材料科学                        
                
                                
                        
                            汗水                        
                
                                
                        
                            大规模运输                        
                
                                
                        
                            织物                        
                
                                
                        
                            吸收(声学)                        
                
                                
                        
                            纳米技术                        
                
                                
                        
                            复合材料                        
                
                                
                        
                            化学工程                        
                
                                
                        
                            工程物理                        
                
                                
                        
                            海洋学                        
                
                                
                        
                            地质学                        
                
                                
                        
                            工程类                        
                
                        
                    
            作者
            
                Han-chao Zhang,Zhan-xiao Kang,Yuxi Wu,Yi Pu,Shou-kun Jiang,Amir Shahzad,Peng Wang,Jintu Fan            
         
                    
            出处
            
                                    期刊:Nano Energy
                                                         [Elsevier BV]
                                                        日期:2024-06-25
                                                        卷期号:128: 109919-109919
                                                        被引量:8
                                 
         
        
    
            
            标识
            
                                    DOI:10.1016/j.nanoen.2024.109919
                                    
                                
                                 
         
        
                
            摘要
            
            Asymmetric (viz. Janus or one-way transport) fabrics that can promote directional sweat transport from the next-to-the-skin surface to the outer surface by the hydrophobic-hydrophilic difference across the fabric thickness have been developed. However, the hydrophobic next-to-the-skin surface inevitably increases the inherent resistance to sweat transportation into the fabric, fundamentally hampering its moisture management property. In this work, by selectively coating a poly-pyrrole (ppy) film with Turing patterns on one side of the fabric to achieve superspreading property, we demonstrated an all-hydrophilic asymmetric fabric with outstanding one-way liquid sweat transport property. Benefiting from the low resistance of sweat absorption, the all-hydrophilic fabric exhibited a dramatically increased directional sweat transport rate of 13.6 mm/s, which is 5.9 times that of the untreated fabric, and significantly enhanced sweat evaporation rate (1.56 times of the untreated fabric) and cooling performance. Furthermore, the conductive ppy-fabric, during the process of ultra-fast sweat transport, generated a potential of 150 mV over an area of 2×2 cm2 or scalable electrical energy output of 2.5 mW/m2 under continuous sweat transportation. The finding in this work not only provided new insight into the design and development of asymmetric fabric for ultrafast sweat transport but also proposed a novel method for the in-situ energy harvesting during the sweat transportation process, which has potential applications in self-powered smart wearables and functional clothing.
         
            
 
                 
                
                    
                    科研通智能强力驱动
Strongly Powered by AbleSci AI