Computational techniques offer a cost-effective and time-efficient alternative to experimental setups, especially for hazardous or unstable compounds. They also enable the exploration of reaction mechanisms at the atomic and electronic levels, providing insights into factors influencing reaction rates and feasibility. For instance, recent studies utilizing computational chemistry have demonstrated accurate predictions of thermodynamic and kinetic parameters for small hydroxy ethers, significantly advancing reaction engineering and energy research . Density Functional Theory (DFT) is a powerful quantum mechanical method widely used to calculate thermodynamic properties, including enthalpy and Gibbs free energy, for chemical reactions such as the combustion of alkanes. A key concept in DFT is the Jacob's ladder, which describes the hierarchy of functionals, improving accuracy as one ascends its levels . The first rung, Local Density Approximation (LDA), considers only electron density, while the second rung, Generalized Gradient Approximation (GGA), adds density gradients for better precision (e.g., PBE). Higher rungs, such as hybrid functionals (e.g., B3LYP) and meta-GGA, include Hartree-Fock exchange and additional corrections, providing superior accuracy for large and complex systems. The choice of functional significantly impacts the reliability of computed ΔH and ΔG values. Table highlights the features, advantages, and limitations of Jacob's ladder methods in Density Functional Theory (DFT), along with dispersion correction techniques (e.g., DFT-D). While Jacob's ladder methods improve accuracy with higher rungs, they often struggle with long-range interactions, which are better addressed using dispersion correction methods. -Examples: LSDA , SVWN .