Localized Self-Growth of Reconfigurable Architectures Induced by a Femtosecond Laser on a Shape-Memory Polymer

Abstract

Architectures of natural organisms especially plants largely determine their response to varying external conditions. Nature-inspired shape transformation of artificial materials has motivated academic research for decades due to wide applications in smart textiles, actuators, soft robotics, and drug delivery. A "self-growth" method of controlling femtosecond laser scanning on the surface of a prestretched shape-memory polymer to realize microscale localized reconfigurable architectures transformation is introduced. It is discovered that microstructures can grow out of the original surface by intentional control of localized laser heating and ablation, and resultant structures can be further tuned by adopting an asymmetric laser scanning strategy. A distinguished paradigm of reconfigurable architectures is demonstrated by combining the flexible and programmable laser technique with a smart shape-memory polymer. Proof-of-concept experiments are performed respectively in information encryption/decryption, and microtarget capturing/release. The findings reveal new capacities of architectures with smart surfaces in various interdisciplinary fields including anti-counterfeiting, microstructure printing, and ultrasensitive detection.

Keywords: femtosecond lasers; polymer self-growth; reconfigurable architectures; shape transformation; shape-memory polymers.