Microstructure inference of organic thin films via light modulated photocurrent characterization

The performance of organic electronic devices is closely tied to their nanoscale donor–acceptor microstructure, yet quantifying these features remains challenging using conventional characterization tools. X-ray scattering and electron microscopy techniques provide high-fidelity structural information, but they are slow, expensive, and challenging to deploy in high-throughput or autonomous processing environments. Here, we propose a complementary, proxy-based route to microstructure inference that leverages the device's transient short-circuit current response under modulated illumination. Using a microstructure-aware excitonic drift–diffusion (EDD) framework that incorporates arbitrary time-dependent generation profiles, we compute current (J(t)) responses for 500 computationally generated donor–acceptor morphologies subjected to full-wave-rectified sinusoidal excitation. From each response, we extract a suite of physically motivated time- and frequency-domain features and pair them with key microstructural descriptors, specifically interfacial area, characteristic domain size, and connectivity. SHAP-based feature selection reveals that a compact subset of transient-response features captures most of the microstructure dependence. Linear surrogate models trained on these subsets achieve good test R² across all descriptors, with interfacial area and domain-size predictions exceeding R²=0.9, using fewer than 10% of the simulated morphologies for training. These results demonstrate that high-frequency, amplitude-modulated electrical measurements can recover essential microstructural fingerprints, suggesting a pathway toward compact, non-destructive, and automation-ready characterization tools for high-throughput research in organic electronics.