Switchable shape memory polymer bio-inspired adhesive and its application for unmanned aerial vehicle landing

Controlled and switchable adhesion is commonly observed in biological systems.In recent years,many scholars have focused on making switchable bio-inspired adhesives.However,making a bio-inspired adhesive with high adhesion performance and excellent dynamic switching properties is still a challenge.A Shape Memory Polymer Bio-inspired Adhesive(SMPBA)was successfully developed,well realizing high adhesion(about 337 kPa),relatively low preload(about90 kPa),high adhesion-to-preload ratio(about 3.74),high switching ratio(about 6.74),and easy detachment,which are attributed to the controlled modulus and contact area by regulating temperature and the Shape Memory Effect(SME).Furthermore,SMPBA exhibits adhesion strength of80–337 kPa on various surfaces(silicon,iron,and aluminum)with different roughness(Ra=0.021–10.280)because of the conformal contact,reflecting outstanding surface adaptability.The finite element analysis verifies the bending ability under different temperatures,while the adhesion model analyzes the influence of preload on contact area and adhesion.Furthermore,an Unmanned Aerial Vehicle(UAV)landing device with SMPBA was designed and manufactured to achieve UAV landing on and detaching from various surfaces.This study provides a novel switchable bio-inspired adhesive and UAV landing method.

Modeling the distribution of Populus euphratica in the Heihe River Basin, an inland river basin in an arid region of China

Populus euphratica is a dominant tree species in riparian Tugai forests and forms a natural barrier that maintains the stability of local oases in arid inland river basins. Despite being critical information for local environmental protection and recovery, establishing the specific spatial distribution of P. euphratica has rarely been attempted via precise and reliable species distribution models in such areas. In this research, the potential geographic distribution of P. euphratica in the Heihe River Basin was simulated with MaxEnt software based on species occurrence data and 29 environmental variables. The result showed that in the Heihe River Basin, 820 km^2 of land primarily distributed along the banks of the lower reaches of the river is a suitable habitat for P. euphratica. We built other MaxEnt models based on different environmental variables and another eight models employing different mathematical algorithms based on the same 29 environmental variables to demonstrate the superiority of this method.MaxEnt based on 29 environmental variables performed the best among these models, as it precisely described the essential characteristics of the distribution of P. euphratica forest land. This study verified that MaxEnt can serve as an effective tool for species distribution in extremely arid regions with sufficient and reliable environmental variables. The results suggest that there may be a larger area of P. euphratica forest distribution in the study area and that ecological conservation and management of P.euphratica should prioritize suitable habitat. This research provides valuable insights for the conservation and management of degraded P. euphratica riparian forests.