Ionic Transport in Doped Solid Electrolytes by Means of DFT Modeling and ML Approaches: A Case Study of Ti-Doped KFeO₂

Abstract

We present a comprehensive study on the influence of Ti doping on K+ migration in the K1–x Fe1–x Ti x O2 solid electrolyte. A novel approach is proposed which is based on modeling of configurational spaces (CSs) and full sets of inequivalent migration pathways by means of density functional theory (DFT) calculations and machine learning (ML) techniques. A 2 × 1 × 1 supercell (32 formula units) of a low-temperature polymorph of the KFeO2 compound with space group symmetry Pbca was used. For the three lowest Ti contents (x = 0.03, 0.06, and 0.09), all symmetrically inequivalent configurations of atomic arrangements (CSs) and K+ migration pathways (total numbers: 128, 59520, and 8630400) were generated. With the DFT-derived energetics of K+ migration at the lowest doping level (x = 0.03), the ML models were trained to predict ionic transport properties by using geometrical descriptors for the pathway-dopant arrangement. The trained ML models were then used to evaluate the K+ migration properties for pathways at higher doping levels. The computational results obtained are in good agreement with the results of a previous experimental study of the title compound. This demonstrates the applicability of the proposed approach for modeling and predicting effects of doping in crystalline solids, such as solid electrolytes and intercalation cathodes. Brief recommendations are given on the application of the proposed combined approach.

Computational Search for Novel Zn-Ion Conductors—A Crystallochemical, Bond Valence, and Density Functional Study

“…The small variations of E m (Zn 2+ ) for the ZnFeGaO 4 and ZnFeCrO 4 supercells (<0.02 eV) show that ordering on the mixed Wyckoff sites might have a minor influence on the Zn pathways. This is also consistent with the example given in Wong et al Hence, the tuning of the E m of these structures by doping might be achieved by taking into account other elements or sites; see for example Eremin et al and Wong et al…”

“…The small variations of E m (Zn 2+ ) for the ZnFeGaO 4 and ZnFeCrO 4 supercells (<0.02 eV) show that ordering on the mixed Wyckoff sites might have a minor influence on the Zn pathways. This is also consistent with the example given in Wong et al 34 Hence, the tuning of the E m of these structures by doping might be achieved by taking into account other elements or sites; see for example Eremin et al 42 and Wong et al 37 We further studied the ionic conductivity σ by roomtemperature KMC simulations. Among the shortlisted compounds in Table 1, KMC results suggest that Zn 0.5 Ti 2 P 3 O 12 and Zn 3 Mo 3 O 8 with simulated σ > 10 −3 S/cm should have the highest ionic conductivities.…”

Combined DFT and geometrical–topological analysis of Li-ion conductivity in complex hydrides

“…The method implemented in a step-by-step manner used within the current research was recently proposed and tested for solid state electrolytes. 25,26 The relaxation (cell shape/ volume and atom positions) of the available crystal structures was performed using the projector-augmented wave approach with the Perdew-Burke-Ernzerhof (PBE) 27 exchange-correlation functional as implemented in Vienna Ab Initio Simulation Package (VASP). 28 The recommended pseudopotentials were used for each chemical element.…”

K+ extraction induced phase evolution of KFeO2

“…[7][8][9][10][11][12] Furthermore, K + cations are capable of migration in the FeO 2 framework, making KFeO 2 a potential cathode or solid-state electrolyte material for rechargeable potassium batteries. [13][14][15][16][17] However, K + cations are prone to extraction when exposing KFeO 2 to a moist environment, which gives rise to phase evolution and subsequently severe performance loss.…”