The combination of genetic algorithm and neural network approach (GANN) has been developed to improve the calculation accuracy of density functional theory. As a demonstration, this combined quantum mechanical calculation and GANN correction approach has been applied to evaluate the optical absorption energies of 150 organic molecules. The neural network approach reduces the root-mean-square (rms) deviation of the calculated absorption energies of 150 organic molecules from 0.47 to 0.22 eV for the TDDFTB3LYP6-31G(d) calculation, and the newly developed GANN correction approach reduces the rms deviation to 0.16 eV.

Recently, potassium iodide was inserted into single-walled carbon nanotubes. We present here a first-principles density-functional theory calculation of the electronic and optical properties of a potassium iodide intercalated (10,10) nanotube. Band structure, density of states, and charge distribution of the intercalated nanotube are determined. Significant changes in the electronic structure of carbon nanotube are found upon the intercalation. In particular, the electron distribution on the tube becomes more diffusive, and one out of every four K4s electrons transfers to the tube wall, while the other three go to I5p orbitals.

The segment-molecular-orbital representation is developed and incorporated into the recently developed linear-scaling localized-density-matrix method. The entire system is divided into many segments, and the molecular orbitals of all segments form the basis functions of the segment-molecular-orbital representation. Introduction of different cutoff lengths for different segment-molecular-orbitals leads to a drastic reduction of the computational cost. As a result, the modified localized-density-matrix method is employed to investigate the optical responses of large Poly(p-phenylenevinylene͒ aggregates. In particular, the interchain excitations are studied. The complete neglect of differential overlap in spectroscopy hamiltonian is employed in the calculation.