Polylactide (PLA)/graphene nanocomposites were prepared by a facile and low‐cost method of solution‐blending of PLA with liquid‐phase exfoliated graphene using chloroform as a mutual solvent. Transmission electron microscopy (TEM) was used to observe the structure and morphology of the exfoliated graphene. The dispersion of graphene in PLA matrix was examined by scanning electron microscope, X‐ray diffraction, and TEM. FTIR spectrum and the relatively low ID/IG ratio in Raman spectroscopy indicate that the structure of graphene sheets (GSs) is intact and can act as good reinforcement fillers in PLA matrix. Thermogravimetric analysis and dynamic mechanical analysis reveal that the addition of GSs greatly improves the thermal stability of PLA/GSs nanocomposites. Moreover, tensile strength of PLA/GSs nanocomposites is much higher than that of PLA homopolymer, increasing from 36.64 (pure PLA) up to 51.14 MPa (PLA/GSs‐1.0). POLYM. COMPOS., 35:396–403, 2014. © 2013 Society of Plastics Engineers

No abstract

No abstract

current, and transferred charges were measured by an electrometer (Keithley 6514). A high-speed camera (Photron FASTCAM Mini AX) was applied to record the vibration state of the STS under the agitation of water current.

Single-pixel imaging (SPI) has recently been intensively studied as an alternative to the traditional focal plane array (FPA) technology. However, limited by the refresh rate of spatial light modulators (SLM) and inherent reconstruction mechanism, SPI is inappropriate for high-speed moving targets. To break through this limitation, we propose a novel SPI scheme for high-speed moving targets. In our scenario, the spatial encoding for the target is done by the movement of the target relative to a static pseudo-random illumination pattern. In this process, a series of single-pixel signals are generated that corresponds to the overlap between the target and certain parts of the illumination structure. This correspondence can be utilized for image reconstruction in the same way as normal SPI. In addition, compressive sensing and deep learning algorithms are used for reconstruction, respectively. Reasonable reconstructions can be obtained with a sampling ratio of only 6%. Experimental verification together with theoretical analysis has shown that our scheme is able to image high-speed moving targets that could be alternatively achieved by a fast FPA camera. Our scheme keeps the inherent advantages of SPI and meanwhile extend its application to moving targets. It is believed that this technology will have wide application in many situations.