Executive Summary : | Discovering novel materials in energy and environment is crucial for human sustenance. Theory, computation, and informatics approaches have become indispensable in rational design of such materials. First-principles calculations have become popular in recent decades, but they are time-consuming and can be viewed as one-compound-at-a-time. Data-driven approaches have shown fruitful results in bio- and chemo-informatics, motivating researchers to employ them in materials informatics. This approach reduces the time frame between materials discovery, development, and deployment. Designing materials for energy storage and conversion is of great interest due to their exceptional physio-chemical properties and extensive energy storage and conversion applications. Two-dimensional (2D) nanomaterials like transition metal chalcogenides, graphitic carbon nitride, and transition metal carbides/nitrides have sparked attention due to their exceptional properties. Data-driven approaches combined with first-principles calculations have been effectively used to discover novel materials for Li-ion batteries, piezoelectric, photocatalytic, and thermoelectric applications. The computational database study of MX2 compounds provides trends and correlations based on their electronic structures. Combining big data approaches with first-principles calculations can help tackle energy storage and conversion, create a database, and derive structure-property correlations using machine learning algorithms. |