Despite the significant advancements in perovskite light-emitting diodes (PeLEDs), achieving high-performance blue LEDs remains a key concern for future display and optical communication applications, particularly pure-blue PeLEDs with high external quantum efficiency (EQE) and luminance. Recently, Hou and colleagues reported the utilization of an efficient additive that enables stable emission color with an enhanced EQE of 9.25% and a maximum luminance of 1806 cd cm-2, representing one of the best-performing pure-blue PeLEDs.

With the rapid development of sensor networks, machine vision faces the problem of storing and computing massive data. The human visual system has a very efficient information sense and computation ability, which has enlightening significance for solving the above problems in machine vision. This review aims to comprehensively summarize the latest advances in bio-inspired image sensors that can be used to improve machine-vision processing efficiency. After briefly introducing the research background, the relevant mechanisms of visual information processing in human visual systems are briefly discussed, including layer-by-layer processing, sparse coding, and neural adaptation. Subsequently, the cases and performance of image sensors corresponding to various bio-inspired mechanisms are introduced. Finally, the challenges and perspectives of implementing bio-inspired image sensors for efficient machine vision are discussed.

Three-dimensional (3D) imaging is essential for understanding intricate biological and biomedical systems, yet live cell and tissue imaging applications still face challenges due to constrained imaging speed and strong scattering in turbid media. Here, we present a unique phase-modulated stimulated Raman scattering tomography (PM-SRST) technique to achieve rapid label-free 3D chemical imaging in cells and tissue. To accomplish PM-SRST, we utilize a spatial light modulator to electronically manipulate the focused Stokes beam along the needle Bessel pump beam for SRS tomography without the need for mechanical z scanning. We demonstrate the rapid 3D imaging capability of PM-SRST by real-time monitoring of 3D Brownian motion of polystyrene beads in water with 8.5 Hz volume rate, as well as the instant biochemical responses to acetic acid stimulants in MCF-7 cells. Further, combining the Bessel pump beam with a longer wavelength Stokes beam (NIR-II window) provides a superior scattering resilient ability in PM-SRST, enabling rapid tomography in deeper tissue areas. The PM-SRST technique provides ∼twofold enhancement in imaging depth in highly scattering media (e.g., polymer beads phantom and biotissue like porcine skin and brain tissue) compared with conventional point-scan SRS. We also demonstrate the rapid 3D imaging ability of PM-SRST by observing the dynamic diffusion and uptake processes of deuterium oxide molecules into plant roots. The rapid PM-SRST developed can be used to facilitate label-free 3D chemical imaging of metabolic activities and functional dynamic processes of drug delivery and therapeutics in live cells and tissue.

Despite the rapid advances of red and green perovskite light-emitting diodes (PeLEDs), achieving high brightness with high external quantum efficiency (EQE) remains a challenge for the pure-blue PeLEDs, which greatly hinders their practical applications, such as white-light illumination and in optical communication as a high-speed and low-loss light source. Herein, we report a high-performance pure-blue PeLED based on mixed-halide quasi-2D perovskites incorporated with a zwitterionic molecule of 3-(benzyldimethylammonio) propanesulfonate (3-BAS). Experimental and density functional theory analysis reveals that 3-BAS can simultaneously eliminate non-radiative recombination loss, suppress halide migration, and regulate phase distribution for smoothing energy transfer in the mixed-halide quasi-2D perovskites, leading to the final perovskites with high photoluminescence quantum yield and robust spectrum stability. Thus, the high-performance pure-blue PeLED with a recorded brightness with 1806 cd m−2 and a relative higher EQE of 9.25% is achieved, which is successfully demonstrated in a visible light communication system for voice signal transmission. We pave the way for achieving highly efficient pure-blue PeLEDs with great application potential in future optical communication networks.

Structured light, where complex optical fields are tailored in all their degrees of freedom, has become highly topical of late, advanced by a sophisticated toolkit comprising both linear and nonlinear optics. Removing undesired structure from light is far less developed, leveraging mostly on inverting the distortion, e.g., with adaptive optics or the inverse transmission matrix of a complex channel, both requiring that the distortion be fully characterized through appropriate measurement. We show that distortions in spatially structured light can be corrected through difference-frequency generation in a nonlinear crystal without any need for the distortion to be known. We demonstrate the versatility of our approach using a wide range of aberrations and structured light modes, including higher-order orbital angular momentum (OAM) beams, showing excellent recovery of the original undistorted field. To highlight the efficacy of this process, we deploy the system in a prepare-and-measure communications link with OAM, showing minimal cross talk even when the transmission channel is highly aberrated, and outline how the approach could be extended to alternative experimental modalities and nonlinear processes. Our demonstration of light-correcting light without the need for measurement opens an approach to measurement-free error correction for classical and quantum structured light, with direct applications in imaging, sensing, and communication.

We report tensorial tomographic Fourier ptychography (T2oFu), a nonscanning label-free tomographic microscopy method for simultaneous imaging of quantitative phase and anisotropic specimen information in 3D. Built upon Fourier ptychography, a quantitative phase imaging technique, T2oFu additionally highlights the vectorial nature of light. The imaging setup consists of a standard microscope equipped with an LED matrix, a polarization generator, and a polarization-sensitive camera. Permittivity tensors of anisotropic samples are computationally recovered from polarized intensity measurements across three dimensions. We demonstrate T2oFu’s efficiency through volumetric reconstructions of refractive index, birefringence, and orientation for various validation samples, as well as tissue samples from muscle fibers and diseased heart tissue. Our reconstructions of healthy muscle fibers reveal their 3D fine-filament structures with consistent orientations. Additionally, we demonstrate reconstructions of a heart tissue sample that carries important polarization information for detecting cardiac amyloidosis.

Synthetic dimensions (SDs) opened the door for exploring previously inaccessible phenomena in high-dimensional space. However, construction of synthetic lattices with desired coupling properties is a challenging and unintuitive task. Here, we use deep learning artificial neural networks (ANNs) to construct lattices in real space with a predesigned spectrum of mode eigenvalues, and thus to validly design the dynamics in synthetic mode dimensions. By employing judiciously chosen perturbations (wiggling of waveguides at desired frequencies), we show resonant mode coupling and tailored dynamics in SDs. Two distinct examples are illustrated: one features uniform synthetic mode coupling, and the other showcases the edge defects that allow for tailored light transport and confinement. Furthermore, we demonstrate morphing of light into a topologically protected edge mode with modified Su–Schrieffer–Heeger photonic lattices. Such an ANN-assisted construction of SDs may advance toward “utopian networks,” opening new avenues for fundamental research beyond geometric limitations as well as for applications in mode lasing, optical switching, and communication technologies.

Optical networks are evolving toward ultrawide bandwidth and autonomous operation. In this scenario, it is crucial to accurately model and control optical power evolutions (OPEs) through optical amplifiers (OAs), as they directly affect the signal-to-noise ratio and fiber nonlinearities. However, a fundamental contradiction arises between the complex physical phenomena in optical transmission and the required precision in network control. Traditional theoretical methods underperform due to ideal assumptions, while data-driven approaches entail exorbitant costs associated with acquiring massive amounts of data to achieve the desired level of accuracy. In this work, we propose a Bayesian inference framework (BIF) to construct the digital twin of OAs and control OPE in a data-efficient manner. Only the informative data are collected to balance the exploration and exploitation of the data space, thus enabling efficient autonomous-driving optical networks (ADONs). Simulations and experiments demonstrate that the BIF can reduce the data size for modeling erbium-doped fiber amplifiers by 80% and Raman amplifiers by 60%. Within 30 iterations, the optimal controlling performance can be achieved to realize target signal/gain profiles in links with different types of OAs. The results show that the BIF paves the way to accurately model and control OPE for future ADONs.

Narrowband photodetection is an important measurement technique for material analysis and sensing, for example, nondispersive infrared sensing technique. Both photoactive material engineering and nanophotonic filtering schemes have been explored to realize wavelength-selective photodetection, while most devices have a responsive bandwidth larger than 2% of the operating wavelength, limiting sensing performance. Near-infrared photodetection with a bandwidth of less than 0.2% of the operating wavelength was demonstrated experimentally in Au/Si Schottky nanojunctions. A minimum linewidth of photoelectric response down to 2.6 nm was obtained at a wavelength of 1550 nm by carefully tailing the absorptive and radiative loss in the nanostructures. Multiple functions were achieved on chip with the corrugated Au film, including narrowband resonance, light harvesting for sensing and photodetection, and electrodes for hot electron emission. Benefiting from such a unity integration with in situ photoelectric conversion of the optical sensing signal and the ultranarrowband resonance, self-contained on-chip biosensing via simple intensity interrogation was demonstrated with a limit of detection down to 0.0047% in concentration for glucose solution and 150 ng/mL for rabbit IgG. Promising potential of this technique is expected for the applications in on-site sensing, spectroscopy, spectral imaging, etc.

The article provides information about the image on the cover of Advanced Photonics, Volume 6 Issue 2.