Along with the functional, a basis set is required for DFT calculation. It provides the mathematical framework to describe the wavefunctions of electrons in atoms and molecules. A basis set is a collection of functions, typically centered on atoms, used to construct molecular orbitals as linear combinations . These functions approximate the solutions to the Schrödinger equation, enabling the calculation of molecular properties like energy, dipole moments, and geometries. Commonly used basis functions include Gaussian functions and Slater-type orbitals (STOs), with Gaussian functions being more computationally efficient. There are 6 types of basis sets which are commonly used for computational calculations. Those are presented in Table . The choice of a basis set depends on the system being studied and the available computational resources. There is often a trade-off between accuracy and efficiency, as larger basis sets provide more accurate results but require significantly higher computational costs. The type of calculation also influences the choice; for example, geometry optimizations can often be performed with mid-level basis sets like 6-31G(d), while tasks demanding high accuracy may necessitate advanced sets such as cc-pVQZ or aug-cc-pVTZ. Additionally, the nature of the system plays a critical role; diffuse functions are essential for accurately modeling anions, whereas effective core potentials (ECPs) simplify computations for systems involving heavy elements . The Basis Set Superposition Error (BSSE) arises when basis sets are shared between fragments in molecular systems, leading to artificial stabilization . To address this issue, techniques such as the counterpoise correction are employed to ensure reliable binding energy calculations. In density functional theory (DFT), the choice of basis sets is as important as the functional itself. Commonly used sets include Pople-style basis sets (e.g., 6-31G*) and correlation-consistent sets, while plane-wave basis sets are often preferred for periodic systems . Recent advancements in the field focus on innovative approaches like density-fitted basis sets, which aim to reduce computational demands in correlated methods, and machine-learning-augmented basis sets, which optimize basis functions for specific systems to enhance efficiency and accuracy . DFT calculations optimize molecular geometries and calculate the frequency of a molecule. All the thermochemistry data are stored in the output file of the DFT simulation. In alkane combustion, the lowest energies of reactants (CnH2n+2 and O2) and products (CO2 and H2O) are required to compute the energy changes due to the reaction. Overall, with the advancement of computational resources, reaction engineers are increasingly getting interested in using quantum chemistry techniques for its simplicity and convenience to integrate ΔH and ΔG values into advanced models of combustion kinetics and thermodynamics.