Self-powered triboelectric electrospun air filters as functional fibrous materials: Experiment-supported modeling of dielectrophoretic capture and scale-up

Functional fibrous materials that combine electrospun architectures with triboelectric charging are attractive for low-energy particulate capture, but their design still relies largely on empirical testing. This study reports a triboelectrically pre-charged electrospun air-filter platform and a 3D multiphysics model evaluated against previously reported filtration data under a prescribed static charged state. The model couples lattice Boltzmann airflow, electrostatic field calculation, and Lagrangian particle tracking in reconstructed microfiber networks. It separates the mechanical baseline from dielectrophoretic (DEP) enhancement and shows that the DEP force scales cubically with particle diameter, producing stronger capture enhancement for particles above ~200 nm. A dual-thickness scale-up model calibrated to the same 12 previously reported filtration values yields L m = 36.905 μm, L d = 27.436 μm, and f DEP = 0 at the fitted lower bound, with mechanical, charged, and combined RMSE values of 5.641, 3.241, and 4.600 percentage points, respectively. The results provide a materials-to-device analysis route for triboelectrically pre-charged electrospun filtration materials by linking the prescribed charge state, DEP-assisted capture, and scale-up behavior within the tested system, without implying independent validation or dynamic TENG operation.