, S; Yang, J; Zhang, WQ
    Cathode degradation is a key factor that limits the cycling stability and rate capability of Li-ion batteries. Coating the surface of cathode particles with metal oxides or fluorides has been reported to suppress this degradation. However, poor Li-ion conductivity of metal oxide and fluoride coatings typically decreases the overall ionic conductivity. In addition, side (electro)chemical reactions at the coating/cathode interface and coating/hydrofluoric acid liquid environment also limit the performance of Li-ion batteries. Identification of stable coating materials with high Li-ion conductivity, which is typically done via a trial-and-error approach, remains a challenge. In this work, we perform high-throughput computational screening of ternary Li-containing fluorides for application as cathode coatings for Li-ion batteries, focusing on their phase stability, electrochemical stability, chemical stability, and Li-ion conductivity. Using the tiered screening approach, we identify 10 promising coating candidates from all the 920 Li-containing fluorides listed in the Materials Project database, including the two experimentally studied Li2ZrF6 and Li2TiF6 compounds. The identified cathode coatings are expected to exhibit optimal battery cycling and rate performance. In particular, Li2MF6 (M = Si, Ge, Zr, Ti) compounds offer the best combination of electrochemical and chemical stability and ionic conductivity, surpassing the performance of common coatings such as oxides and binary fluorides. © 2019 American Chemical Society
  • Thumbnail Image
    Item
    High-throughput screening platform for solid electrolytes combining hierarchical ion-transport prediction algorithms
    (Springer Nature, 2020-05-21) He, B; Chi, ST; Ye, AJ; Mi, PH; Zhang, LW; Pu, B; Zou, Z; Ran, YB; Zhao, Q; Wang, D; Zhang, WQ; Zhao, JT; Adams, S; Avdeev, M; Shi, S
    The combination of a materials database with high-throughput ion-transport calculations is an effective approach to screen for promising solid electrolytes. However, automating the complicated preprocessing involved in currently widely used ion-transport characterization algorithms, such as the first-principles nudged elastic band (FP-NEB) method, remains challenging. Here, we report on high-throughput screening platform for solid electrolytes (SPSE) that integrates a materials database with hierarchical ion-transport calculations realized by implementing empirical algorithms to assist in FP-NEB completing automatic calculation. We first preliminarily screen candidates and determine the approximate ion-transport paths using empirical both geometric analysis and the bond valence site energy method. A chain of images are then automatically generated along these paths for accurate FP-NEB calculation. In addition, an open web interface is actualized to enable access to the SPSE database, thereby facilitating machine learning. This interactive platform provides a workflow toward high-throughput screening for future discovery and design of promising solid electrolytes and the SPSE database is based on the FAIR principles for the benefit of the broad research community. © 2020, The Author(s)
  • No Thumbnail Available
    Item
    A highly efficient and informative method to identify ion transport networks in fast ion conductors
    (Elsevier, 2021-01-15) He, B; Mi, PH; Ye, AJ; Chi, ST; Jiao, Y; Zhang, LW; Pu, BW; Zou, Z; Zhang, WQ; Avdeev, M; Adams, S; Zhao, JT; Shi, S
    High-throughput analysis of the ion transport pathways is critical for screening fast ion conductors. Currently, empirical methods, such as the geometric analysis and bond valence site energy (BVSE) methods, are respectively used for the task. Geometric analysis method can only extract geometric and topological pathway properties without considering the interatomic interactions, while the BVSE method alone does not yield a geometric classification of the sites and interstices forming the pathway. Herein, we propose a highly efficient and informative method to identify interstices and connecting segments constructing an ion transport network by combining topological pathway network and BVSE landscape, which enables to obtain both the geometry and energy profiles of nonequivalent ion transport pathways between adjacent lattice sites. These pathways can be further used as the input for first-principles nudged elastic band calculations with automatically generated chains of images. By performing high-throughput screening of 48,321 Li-, Na-, Mg- and Al-containing ionic compounds from the Inorganic Crystal Structure Database based on the filter combining geometric analysis and BVSE methods, we obtain 1,270 compounds with connected ionic migration pathways of suitable sizes and low migration energy barriers, which include both previously reported fast ion conductors, and new promising materials to be explored further. © 2020 Acta Materialia Inc. Published by Elsevier Ltd.