The electronic and optical properties of polythiophene (PT) for polymer light-emitting diodes (PLEDs) were calculated using density functional theory (DFT) and time-dependent DFT. We calculated the electronic and optical properties of thiophene and PT polymers with degrees of polymerization (DP) from 2 to 30 monomers (T1–T30) and their derivatives. The associated highest occupied molecular orbital (HOMO) energy, lowest unoccupied molecular orbital (LUMO) energy, band gaps, electron orbitals, and molecular structures were determined. As the DP increased, the LUMO energy gradually decreased, and the HOMO energy gradually increased. The band gap of PT approached 2 eV as the DP of the PT polymer increased from 1 to 30. The calculations and exchange–correlation functional were verified against values in the literature and experimental data from cyclic voltammetry (redox potential) and ultraviolet-visible, photoluminescence, and ultraviolet photoelectron spectra. The color of PT PLEDs can be adjusted by controlling the DP of the polymer and the substituents.

As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, efficacy prediction, and fault diagnosis, it is crucial to rapidly and accurately establish reliability modules and extract parameters from the system modules. This study employed three types of particle swarm optimization (PSO) algorithms to find the optimal parameters of two energy models by minimizing the sum squared errors (SSE) and roots mean squared errors (RMSE). The three algorithms are inertia weight PSO, constriction PSO, and momentum PSO. The obtained calculation results of these three algorithms were compared with those obtained using algorithms from other relevant studies. This study revealed that the use of momentum PSO enables rapid convergence (under 30 convergence times) and the most accurate modeling and yields the most stable parameter extraction (SSE of PEMFC is 2.0656, RMSE of PV cells is 8.839 · 10⁻⁴). In summary, momentum PSO is the algorithm that is most suitable for system parameter identification with multiple dimensions and complex modules.

The near-infrared (NIR) absorption of nitrogen-doped graphene quantum dots (NGQDs) containing different N-doping sites is systematically investigated with density functional theory (DFT) and time-dependent density functional theory (TD-DFT) calculations with PBE functionals.