Shape memory superamphiphobic sponge: a tunable platform for oil aerosol filtration

Abstract

Oil aerosol emissions from industrial processes pose severe environmental and health risks, demanding advanced filtration solutions. Conventional 2D fibrous filters are efficient but suffer from high airflow resistance; in contrast, 3D porous materials offer lower pressure drops but lack structural tunability, limiting their performance optimization. Herein, we propose a structurally adaptive 3D superamphiphobic sponge filter leveraging shape memory polymers (SMPs) to achieve controllable oil aerosol capture. The shape memory superamphiphobic sponge (SMSAS) was fabricated by sequentially coating a polyurethane sponge with an SMP layer and fluorinated SiO₂ nanoparticles, enabling programmable structural reconfiguration upon radial and axial compression. By tailoring pore geometry and compression ratios, the SMSAS filters achieved a balance between efficiency and airflow resistance, realizing up to 95% filtration efficiency with an ultralow pressure drop of 0.054 kPa and a quality factor of 57.02 kPa⁻¹. This work pioneers the integration of shape memory functionality into oil aerosol filtration, offering a versatile strategy to design adaptive 3D filters with tunable architectures for energy-efficient and durable air purification. Moreover, we investigated the factors influencing the separation efficiency of three-dimensional filters, providing valuable guidance for subsequent material design of novel filter media.