Computational Design and Preparation of Cation‐Disordered Oxides for High‐Energy‐Density Li‐Ion Batteries. Issue 15 (31st May 2016)

• Record Type: Journal Article
• Authors: Urban, Alexander; Matts, Ian; Abdellahi, Aziz; Ceder, Gerbrand
• Is Part Of: Advanced energy materials. Volume 6:Issue 15(2016)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-05-31
• Subjects: lithium batteries -- cation disorder -- cluster expansion -- DFT calculations -- transition‐metal oxides; Energy harvesting -- Materials -- Periodicals; Energy conversion -- Materials -- Periodicals; Energy storage -- Materials -- Periodicals; Photovoltaics -- Periodicals; Fuel cells -- Periodicals; Thermoelectric materials -- Periodicals; 621.31
• DOI: 10.1002/aenm.201600488
• Languages: English
• ISSNs: 1614-6832

Abstract

Abstract : Cation‐disordered lithium‐excess metal oxides have recently emerged as a promising new class of high‐energy‐density cathode materials for Li‐ion batteries, but the exploration of disordered materials has been hampered by their vast and unexplored composition space. This study proposes a practical methodology for the identification of stable cation‐disordered rocksalts. Here, it is established that the efficient method, which makes use of special quasirandom structures, correctly predicts cation‐ordering strengths in agreement with accurate Monte‐Carlo simulations and experimental observations. By applying the approach to the composition space of ternary oxides with formula unit Li A 0.5 B 0.5 O2 ( A, B : transition metals), this study discovers a previously unknown cation‐disordered structure, LiCo0.5 Zr0.5 O2, that may function as the basis for a new class of cation‐disordered cathode materials. This computational prediction is confirmed experimentally by solid‐state synthesis and subsequent characterization by powder X‐ray diffraction demonstrating the potential of the computational screening of large composition spaces for accelerating materials discovery. Abstract : New cation‐disordered materials for Li‐ion battery electrodes can be identified using the rapid computational screening approach established in this article. The methodology is demonstrated for ternary oxides, predicting several previously unknown disordered compositions. As a proof of concept, cation‐disordered LiCo0.5 Zr0.5 O2 is synthesized and characterized, confirming the viability of the approach.