Senses Erkan, Narayanan Suresh, Mao Yimin, Faraone Antonio
NIST Center for Neutron Research, National Institute of Standards and Technology Gaithersburg, Maryland 20899-8562 USA.
Department of Materials Science and Engineering, University of Maryland College Park, Maryland 20742-2115 USA.
Phys Rev Lett. 2017 Dec 8;119(23):237801. doi: 10.1103/PhysRevLett.119.237801. Epub 2017 Dec 6.
Using x-ray photon correlation spectroscopy, we examined the slow nanoscale motion of silica nanoparticles individually dispersed in an entangled poly (ethylene oxide) melt at particle volume fractions up to 42%. The nanoparticles, therefore, serve as both fillers for the resulting attractive polymer nanocomposites and probes for the network dynamics therein. The results show that the particle relaxation closely follows the mechanical reinforcement in the nanocomposites only at the intermediate concentrations below the critical value for the chain confinement. Quite unexpectedly, the relaxation time of the particles does not further slow down at higher volume fractions-when all chains are practically on the nanoparticle interface-and decouples from the elastic modulus of the nanocomposites that further increases orders of magnitude.
利用X射线光子相关光谱，我们研究了在高达42%的颗粒体积分数下，单独分散在缠结的聚环氧乙烷熔体中的二氧化硅纳米颗粒的缓慢纳米级运动。因此，纳米颗粒既作为所得有吸引力的聚合物纳米复合材料的填料，又作为其中网络动力学的探针。结果表明，仅在低于链受限临界值的中间浓度下，颗粒弛豫才紧密跟随纳米复合材料中的机械增强。非常出乎意料的是，在更高的体积分数下——当所有链实际上都在纳米颗粒界面上时——颗粒的弛豫时间不会进一步减慢，并且与进一步增加几个数量级的纳米复合材料的弹性模量解耦。
