Nitrogen Fixation Optimization Strategy Based on a Tree‐Structured Parzen Estimator‐Multilayer Perceptron (TPE‐MLP) Model

ABSTRACT Atmospheric‐pressure non‐thermal plasma has shown great potential in the field of nitrogen fixation (NF). In this study, a Magnetic Field Stabilized Glow Discharge (MSGD) device is employed, utilizing Lorentz forces generated by an external magnetic field to stabilize the plasma channel. It enhances gas utilization and reduces energy cost compared to traditional gliding arc discharges. To address the challenge of plasma parameters involved, experimentally optimizing NF energy cost across numerous plasma parameters, a Multilayer Perceptron (MLP) model is trained to predict NF energy cost and NO X concentration and energy cost. Hyperparameters are optimized using the tree‐structured Parzen estimator (TPE), and gradient analysis is conducted to evaluate feature importance. The results demonstrate that this approach enables accurate prediction and offers an effective strategy for optimizing plasma‐based NF processes.