UV-Light-Induced Morphological Transformation of Spiropyran Assemblies from Irregular Sheet-like Structures to Nanospheres.

Studies on self-assembling systems with a controllable morphology responding to light stimulation are significant for revealing the process and mechanism of assembly. Here, a molecule of spiropyran derivative (SP) possessing photoresponsive assembly morphology is constructed. SP self-assembles into irregular sheet-like structures whose morphology can be significantly transformed into regular nanospheres under continuous ultraviolet light stimulation. The UV-vis absorption spectra indicate that 56% of SP are isomerized from closed-ring form (SPC) to open-ring form (SPO) with color changes from colorless to magenta. Furthermore, theoretical calculations demonstrate that SPO-SPO aggregates possess stronger van der Waals forces than do SPC-SPC aggregates and tend to form stable intermediates combined with SPO isomers. Therefore, the isomerization of SP from SPC to SPO and the differences in intermolecular interactions are important factors in the morphological transition. Our study provides an efficient strategy to modulate the assembled morphology, which holds great promise to be applied in the field of smart materials.

Non-line-of-sight imaging with arbitrary illumination and detection pattern.

Non-line-of-sight (NLOS) imaging aims at reconstructing targets obscured from the direct line of sight. Existing NLOS imaging algorithms require dense measurements at regular grid points in a large area of the relay surface, which severely hinders their availability to variable relay scenarios in practical applications such as robotic vision, autonomous driving, rescue operations and remote sensing. In this work, we propose a Bayesian framework for NLOS imaging without specific requirements on the spatial pattern of illumination and detection points. By introducing virtual confocal signals, we design a confocal complemented signal-object collaborative regularization (CC-SOCR) algorithm for high-quality reconstructions. Our approach is capable of reconstructing both the albedo and surface normal of the hidden objects with fine details under general relay settings. Moreover, with a regular relay surface, coarse rather than dense measurements are enough for our approach such that the acquisition time can be reduced significantly. As demonstrated in multiple experiments, the proposed framework substantially extends the application range of NLOS imaging.

Single-pixel imaging of a randomly moving object.

Single-pixel imaging enjoys advantages of low budget, broad spectrum, and high imaging speed. However, existing methods cannot clearly reconstruct the object that is fast rotating or randomly moving. In this work, we put forward an effective method to image a randomly moving object based on geometric moment analysis. To the best of our knowledge, this is the first work that reconstructs the shape and motion state of the target without prior knowledge of the speed or position. By using the cake-cutting order Hadamard illumination patterns and low-order geometric moment patterns, we obtain a high-quality video stream of the target which moves at high and varying translational and rotational speeds. The efficient method as verified by simulation and experimental results has great potential for practical applications such as Brownian motion microscopy and remote sensing.