The self-assemblies of polycyclic aromatic diimide (PAI) compounds on solid surfaces have attracted great interest because of the versatile and attractive properties for application in organic electronics. Here, a planar guest species (coronene) selectively adsorbs on the helicene-typed PAI1 monolayer strongly, depending on the conjugated cores of these PAIs. PAI1 molecule displays evidently a bowl structure lying on the highly oriented pyrolytic graphite surface due to the torsion of the "C"-shaped fused benzene rings. In combination with density functional theory calculation, the selective inclusion of coronene atop the backbone of the PAI1 array might be attributed to the bowl structure, which provides a groove for immobilizing coronene molecules. On the other planar densely packed arrays, it is difficult to observe the unstable adsorption of coronene. The selective addition of coronene molecules would be a strategic step toward the controllable multicomponent supramolecular architectures.
High-sensitivity plasmonic refractive index sensors show great applications in the areas of the biomedical diagnostics, healthcare, food safety, environmental monitoring, homeland security, and chemical reaction. However, the unstable and complicated environments considerably limit their practical applications. By employing the independent double Fano resonances in a simple metallic grating, we experimentally demonstrated a self-reference plasmonic sensor, which significantly reduces the error contributions of the light intensity fluctuations in the long-distance propagation and local temperature variations at the metallic grating, and the detection accuracy is guaranteed. The numerical simulation shows that the two Fano resonances have different originations and are independent with each other. As a result, the left Fano resonance is quite sensitive to the refractive index variations above the metal surface, while the right Fano resonance is insensitive to that. Experimentally, a high figure of merit (FOM) of 31 RIU-1 and FOM* of 860 RIU-1 are realized by using the left Fano resonance. More importantly, by using the right Fano resonance as a reference signal, the influence of the light intensity fluctuations and local temperature variations are monitored and eliminated in the experiment. This simple self-reference plasmonic sensor based on the double Fano resonances may find important applications in high-sensitive and accurate sensing under the unstable and complicated environments, as well as multi-parameter sensing.
Learning the spatial-temporal representation of motion information is crucial to human action recognition. Nevertheless, most of the existing features or descriptors cannot capture motion information effectively, especially for long-term motion. To address this problem, this paper proposes a long-term motion descriptor called sequential Deep Trajectory Descriptor (sDTD). Specifically, we project dense trajectories into two-dimensional planes, and subsequently a CNN-RNN network is employed to learn an effective representation for long-term motion. Unlike the popular two-stream ConvNets, the sDTD stream is introduced into a three-stream framework so as to identify actions from a video sequence. Consequently, this three-stream framework can simultaneously capture static spatial features, short-term motion and long-term motion in that video. Extensive experiments were conducted on three challenging datasets: KTH, HMDB51 and UCF101. Experimental results show that our method achieves state-of-the-art performance on the KTH and UCF101 datasets, and is comparable to the state-of-the-art methods on the HMDB51 dataset.
The critical behaviors of a granular system at the jamming transition have been extensively studied from both mechanical and thermodynamic perspectives. In this work, we numerically investigate the jamming behaviors of a variety of frictionless non-spherical particles, including spherocylinder, ellipsoid, spherotetrahedron and spherocube. In particular, for a given particle shape, a series of random configurations at different fixed densities are generated and relaxed to minimize interparticle overlaps using the relaxation algorithm. We find that as the jamming point (i.e., point J">J) is approached, the number of iteration steps (defined as the “time-scale” for our systems) required to completely relax the interparticle overlaps exhibits a clear power-law divergence. The dependence of the detailed mathematical form of the power-law divergence on particle shapes is systematically investigated and elucidated, which suggests that the shape effects can be generally categorized as elongation and roundness. Importantly, we show the jamming transition density can be accurately determined from the analysis of time-scale divergence for different non-spherical shapes, and the obtained values agree very well with corresponding ones reported in literature. Moreover, we study the plastic behaviors of over-jammed packings of different particles under a compression–expansion procedure and find that the jamming of ellipsoid is much more robust than other non-spherical particles. This work offers an alternative approximate procedure besides conventional packing algorithms for studying athermal jamming transition in granular system of frictionless non-spherical particles.
The side-chain structures of conjugated molecules are well recognized to sensitively influence the crystallinity, morphology and thus carrier transport properties of organic semiconductors. Here, by varying the alkyl side-chain length in the polymer acceptors, the effect of side-chain engineering on the photovoltaic performance is systematically studied in all-polymer solar cells. Clear trends of first an increase and then a decrease in the J(sc) and FF values are observed as the branched alkyl groups are extended from 4 to 8 carbons. Correspondingly, the maximum average PCE (ca. 7.40%) is attained with an acceptor bearing a branched side-chain length of seven carbon atoms.
