Journal Highlights

The authors introduce a novel machine learning framework for predicting properties of lead-free perovskites using a neural network incorporating additive kernel regression-based activation functions.Combining the flexibility of neural networks with the interpretability of kernel methods improves prediction accuracy and reliability.This enables more efficient discovery, evaluation, and optimization of environmentally friendly perovskite materials for electronic, optical, and energy applications.