This project aims to establish a computational framework for understanding the relationship between molecular packing and electronic properties in organic photovoltaic (OPV) materials. Organic solar cells based on non-fullerene acceptors have achieved power conversion efficiencies exceeding 20%, yet the molecular-level origins of efficient charge generation at donor–acceptor interfaces remain poorly understood. We will employ density functional theory (DFT) and machine-learning-driven molecular dynamics (ML-MD) simulations to investigate prototypical OPV systems, including polymer donors (e.g., PM6, D18) and non-fullerene acceptors (e.g., Y6 and its derivatives). The computational workflow proceeds in three stages: (1) geometry optimization and electronic structure calculations of isolated molecules and dimers using Gaussian 16 at the B3LYP/6-31G(d) level, extracting frontier orbital energies, reorganization energies, and electrostatic potential surfaces; (2) molecular dynamics simulations of bulk and thin-film morphologies using the MACE-OFF universal organic force field, generating equilibrated molecular packing configurations; and (3) validation of simulated packing structures against experimental grazing-incidence wide-angle X-ray scattering (GIWAXS) data available in our group. This project directly supports ongoing experimental work in the LOE/YFK group at Linköping University, where we investigate interface energetics using ultraviolet and X-ray photoelectron spectroscopy (UPS/XPS). The computational results will provide atomistic insight into experimentally observed phenomena such as ambient-induced surface doping, interface dipole formation, and trap state generation in OPV devices. Supervisor:Prof. Mats Fahlman and Xianjie Liu (Linköping University,Laboratory of Organic Electronics)