The second rung, Generalized Gradient Approximation (GGA), builds on LDA by incorporating the gradient of the electron density, which accounts for non-homogeneous electron distributions. GGA functionals, such as the widely-used PBE (Perdew-Burke-Ernzerhof) functional, significantly improve accuracy for molecular systems and are commonly applied in chemical and materials science calculations . By considering both the local density and its rate of change, GGA strikes a balance between simplicity and accuracy, making it one of the most popular choices for DFT calculations. However, GGA still has limitations in capturing long-range van der Waals interactions and strong correlation effects. The third rung of Jacob's Ladder, Meta-GGA, takes another step forward by including second-order density derivatives, such as the kinetic energy density. Meta-GGA functionals, like the TPSS functional (Tao-Perdew-Staroverov-Scuseria), aim to improve upon GGA by incorporating even more detailed information about the electron density distribution . Meta-GGA functionals have shown promise in capturing intermediate correlation effects and predicting more accurate thermodynamic properties, reaction barriers, and non-covalent interactions compared to GGA. This rung provides a useful trade-off between computational cost and accuracy, especially for organic molecules, transition states, and catalysis.