Dataset for: Exploring Battery Cathode Materials in the Li-Ni-O Phase Diagrams using Structure Prediction
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The Li-Ni-O phase diagram contains several electrochemically active ternary phases. Many compositions and structures in this phase space can easily be altered by (electro-)chemical processes, yielding many more (meta-)stable structures with interesting properties. In this study, we use<em> ab initio </em>random structure searching (AIRSS) to accelerate materials discovery of the Li-Ni-O phase space. We demonstrate that AIRSS can efficiently explore structures (e.g. LiNiO<sub>2</sub>) displaying dynamic Jahn-Teller effects. A thermodynamically stable Li<sub>2</sub>Ni<sub>2</sub>O<sub>3</sub> phase which reduces the thermodynamic stability window of LiNiO<sub>2</sub> was discovered. AIRSS also encountered many dynamically stable structures close to the convex hull. Therefore, we confirm the presence of metastable Li-Ni-O phases by revealing their structures and properties. This work will allow Li-Ni-O phases to be more easily identified in future experiments and help to combat the challenges in synthesizing Li-Ni-O phases. This dataset contains the raw research data and key analysis files for "Exploring Battery Cathode Materials in the Li-Ni-O Phase Diagrams using Structure Prediction". `known_phases_aiida_data.zip` and `new_phases_exports.aiida.zip` contain the archives exported from the AiiDA framework which was used to perform parts of the DFT calculations for this project. `search_data.zip` contains search seed files and the structures generated by the searches. `data_analysis.zip` contains the data and notebooks to reproduce the figures and tables shown in the manuscript.
