2020
DOI: 10.1002/batt.201900186
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Materials Informatics Screening of Li‐Rich Layered Oxide Cathode Materials with Enhanced Characteristics Using Synthesis Data

Abstract: Lithium-ion batteries (LIBs) are the objects of active research and attract interest as important elements of near-term energy storage technologies. The ever-growing requirements for cathode materials of next-generation LIBs impel the need to screen the materials with high energy and power densities, cycling stability, rate capability, safety and compatibility with other battery elements. This study is focused on Li-rich layered oxide cathode materials as the materials candidates that are characterized by high… Show more

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Cited by 21 publications
(10 citation statements)
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“…[1][2][3] The latter two compounds have been subject to a variety of efforts aimed at optimising their electrochemical performance as a step towards commercialization. [4][5][6][7] Despite the research attention, the crystallographic description of these materials suffers from a distinct lack of consensus, [8][9][10] possibly due to a high susceptibility to synthetic variations. [11][12][13][14][15] Previously, the interdependencies between the synthesis, composition and structure of (non-Li-rich) Li transition metal (TM) oxides have been explored through combinatorial studies.…”
Section: Introductionmentioning
confidence: 99%
“…[1][2][3] The latter two compounds have been subject to a variety of efforts aimed at optimising their electrochemical performance as a step towards commercialization. [4][5][6][7] Despite the research attention, the crystallographic description of these materials suffers from a distinct lack of consensus, [8][9][10] possibly due to a high susceptibility to synthetic variations. [11][12][13][14][15] Previously, the interdependencies between the synthesis, composition and structure of (non-Li-rich) Li transition metal (TM) oxides have been explored through combinatorial studies.…”
Section: Introductionmentioning
confidence: 99%
“…In addition, the authors proposed optimal experimental parameters by conducting inverse design, which they successfully validated with additional experiments. In a more recent study, Kireeva and Pervov also considered experimental data sets to identify synthesis and electrochemical property relationships in Li-rich layered oxide cathodes using a SVM model . In this case, input variables included composition, synthesis method, Li and transition metal sources, Li excess, temperature, and time of calcination and sintering; whereas initial discharge capacity and Coulombic efficiency were set as output variables.…”
Section: Application To Materials Design and Synthesismentioning
confidence: 99%
“…The stack noise reduction selfcoder further calculates the collected teaching data affecting college mental health. In the learning process, further extract the sample features, image features, or text data features of the data to be learned [19], so as to further learn the received abstract sample data, and apply the learning results to the nearest neighbor algorithm for further prediction and scoring [20,21]. Through this algorithm, we can actively search and find the information with high user interest from the massive database information and recommend the information to the users.…”
Section: Data Recommendation System Based On Deep Learningmentioning
confidence: 99%