Lithium-ion batteries are commonly used for portable electronics, electric vehicles, and aerospace applications. During discharge, Lithium ions move from the negative electrode through an electrolyte to the positive electrode to create a voltage and current. During recharging, the ions migrate back to the negative electrode.
To perform EDA on the crystal system of Li-ion battery and to classify the battery class as monoclinic, orthorhombic and triclinic on the basis of their crystal system.
The dataset contains the physical and chemical properties of the Li-ion silicate cathodes. These properties are used to predict the class of a Li-ion battery on the basis of their crystal system. This data consist of 339 rows and 11 columns.
- Formula: chemical formula of the compound.
- Space group: symmetry group of a 3D crystal pattern.
- Formation Energy : energy required to produce material from standard elements.
- E Above Hull : energy released if compound is decomposed to the most stable compounds.
- Band Gap : Larger band gap indicates that the compound is worse at conducting electricity or heat.
- Nsites : Number of atoms in the unit cell of the crystal.
- Density : mass per volume of bulk crystalline materials.
- Volume: unit cell volume of the material
- Band structure : Boolean variable for band structure.
- The crystal structure has a major effect on the physical and chemical properties of Li-ion batteries. These properties can be useful to predict the class of a Li-ion battery.
- These batteries can be classified on the basis of their crystal system. that include monoclinic, orthorhombic and triclinic.
- Comparing the ML models, the Random forest classifier has the highest accuracy and wins the race among the other models. Thereby making a better predictions and achieve better performance.