Visible light communication (VLC) is an emerging technology employing light-emitting diodes (LEDs) to provide illumination and wireless data transmission simultaneously. Harnessing cost-efficient printable organic LEDs (OLEDs) as environmentally friendly transmitters in VLC systems is extremely attractive for future applications in spectroscopy, the internet of things, sensing, and optical ranging in general. Here, we summarize the latest research progress on emerging semiconductor materials for LED sources in VLC, and highlight that OLEDs based on nontoxic and cost-efficient organic semiconductors have great opportunities for optical communication. We further examine efforts to achieve high-performance white OLEDs for general lighting, and, in particular, focus on the research status and opportunities for OLED-based VLC. Different solution-processable fabrication and printing strategies to develop high-performance OLEDs are also discussed. Finally, an outlook on future challenges and potential prospects of the next-generation organic VLC is provided.

We review the recent biomedical detection developments of scanning near-field optical microscopy (SNOM), focusing on scattering-type SNOM, atomic force microscope-based infrared spectroscopy, peak force infrared microscopy, and photo-induced force microscopy, which have the advantages of label-free, noninvasive, and specific spectral recognition. Considering the high water content of biological samples and the strong absorption of water by infrared waves, we divide the relevant research on these techniques into two categories: one based on a nonliquid environment and the other based on a liquid environment. In the nonliquid environment, the chemical composition and structural information of biomedical samples can be obtained with nanometer resolution. In the liquid environment, these techniques can be used to monitor the dynamic chemical reaction process and track the process of chemical composition and structural change of single molecules, which is conducive to exploring the development mechanism of physiological processes. We elaborate their experimental challenges, technical means, and actual cases for three microbiomedical samples (including biomacromolecules, cells, and tissues). We also discuss the prospects and challenges for their development. Our work lays a foundation for the rational design and efficient use of near-field optical microscopy to explore the characteristics of microscopic biology.

Accurate localization of blood vessels with image navigation is a key element in vascular-related medical research and vascular surgery. However, current vascular navigation techniques cannot provide naked-eye visualization of deep vascular information noninvasively and with high resolution, resulting in inaccurate vascular anatomy and diminished surgical success rates. Here, we introduce a photoacoustic-enabled automatic vascular navigation method combining photoacoustic computed tomography with augmented and mixed reality, for the first time, to our knowledge, enabling accurate and noninvasive visualization of the deep microvascular network within the tissues in real time on a real surgical surface. This approach achieves precise vascular localization accuracy (<0.89 mm) and tiny vascular relocation latency (<1 s) through a zero-mean normalization idea-based visual tracking algorithm and a curved surface-fitting algorithm. Further, the subcutaneous vessels of minimum diameter (∼0.15 mm) in rabbit thigh and the maximum depth (∼7 mm) in human arm can be vividly projected on the skin surface with a computer vision-based projection tracking system to simulate preoperative and intraoperative vascular localization. Thereby, this strategy provides a way to visualize deep vessels without damage on the surgical surface and with precise image navigation, opening an avenue for the application of photoacoustic imaging in surgical operations.

We present a scheme for estimating the noise-equivalent temperature difference (NETD) of frequency upconversion detectors (UCDs) that detect mid-infrared (MIR) light. In particular, we investigate the frequency upconversion of a periodically poled crystal based on lithium niobate, where an MIR conversion bandwidth of 220 nm can be achieved in a single-poled period by a special design. Experimentally, for an MIR radiating target at a temperature of 95°C, the NETD of the device was estimated to be 56 mK with an exposure time of 1 s. Meanwhile, a direct measurement of the NETD was performed utilizing conventional methods, which resulted in 48 mK. We also compared the NETD of our UCD with commercially available direct MIR detectors. We show that the limiting factor for further NETD reduction of our device is not primarily from the upconversion process and camera noise but from the limitations of the heat source and laser performance. Our detectors have good temperature measurement performance and can be used for a variety of applications involving temperature object identification and material structure detection.

Suitable optoelectronic integration platforms enable the realization of numerous application systems at the chip scale and are highly anticipated in the rapidly growing market. We report a GaN-on-silicon-based photonic integration platform and demonstrate a photonic integrated chip comprising a light source, modulator, photodiode (PD), waveguide, and Y-branch splitter based on this platform. The light source, modulator, and PD adopt the same multiple quantum wells (MQWs) diode structure without encountering incompatibility problems faced in other photonic integration approaches. The waveguide-structure MQW electro-absorption modulator has obvious indirect light modulation capability, and its absorption coefficient changes with the applied bias voltage. The results successfully validate the data transmission and processing using near-ultraviolet light with peak emission wavelength of 386 nm. The proposed complete active–passive approach that has simple fabrication and low cost provides new prospects for next-generation photonic integration.

The carrier-free phase-retrieval (CF-PR) receiver can reconstruct the optical field information only from two de-correlated intensity measurements without the involvement of a continuous-wave optical carrier. Here, we propose a digital subcarrier multiplexing (DSM)-enabled CF-PR receiver with hardware-efficient and modulation format-transparent merits. By numerically retrieving the optical field information of 56 GBaud DSM signals with QPSK/16QAM/32QAM modulation after 80-km standard single-mode fiber (SSMF) transmission, we identify that the DSM enabled CF-PR receiver is beneficial in reducing the implementation complexity of the CF-PR process, in comparison with the traditional single-carrier counterpart, because the lower symbol rate of each subcarrier is helpful in reducing the implementation complexity of multiple chromatic dispersion compensations and emulations during the PR iteration. Moreover, the DSM-enabled CF-PR receiver is verified to be robust toward various transmission imperfections, including transmitter-side laser linewidth and its wavelength drift, receiver-side time skew, and amplitude imbalance between two intensity tributaries. Finally, the superiority of the DSM-enabled CF-PR receiver is experimentally verified by recovering the optical field information of 25 GBaud 16QAM signals, after 40-km SSMF transmission for the first time. Thus, the DSM-enabled CF-PR receiver is promising for high-capacity photonic interconnection with direct detection.

Structured illumination microscopy (SIM) has been widely applied in the superresolution imaging of subcellular dynamics in live cells. Higher spatial resolution is expected for the observation of finer structures. However, further increasing spatial resolution in SIM under the condition of strong background and noise levels remains challenging. Here, we report a method to achieve deep resolution enhancement of SIM by combining an untrained neural network with an alternating direction method of multipliers (ADMM) framework, i.e., ADMM-DRE-SIM. By exploiting the implicit image priors in the neural network and the Hessian prior in the ADMM framework associated with the optical transfer model of SIM, ADMM-DRE-SIM can further realize the spatial frequency extension without the requirement of training datasets. Moreover, an image degradation model containing the convolution with equivalent point spread function of SIM and additional background map is utilized to suppress the strong background while keeping the structure fidelity. Experimental results by imaging tubulins and actins show that ADMM-DRE-SIM can obtain the resolution enhancement by a factor of ∼1.6 compared to conventional SIM, evidencing the promising applications of ADMM-DRE-SIM in superresolution biomedical imaging.

Large-scale computational imaging can provide remarkable space-bandwidth product that is beyond the limit of optical systems. In coherent imaging (CI), the joint reconstruction of amplitude and phase further expands the information throughput and sheds light on label-free observation of biological samples at micro- or even nano-levels. The existing large-scale CI techniques usually require scanning/modulation multiple times to guarantee measurement diversity and long exposure time to achieve a high signal-to-noise ratio. Such cumbersome procedures restrict clinical applications for rapid and low-phototoxicity cell imaging. In this work, a complex-domain-enhancing neural network for large-scale CI termed CI-CDNet is proposed for various large-scale CI modalities with satisfactory reconstruction quality and efficiency. CI-CDNet is able to exploit the latent coupling information between amplitude and phase (such as their same features), realizing multidimensional representations of the complex wavefront. The cross-field characterization framework empowers strong generalization and robustness for various coherent modalities, allowing high-quality and efficient imaging under extremely low exposure time and few data volume. We apply CI-CDNet in various large-scale CI modalities including Kramers–Kronig-relations holography, Fourier ptychographic microscopy, and lensless coded ptychography. A series of simulations and experiments validate that CI-CDNet can reduce exposure time and data volume by more than 1 order of magnitude. We further demonstrate that the high-quality reconstruction of CI-CDNet benefits the subsequent high-level semantic analysis.

Silicon nitride (Si3N4) waveguides with high confinement and low loss have been widely used in integrated nonlinear photonics. Indeed, state-of-the-art ultralow-loss Si3N4 waveguides are all fabricated using complex fabrication processes, and all of those reported that high Q microring resonators (MRRs) are fabricated in laboratories. We propose and demonstrate an ultralow-loss Si3N4 racetrack MRR by shaping the mode using a uniform multimode structure to reduce its overlap with the waveguide. The MRR is fabricated by the standard multi project wafer (MPW) foundry process. It consists of two multimode straight waveguides (MSWs) connected by two multimode waveguide bends (MWBs). In particular, the MWBs are based on modified Euler bends, and an MSW directional coupler is used to avoid higher-order mode excitation. In this way, although a multimode waveguide is used in the MRR, only the fundamental mode is excited and transmitted with ultralow loss. Meanwhile, thanks to the 180 deg Euler bend, a compact chip footprint of 2.226 mm perimeter with an effective radius as small as 195 μm and a waveguide width of 3 μm is achieved. Results show that based on the widely used MPW process, a propagation loss of only 3.3 dB / m and a mean intrinsic Q of around 10.8 million are achieved for the first time.

Orbital angular momentum (OAM), emerging as an inherently high-dimensional property of photons, has boosted information capacity in optical communications. However, the potential of OAM in optical computing remains almost unexplored. Here, we present a highly efficient optical computing protocol for complex vector convolution with the superposition of high-dimensional OAM eigenmodes. We used two cascaded spatial light modulators to prepare suitable OAM superpositions to encode two complex vectors. Then, a deep-learning strategy is devised to decode the complex OAM spectrum, thus accomplishing the optical convolution task. In our experiment, we succeed in demonstrating 7-, 9-, and 11-dimensional complex vector convolutions, in which an average proximity better than 95% and a mean relative error <6 % are achieved. Our present scheme can be extended to incorporate other degrees of freedom for a more versatile optical computing in the high-dimensional Hilbert space.

Optical skyrmion serves as a crucial interface between optics and topology. Recently, it has attracted great interest in linear optics. Here, we theoretically introduce a framework for the all-optical generation and control of free-space optical skyrmions in extreme ultraviolet regions via high harmonic generation (HHG). We show that by employing full Poincaré beams, the created extreme ultraviolet fields manifest as skyrmionic structures in Stokes vector fields, whose skyrmion number is relevant to harmonic orders. We reveal that the generation of the skyrmionics structure is attributed to spatial-resolved spin constraint of HHG. Through qualifying the geometrical parameters of full Poincaré beams, the topological texture of extreme ultraviolet fields can be completely manipulated, generating the Bloch-type, Néel-type, anti-type, and higher-order skyrmions. We promote the investigation of topological optics in optical highly nonlinear processes, with potential applications toward ultrafast spintronics with structured light fields.