A Hybrid Physics-Guided Residual Multi-Task Neural Network Framework for Predictive Modeling of Power Conversion Efficiency and Static Electrical Stability in Perovskite Solar Cells
This study proposed a hybrid physics-guided residual multi-task neural network framework based on a large-scale simulated J-V dataset, comprising approximately 2.47 million samples. Physics-based descriptors were constructed, and residual learning with a heuristic empirical baseline was adopted through carrier transpor...