Advanced Photonics Research最新文献

Topological Photonic Insulators

In article number 2400023, Vien Van and Hanfa Song present the design and realization of (2 + 1)D topological photonic insulators hosting all flat bands, which exhibit novel properties such as anomalous Floquet insulator phase, ultra-wide edge mode continuum, super robustness to disorder, and photon caging in compact localized bulk states. These lattices have broadband applications in topologically-protected quantum photonics and programmable photonic circuits.

The hole accelerator is proven to benefit the hole injection for traditional light-emitting diodes (LEDs) because the induced electric field provides the holes with more kinetic energy to pass through the electron-blocking layer, enhancing the hole injection efficiency. Herein, the effect of the hole accelerator (HA) layer on the micro-LEDs by modeling the characteristics of the devices with a current density of lower than 10 A cm⁻² is investigated. The simulation results show that the appended HA layer brings a knot of the electric field in the HA layer, leading to higher internal quantum efficiency (IQE) than the device without HA under the low current density. The thickness and composition of HA, the quantum number, and the material of quantum barrier are also simulated and analyzed. The simulated radiative, Shockley–Read–Hall, and Auger recombination rates show that the IQE of the micro-LED with the HA layer is higher than that without the HA layer under the current density of lower than 10 A cm⁻².

Photoinduced Structural Modification

In article number 2300326, Ashim Dhakal and co-workers show that photo-induced metastable modification of electronic structure in graphite allows for multiphoton processes that can up-convert an O-band infrared excitation to visible-NIR band in graphite powder. Theoretically, this process can upconvert an infrared light near the wavelength of 3 μm to VIS-NIR wavelengths. It opens exciting new avenues for applications in visible light generation and low-noise imaging using infrared light excitation.

Microfluidic lab-on-a-chip (LOC) devices have become essential tools for multitudes of applications in various research fields. 3D printing of microfluidic LOC devices offers many advantages over more traditional manufacturing processes, including rapid prototyping and single-step fabrication of complex 3D structures. In this work, 3D-printed microfluidic devices are designed and fabricated for optical chromatography and sorting. Optical chromatography is performed by inserting a single-mode optical fiber into the device creating a counter-propagating laser beam to the fluid flow. Particles are separated depending on refractive index and size. To demonstrate optical sorting, a cross-type sorter 3D-printed microfluidic device is fabricated that directs the laser beam perpendicular to the flow direction. Design features such as a sloping channel and a channel configuration for 3D hydrodynamic focusing (to aid in controlled sample flow and particle position) help to optimize sorting performance. Stable optofluidic trapping and sorting are successfully achieved using the fabricated microfluidic devices. These results highlight the tremendous potential of 3D printing of microfluidic LOC devices for applications aimed at the optofluidic manipulation of micron-sized particles.

Global concern about microplastic (MP) and nanoplastic (NP) particles is continuously rising with their proliferation worldwide. Effective identification methods for MP and NP pollution monitoring are highly needed, but due to different requirements and technical challenges, much of the work is still in progress. Herein, the advanced optical imaging systems that are successfully applied or have the potential for MP identification are focused on. Compared with chemical and thermal analyses, optical methods have the unique advantages of being nondestructive and noncontact and allow fast detection without complex sample preprocessing. Furthermore, they are capable of revealing the morphology, anisotropy, and material characteristics of MP for their quick and robust detection. This review aims to present a comprehensive discussion of the relevant optical imaging systems, emphasizing their operating principles, strengths, and drawbacks. Multiple comparisons and analyses among these technologies are conducted in order to provide practical guidelines for researchers. In addition, the combination of optical and other alternative technologies is described and the representative portable MP detection devices are highlighted. Together, they shed light on the prospects for long-term MP pollution monitoring and environmental protection.

Combining cellulose-based components with functional materials is highly interesting in various research fields due to the improved strength and stiffness of the materials combined with their low weight. Herein, the mechanical properties of opal films are improved by incorporating cellulose fibers and microcrystalline cellulose. This is evidenced by the increase in tensile strength of 162.8% after adding 10 wt% of microcrystalline cellulose. For this purpose, core–shell particles with a rigid, crosslinked polystyrene core and a soft shell of poly(ethyl acrylate) and poly(ethyl acrylate-co-hydroxyethyl methacrylate) are synthesized via starved-feed emulsion polymerization. The synthesized particles’ well-defined shape, morphology, and thermal properties are analyzed using transmission electron microscopy, scanning electron microscopy, and differential scanning calorimetry measurements. Free-standing mechanochromic opal films with incorporated cellulose and structural colors are obtained after processing the core–shell particles with cellulose via extrusion and the melt-shear organization technique. The homogeneous distribution of the cellulose within the composite material is investigated using fluorescent-labeled cellulose. The opal film's angle-dependent structural color is demonstrated using reflection spectroscopy.

This review explores how artificial intelligence (AI) is transforming fluorescence microscopy, providing an overview of its fundamental principles and recent advancements. The roles of AI in improving image quality and introducing new imaging modalities are discussed, offering a comprehensive perspective on these changes. Additionally, a unified framework is introduced for comprehending AI-driven microscopy methodologies and categorizing them into linear inverse problem-solving, denoising, and nonlinear prediction. Furthermore, the potential of self-supervised learning techniques that address the challenges associated with training the networks are explored, utilizing unlabeled microscopy data to enhance data quality and expand imaging capabilities. It is worth noting that while the specific examples and advancements discussed in this review focus on fluorescence microscopy, the general approaches and theories are directly applicable to other optical microscopy methods.

Accurate and precise measurement of radiation energy delivered to and absorbed by the patient's tissue is of great importance in radiation therapy (RT) quality assurance. Radioluminescence (RL) dosimetry has shown great potential for high spatiotemporal resolution dose measurement of RT fields. Implementation of efficient RL dosimetry in RT requires multidisciplinary effort and skills in optics, medical physics, radiation physics, electronics, and imaging science. In this review, a wide overview of fundamentals and applications of RL properties of media for RT dosimetry with emphasis on their potential use for multidimensional, small-field, and ultra-high dose rate RT dosimetry is provided.