Development of a Bionic Self-Cleaning Drill Tool toward Enhanced In-Situ Fidelity in Subsea Sediment Sampling

Subsea sediment sampling is of great significance for marine geological research, resource exploration, environmental assessment, and geotechnical investigation. However, due to the common characteristics of high clay content, high water content, and under-consolidation of seabed sediments, conventional sampling techniques often cause severe sample disturbance, compression, or even loss. This leads to engineering challenges such as low core recovery and destruction of the original structure, which significantly compromises the in-situ characteristics and representativeness of the samples.Inspired by organisms (such as lotus leaves and earthworm) that maintain clean body surfaces in viscous environments, this study developed a material-structure coupled bionic anti-adhesion and drag-reduction surface by mimicking their micro-nano structure and low interfacial energy characteristics. This surface was constructed using a specific etching process combined with a low interfacial energy material coating technique and applied to the key contact parts of a subsea sediment sampling drill tool. Microstructural characterization and comparative sampling tests in typical clay and silty clay demonstrated that the bionic drill tool significantly reduces soil adhesion and frictional resistance during the sampling process. Consequently, it substantially increases the core recovery rate and effectively preserves the original stratigraphic sequence and moisture condition of the samples, markedly enhancing their in-situ fidelity.The bionic self-cleaning surface technology proposed in this study offers an innovative solution to the technical bottleneck of low-disturbance, high-fidelity sampling of highly viscous subsea sediments. Preliminary tests have verified the chemical stability and corrosion resistance of the surface coating in simulated seawater environments. Its long-term service reliability and large-scale engineering application processes require further research and optimization.