Magnetic wood composite for electromagnetic shielding: Experimental study and machine learning predictions

The use of electronic instruments is increasing globally, and at the same time, the demand for shielding the electromagnetic (EM) radiation from these instruments is also growing. In this study, magnetic wood-based polymer composites are proposed for EM wave absorption. For this purpose, Red oak wood was chosen as the filler, and composites (Specimens I, II, and III) were fabricated by hand lay-up technique and subjected to chemical treatment for 0, 24, and 48 h. The specimens are evaluated for EM properties of permittivity, permeability, tangent losses, and Reflection Loss (RL), and mechanical properties of tensile and flexural. In addition, regression and machine learning techniques are implemented to observe the influence of chemical treatment on EM and mechanical properties. The results reveal that, with increased duration of chemical interaction, the composite specimens' properties were enhanced. It is also observed that Specimen III (48 h of treatment) exhibits improvements of 35.85% in tensile stress, 53.84% in flexural stress, and RL by 43.75% compared to Specimen I. Similarly, regression and machine learning (ML) techniques show strong correlations between the chemical treatment and mechanical and EM properties, with high R² values. These results outline the wood composite as one of the feasible materials for EM shielding applications. • Red Oak wood as an EM wave absorption polymer composite material. • High chemical interaction enhances the EM properties. • ML techniques like SVR, XGBoost, and ANN, were utilized for corelation of properties.