Bioinspired multifunctional antifogging surfaces: Progress, AI design and challenges

Abstract

Over the past few decades, various antifogging strategies and preparation methods have been proposed. Unfortunately, a surface with a single antifogging function cannot achieve a wide range of practical applications. For example, medical endoscopes require antifogging and antibacterial capabilities to improve diagnostic accuracy and safety. Inspired by the near-perfect multifunctional properties of natural creatures, antifogging materials with specific functions have drawn more and more attention owing to their promising and wide applications. However, the design of bioinspired antifogging surfaces with broad applicability still presents some challenges, such as the integration of multifunctional properties, and the optimization of preparation routes. In this review, beginning with the fogging mechanism and wettability theory, the latest antifogging surface materials and pattern designs are analyzed in detail and critically evaluated. The natural biomaterials with multifunctional characteristics are summarized, and the integration mechanism and design difficulties of the four multifunctional characteristics are then emphatically analyzed. Based on artificial intelligence (AI) assisted design optimization, we introduce the neural network into the bionic multifunction antifogging path realization for the first time and summarize the antifogging prototype and antifogging multifunction database. Finally, the challenges and future trends of bioinspired multifunction antifogging surfaces (MF-AFS) are presented.