Mechanobiology-aware autonomous antifouling interfaces: multimodal sensing, adaptive actuation, and closed-loop biofouling control.

Abstract

Biofouling is a dynamic, spatially heterogeneous, and history-dependent interfacial process, whereas most control strategies remain static or calendar-based. This mismatch can cause unnecessary chemical and energy use, delayed intervention, coating damage, and incomplete recovery. This critical review develops a mechanobiology-aware framework for autonomous antifouling interfaces that detect a fouling-relevant signal, estimate latent interfacial state, select a bounded action, actuate locally, and verify recovery. It links conditioning-film ageing, bacterial surface sensing, cyclic di-GMP-mediated commitment, extracellular polymeric substance assembly, collective mechanics, transport limitation, community interactions, and dispersal to optical, electrochemical, acoustic, mechanical, and molecular sensing. Electrochemical, optical, thermal, acoustic, hydrodynamic, topographic, hydrated or liquid-infused, enzymatic, and quorum-interference actuation are evaluated in relation to target state and failure mode. Passive resistance, pre-programmed responsiveness, and genuine closed-loop operation are distinguished explicitly. The proposed architecture treats the fouled interface as a partially observed system in which multimodal measurements support an uncertainty-aware state estimate, a constrained policy selects the least harmful action likely to succeed, and post-action sensing verifies biological and functional recovery. Reduced digital-twin models are positioned as decision-support tools rather than as established universal solutions. Key deployment requirements include calibration transfer, sensor self-fouling, latency, material ageing, detached-biomass capture, release accounting, safe fallback, and direct comparison with the identical actuator operated open-loop.