Design of a High -Factor Label-Free Optical Biosensor Based on a Photonic Crystal Coupled Cavity Waveguide.

In recent years, there has been a significant increase in research into silicon-based on-chip sensing. In this paper, a coupled cavity waveguide (CCW) based on a slab photonic crystal structure was designed for use as a label-free biosensor. The photonic crystal consisted of holes arranged in a triangular lattice.

Design of a Narrow Band Filter Based on a Photonic Crystal Cavity for CO Sensing Application.

This paper investigates the use of a miniaturized filter based on a triangular lattice of holes in a photonic crystal (PhC) slab. The plane wave expansion method (PWE) and finite-difference time-domain (FDTD) techniques were utilized to analyze the dispersion and transmission spectrum, as well as the quality factor and free spectral range (FSR) of the filter. A 3D simulation has demonstrated that for the designed filter, an FSR of more than 550 nm and a quality factor of 873 can be attained by adiabatically coupling light from a slab waveguide into a PhC waveguide.

Generation and Observation of Long-Lasting and Self-Sustaining Marangoni Flow.

When solute molecules in a liquid evaporate at the surface, concentration gradients can lead to surface tension gradients and provoke fluid convection at the interface, a phenomenon commonly known as the Marangoni effect. Here, we demonstrate that minute quantities of ethanol in concentrated sodium hydroxide solution can induce pronounced and long-lasting Marangoni flow upon evaporation at room temperature. By employing particle image velocimetry and gravimetric analysis, we show that the mean interfacial speed of the evaporating solution sensitively increases with the evaporation rate for ethanol concentrations lower than 0.

Nucleation of Porous Crystals from Ion-Paired Prenucleation Clusters.

Current nucleation models propose manifold options for the formation of crystalline materials. Exploring and distinguishing between different crystallization pathways on the molecular level however remain a challenge, especially for complex porous materials. These usually consist of large unit cells with an ordered framework and pore components and often nucleate in complex, multiphasic synthesis media, restricting in-depth characterization.

A deep learning-based whole-body solution for PET/MRI attenuation correction.

Background: Deep convolutional neural networks have demonstrated robust and reliable PET attenuation correction (AC) as an alternative to conventional AC methods in integrated PET/MRI systems. However, its whole-body implementation is still challenging due to anatomical variations and the limited MRI field of view. The aim of this study is to investigate a deep learning (DL) method to generate voxel-based synthetic CT (sCT) from Dixon MRI and use it as a whole-body solution for PET AC in a PET/MRI system.