Visualizing rapid biological dynamics like neuronal signaling and microvascular flow is crucial yet challenging due to photon noise and motion artifacts. Here we present a deep learning framework for enhancing the spatiotemporal relations of optical microscopy data. Our approach leverages correlations of mirrored perspectives from conjugated scan paths, training a model to suppress noise and motion blur by restoring degraded spatial features. Quantitative validation on vibrational calcium imaging validates significant gains in spatiotemporal correlation (2.2×), signal-to-noise ratio (9–12 dB), structural similarity (6.6×), and motion tolerance compared to raw data. We further apply the framework to diverse in vivo experiments from mouse cerebral hemodynamics to zebrafish cardiac dynamics. This approach enables the clear visualization of the rapid nutrient flow (30 mm/s) in microcirculation and the systolic and diastolic processes of heartbeat (2.7 cycle/s), as well as cellular and vascular structure in deep cortex. Unlike techniques relying on temporal correlations, learning inherent spatial priors avoids motion-induced artifacts. This self-supervised strategy flexibly enhances live microscopy under photon-limited and motion-prone regimes.

Metamaterials and metasurfaces of artificial micro-/nano- structures functioning from microwave, terahertz, to infrared regime have enabled numerous applications from bioimaging, cancer detection and immunoassay to on-body health monitoring systems in the past few decades. Recently, the trend of turning metasurface devices flexible and stretchable has arisen in that the flexibility and stretchability not only makes the device more biocompatible and wearable, but also provides unique control and manipulation of the structural and geometrical reconfiguration of the metasurface in a creative manner, resulting in an extraordinary tunability for biomedical sensing and detection purposes. In this Review, we summarize recent advances in the design and fabrication techniques of stretchable reconfigurable metasurfaces and their applications to date thereof, and put forward a perspective for future development of stretchable reconfigurable metamaterials and metasurfaces.

There has been a long fundamental pursuit to enhance and levitate the Raman scattering signal intensity of molecule by a huge number of ~ 14–15 orders of magnitude, to the level comparable with the molecule fluorescence intensity and truly entering the regime of single-molecule Raman spectroscopy. In this work we report unambiguous observation of single-molecule Raman spectroscopy via synergic action of electromagnetic and chemical enhancement for rhodamine B (RhB) molecule absorbed within the plasmonic nanogap formed by gold nanoparticle sitting on the two-dimensional (2D) monolayer WS2 and 2 nm SiO2 coated gold thin film. Raman spectroscopy down to an extremely dilute value of 10–18 mol/L can still be clearly visible, and the statistical enhancement factor could reach 16 orders of magnitude compared with the reference detection sample of silicon plate. The electromagnetic enhancement comes from local surface plasmon resonance induced at the nanogap, which could reach ~ 10–11 orders of magnitude, while the chemical enhancement comes from monolayer WS2 2D material, which could reach 4–5 orders of magnitudes. This synergic route of Raman enhancement devices could open up a new frontier of single molecule science, allowing detection, identification, and monitor of single molecules and their spatial–temporal evolution under various internal and external stimuli.

Detection noise significantly degrades the quality of structured illumination microscopy (SIM) images, especially under low-light conditions. Although supervised learning based denoising methods have shown prominent advances in eliminating the noise-induced artifacts, the requirement of a large amount of high-quality training data severely limits their applications. Here we developed a pixel-realignment-based self-supervised denoising framework for SIM (PRS-SIM) that trains an SIM image denoiser with only noisy data and substantially removes the reconstruction artifacts. We demonstrated that PRS-SIM generates artifact-free images with 20-fold less fluorescence than ordinary imaging conditions while achieving comparable super-resolution capability to the ground truth (GT). Moreover, we developed an easy-to-use plugin that enables both training and implementation of PRS-SIM for multimodal SIM platforms including 2D/3D and linear/nonlinear SIM. With PRS-SIM, we achieved long-term super-resolution live-cell imaging of various vulnerable bioprocesses, revealing the clustered distribution of Clathrin-coated pits and detailed interaction dynamics of multiple organelles and the cytoskeleton.

The vacuum-ultraviolet (VUV, 10–200 nm) imaging photodetector (PD) based on the wide bandgap semiconductor (WBGS) can realize a more detailed observation of solar storms than the silicon ones. Here, an 8 × 8 VUV PD array based on the semiconductor AlN with an ultra-wide bandgap is presented, exhibiting the shortest cutoff wavelength (203 nm) reported so far. The PD array with a Pt/AlN/SiC/Ti/Au photovoltaic structure shows an excellent selective response to VUV light, an extremely low dark current density of 2.85 × 10–11 A·cm-2@ -2 V, a responsivity of 0.054 A·W-1@ 0 V and an ultra-short rise time of 13 ns. Also, the clear boundaries and an obvious contrast between light and dark of the VUV image displayed in the imaging measurement indicate the good imaging ability of this PD array, which can be used for the imaging application with high signal-to-noise ratio and high response speed. These results provide rich experience for the development of VUV imaging PDs based on WBGSs both in their fabrication and the practical applications in VUV detection.

Aqueous zinc-ion batteries provide a most promising alternative to the existing lithium-ion batteries due to their high theoretical capacity, intrinsic safety, and low cost. However, commercializing aqueous zinc-ion batteries suffer from dendritic growth and side reactions on the surface of metallic zinc, resulting in poor reversibility. To overcome this critical challenge, here, we report a one-step ultrafast laser processing method for fabricating three-dimensional micro-/nanostructures on zinc anodes to optimize zinc nucleation and deposition processes. It is demonstrated that the three-dimensional micro-/nanostructure with increased specific surface area significantly reduces nucleation overpotential, as well as preferentially absorbs zinc ions to prevent dendritic protuberances and corrosion. As a result, the presence of three-dimensional micro-/nanostructures on the zinc metal delivers stable zinc plating/stripping beyond 2500 h (2 mA cm-2/1 mAh cm-2) in symmetric cells, a high Coulombic efficiency (99.71%) in half cells, and moreover an improved capacity retention (71.8%) is also observed in full cells. Equally intriguingly, the pouch cell with three-dimensional micro-/nanostructures can operate across various bending states without severely compromising performance. This work provides an effective strategy to construct ultrafine and high-precision three-dimensional micro-/nanostructures achieving high-performance zinc metal anodes and is expected to be of immediate benefit to other metal-based electrodes.

Optical imaging techniques provide low-cost, non-radiative images with high spatiotemporal resolution, making them advantageous for long-term dynamic observation of blood perfusion in stroke research and other brain studies compared to non-optical methods. However, high-resolution imaging in optical microscopy fundamentally requires a tight optical focus, and thus a limited depth of field (DOF). Consequently, large-scale, non-stitched, high-resolution images of curved surfaces, like brains, are difficult to acquire without z-axis scanning. To overcome this limitation, we developed a needle-shaped beam optical coherence tomography angiography (NB-OCTA) system, and for the first time, achieved a volumetric resolution of less than 8 μm in a non-stitched volume space of 6.4 mm × 4 mm × 620 μm in vivo. This system captures the distribution of blood vessels at 3.4-times larger depths than normal OCTA equipped with a Gaussian beam (GB-OCTA). We then employed NB-OCTA to perform long-term observation of cortical blood perfusion after stroke in vivo, and quantitatively analyzed the vessel area density (VAD) and the diameters of representative vessels in different regions over 10 days, revealing different spatiotemporal dynamics in the acute, sub-acute and chronic phase of post-ischemic revascularization. Benefiting from our NB-OCTA, we revealed that the recovery process is not only the result of spontaneous reperfusion, but also the formation of new vessels. This study provides visual and mechanistic insights into strokes and helps to deepen our understanding of the spontaneous response of brain after stroke.

Optical encryption strategies utilizing fully coherent light have been widely explored but often face challenges such as speckle noise and beam instabilities. In this work, we introduce a novel protocol for multi-channel optical information encoding and encryption using vectorial spatial coherence engineering of a partially coherent light beam. By characterizing the beam’s spatial coherence structure with a $$2 \times 2$$ coherence matrix, we demonstrate independent control over the three components of the coherence Stokes vector. This allows for three-channel optical information encoding and encryption, with applications in color image representation. Unlike existing methods based on fully coherent light modulations, our approach utilizes a two-point dependent coherence Stokes vector, proving resilient to random noise in experimental scenarios. Our findings provide a robust foundation for higher-dimensional optical encoding and encryption, addressing limitations associated with partially coherent light in complex environments.