Dataset for: Exploring Battery Cathode Materials in the Li-Ni-O Phase Diagrams using Structure Prediction

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 ab initio 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. LiNiO2) displaying dynamic Jahn-Teller effects. A thermodynamically stable Li2Ni2O3 phase which reduces the thermodynamic stability window of LiNiO2 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.