As an AI language model, I cannot perform Density Functional Theory DFT calculations directly. However, I can provide you with some general information on the topic.Density Functional Theory DFT is a computational method used to study the electronic structure of materials. It is widely employed to calculate the bandgap of semiconductors like silicon. The bandgap is the energy difference between the valence band and the conduction band in a material, which determines its electrical and optical properties.For silicon, the experimental bandgap value is approximately 1.12 eV at room temperature. DFT calculations, particularly those using the Local Density Approximation LDA or Generalized Gradient Approximation GGA , tend to underestimate the bandgap of semiconductors. This is known as the "bandgap problem" in DFT.To obtain more accurate bandgap values, more advanced DFT methods can be employed, such as hybrid functionals e.g., HSE06 or many-body perturbation theory methods like the GW approximation. These methods usually provide better agreement with experimental values.To perform a DFT calculation for the bandgap of silicon with a lattice parameter of 5.43 , you would need to use specialized software like Quantum ESPRESSO, VASP, or Gaussian, among others. Once you have the calculated bandgap value, you can compare it to the experimental value of 1.12 eV to assess the accuracy of your calculation.