Structural color technology has garnered extensive attention in the development of ink-free color technology for applications such as color displays, color reflectors, and colorimetric devices. A Fabry–Perot (F–P) structure formed by stacking a metal base, an interference cavity, and a phase change material layer (MIP) is of significant interest as a lithography-free and scalable color-reflecting structure. Such a structure can selectively reflect interfered light over a range of visible wavelengths, resulting in bright colors. However, obtaining a wide range of saturation regulation spaces has become a challenge. In this study, an F–P color reflector based on a phase-change material (PCM) base is proposed, which consists of a PCM base, an interference layer, and a PCM top layer (PIP). The results of the finite element simulation and experimental measurements demonstrated that the PIP reflector had an adjustable saturation range 10.75 times larger than that of the MIP reflector. The effects of the structure size and phase change of the PCM layer on the structural characteristics were further analyzed. In addition, the performance of laser-induced color change and its application in color printing were demonstrated. The present study sheds new light on color reflectors, and the strategy proposed indicates their potential optoelectronic applications based on saturation modulation.
Owing to acoustic-pressure dependence, amplitudes of backscattered-echoes of encapsulated microbubbles (MBs) are unavoidably regulated by an uneven acoustic field, resulting in the misestimation of hemodynamics in conventional amplitude-coding dynamic contrast-enhanced ultrasound (DCEUS) with focused pulse transmission. This study aimed to investigate the feasibility and performance of Nakagami statistical-feature parametric imaging to recover the above misestimation. Methods: Logarithmic Nakagami parameter (m)-coding DCEUS scheme was investigated via simulation and in vitro MB phantoms as well as in vivo kidneyperfusion experiments of four rabbits in the uneven acoustic fields with two different focal depths. In vivo tissue artifacts for m estimation were suppressed by pulse-inversion second-harmonic imaging and its robustness was enhanced by multiscale moment-estimation strategy. Time-Nakagami-m curves and the corresponding perfusion metrics of intensity and volume were calculated from the logarithmic m-coding DCEUS images within the prefocal and focal regions. These curves and metrics were further compared with the perfusion curves and metrics estimated from the conventional amplitude-coding images within the same regions. Results: Compared with amplitudes of nonlinear scattering MB echoes, their logarithmic m values were relatively independent of the changes in acoustics pressures. Compared with the fixed-scale moment-estimation, the perfusion intensity estimated from logarithmic m-coding DCEUS scheme using multiscale statistical moment-estimation had smaller differences between the prefocal and focal regions. The differences of perfusion intensity induced by an uneven acoustic field decreased to 3.47% ± 1.58 %. The differences decreased by the logarithmic m-coding DCEUS scheme were further regulated by threshold values of m estimation.
Conclusions:The logarithmic m-coding DCEUS scheme could recover the underestimated MB backscattered-echoes and the misestimated perfusion intensity induced by the uneven acoustic field. The scheme had the potential to weaken the limitation of microvasculature identification and hemodynamic characterization marked by MBs within tissues or tumors in the uneven acoustic field.
K E Y W O R D Scontrast-enhanced ultrasound, focused acoustic field, hemodynamic, Nakagami parameter 2452
Inspired by the human brain, neural network computing was expected to break the bottleneck of traditional computing, but the integrated design still faces great challenges. Here, a readily integrated membrane-system photonic synapse was demonstrated. By pre-pulse training at 1064 nm (cutoff wavelength), the photonic synapse can be regulated both excitatory and inhibitory at tunable wavelengths (1200–2000 nm). Furthermore, more weights and memory functions were shown through the photonic synapse integrated network. Additionally, the digital recognition function of the single-layer perceptron neural network constructed by photonic synapses has been successfully demonstrated. Most of the biological synaptic functions were realized by the photonic synaptic network, and it had the advantages of compact structure, scalable, adjustable wavelength, and so on, which opens up a new idea for the study of the neural synaptic network.
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