This study establishes a label-free optical diffraction tomography (ODT)-based workflow for live-cell imaging and analysis to observe time-dependent morphological changes in macrophages. The method enables continuous recording of single-cell morphology and movement over extended periods under stable environmental conditions and allows extraction of quantitative parameters, including projected area, perimeter, and average migration speed. This workflow provides a practical approach for capturing dynamic cellular behaviors at the single-cell level without exogenous labeling. Using RAW264.7 macrophages as a model, time-lapse imaging was performed under lipopolysaccharide stimulation with baicalin pretreatment to capture dynamic cellular changes under different conditions. Representative cells were selected for tracking and quantitative analysis. The results show that this workflow supports stable long-term single-cell tracking and reflects temporal changes in cell morphology and motility. This approach provides a label-free method for observing dynamic cellular behaviors in response to different stimuli and can serve as a useful complement to conventional endpoint-based assays. It may also be applicable to other adherent cell types for studies of cell morphodynamics.

Polystyrene nanoplastics induce mitochondrial dysfunction and stress responses in human PBMCs.

Two-dimensional cell culture models have long been a cornerstone of biomedical research; however, they often fail to accurately replicate the in vivo environment. In recent years, three-dimensional (3D) cell cultures, particularly 3D spheroid models, have gained recognition for their ability to better mimic the complexities of the in vivo environment, making them valuable tools for studying cellular behavior and responses. Tumor spheroids, in particular, have significant applications in anticancer therapy evaluation, providing a more physiologically relevant model by simulating the spatial architecture and microenvironment of tumors. However, due to the limitations imposed by optical diffraction and background noise in 3D imaging, traditional imaging methods are unable to accurately resolve the growth, morphological changes, and drug responses of tumor spheroids. To address this issue, super-resolution imaging technologies have emerged. Structured illumination microscopy (SIM) combined with reconstruction algorithms can effectively enhance resolution, but challenges such as limited light penetration of single-photon imaging and high background noise remain in 3D imaging. In this paper, an advanced SIM technology with large depth and low noise 3D imaging capability is developed. This study introduces a novel frequency-specific denoising method (FSDM) to effectively reduce noise through adjusting the weights of high-frequency signals to preserve image details. The FSDM optimization significantly reduces background interference from deeper tissue layers, improving image details and the overall quality of 3D imaging. For the first time, scanning SIM is integrated with two-photon microscopy (TPEF-SIM) for 3D imaging, leveraging the strengths of both techniques to enhance resolution and overcome light penetration limitations.

We present optical design concepts for a miniaturized multimodal endoscopic imaging system capable of targeting the same sample plane across widely separated wavelength ranges. The system uses a scanning-fiber approach and exploits the wavelength-selective imaging properties of diffractive optical elements (DOEs), allowing different diffraction orders to form images for distinct spectral bands and partially decoupling the optical design for each range. The system is designed to achieve high first-order diffraction efficiency in the UV/short visible region while simultaneously operating in the zeroth order for 1300-1700nm. Angular emission variations of the scanning fiber are compensated, enabling a compact layout and low-loss beam delivery. Both three- and two-element designs with strongly aspheric surfaces are analyzed. Backward light propagation to the scanning fiber is evaluated theoretically, highlighting efficient collection via the fiber cladding and its potential enhancement by introducing ring-shaped lenses and reflective surfaces.

Dataset-driven holographic incoherent-light-source optical diffraction tomography applied to red blood cells

We present the employment of wavefront imaging using Quadriwave Lateral Shearing Interferometry (QLSI) for Optical Diffraction Tomography (ODT) reconstructions. Compared to a conventional Digital Holographic (DH) Interferometer, QLSI does not require a reference beam. It can also work efficiently with an incoherent source and hence reduces the speckle noise. Furthermore, QLSI is almost insensitive to phase wrapping, thus avoiding artefacts and easing the signal processing in ODT. We validate the method by reconstructing the 3D refractive index (3DRI) of a polystyrene bead via angle-scan diffraction tomography. The 3DRI reconstruction of the nano-printed phantom cell and the living yeast cell is also presented.

Rapid and high-fidelity nanoscale 3D printing is highly desirable, but it is difficult due to the tradeoff between speed and accuracy. Although optical projection techniques can massively scale up printing, fidelity is compromised due to the difficulty in precisely controlling the light dosage over the entire field. This challenge is typically addressed by using multiple projections, but it slows down printing. Here, we present grayscale projection two-photon lithography to overcome this tradeoff. Despite using a binary mask, it enables projecting more than 15,000 focal spots, each with independently tunable intensity. It advantageously leverages constraints imposed by optical diffraction to achieve grayscale tuning over the entire field at once. By directly tuning the focal spot intensities, we demonstrate suppression of proximity effects, compensation of non-uniform illumination, compensation of stitching artefacts, and rapid 3D printing with a single femtosecond pulse per layer. We demonstrate printing of nanowires as thin as 55 nm and achieve rates of 1.7 billion voxels/s and 215 mm3/hr.

Extracellular vesicles (EVs) facilitate intercellular communication and have emerged as valuable diagnostic and prognostic biomarkers, therapeutic tools, and delivery systems. Due to their heterogeneity, precise profiling of EVs requires sub-EV resolution beyond standard EV biomarkers. Additionally, there is a growing need to trace the biogenesis of individual EVs. While super-resolution microscopy enables EV profiling at the nanoscale with biochemical specificity, the lack of standardized workflows for EV purification, immobilization, and labeling continues to limit reproducibility and biological interpretation. Here, we demonstrate the use of two standard purification methods to prepare EVs isolated from two cellular sources for nanoscale characterizations of CD81 using direct stochastic optical reconstruction microscopy (dSTORM). Using polymer-based precipitation and size-exclusion chromatography, we isolated EVs from cultured cells and immobilized them on poly-l-lysine-coated glass surfaces for immunofluorescence staining. dSTORM imaging revealed broad size distributions of EVs and variations in the nanoscale spatial organization of CD81. In both Jurkat T cells and hepatocellular carcinoma cells (HCC), we identified a subpopulation of EVs below the optical diffraction limit with asymmetrical CD81 distributions and developed quantification metrics to characterize this feature. In addition, we demonstrated the successful distinction between ectosomes and exosomes using a pan-membrane-protein labeling strategy. Together, these findings establish EV isolation methods coupled with dSTORM as a robust strategy for high-resolution sub-EV analysis, enabling the precise characterization of EV heterogeneity and biomarker discovery.

Elastomers with nanostructured surfaces exhibit substantial importance in enhancing interfacial properties including mechanics and optical diffraction. However, the structure on elastomer surfaces by imprinting is limited to microscale features due to kinetically arrested reptation diffusion and inevitable entropic recovery. Herein, we design a dynamic elastomeric network to achieve nanoimprinting with ultrahigh resolution and aspect ratios by chain translocated crystallization in nanochannels. Specifically, dynamic covalent bonds trigger network reconstruction after thermal activation and enhance chain disentanglement, which promotes chain translocation in nanochannels. Meanwhile, the crystalline phase within nanochannels creates energetic barriers that effectively restrict entropy-driven recovery. This strategy enables imprinting of elastomer surfaces with sub–10-nm structures, across a 107 range in length scale and aspect ratios exceeding 100:1, far outperforming conventional elastomers. Moreover, the imprinted nanostructures provide elastomer surfaces with a marked modulus enhancement by ~5 times to reach 4.2 gigapascals while simultaneously improving optical transparency, which endows elastomers with highly integrated multifunctional protective capabilities.

The uniformity of local photoelectric properties in infrared detectors is critical for detection sensitivity. However, micro-nano-scale surface abnormalities introduced during mercury cadmium telluride (HgCdTe) fabrication systematically degrade in-plane photoelectric response consistency. To overcome the optical diffraction limits of standard far-field metrology, we utilized a cryogenic scattering-type scanning near-field optical microscopy (Cryo-SNOM) system to achieve the first super-resolution, in situ imaging of local near-field photocurrent in HgCdTe photoconductive detectors at 10 K. Device-level measurements reveal that sub-wavelength surface protrusions (~tens of nanometers high) act as strong recombination centers, suppressing local photocurrent and causing a consistent 10~20% relative signal attenuation compared to planar regions. Power and bias-dependent testing indicate these defects function as unsaturated linear recombination states. Increasing bias voltage amplifies the coupling between the external field and the defect’s built-in field, broadening the local depletion region and driving a non-linear escalation in the attenuation ratio. This study establishes quantitative engineering tolerances for morphological deviations at the nanoscale, providing critical criteria for the chip integration, structural optimization, and precision manufacturing of high-performance infrared sensing arrays.

Fe and La-co-doped ZnO nanoparticles were preparedby using the sol–gel method. We investigated the samples’structural, morphological, vibrational, and optical properties usingX-ray diffraction (XRD), field emission scanning electron microscopy(FESEM) with energy-dispersive X-ray spectroscopy (EDS) elementalmapping, Fourier transform infrared spectroscopy (FTIR), ultraviolet–visible(UV–vis) diffuse reflectance spectroscopy (DRS), and photoluminescence(PL) spectroscopy. Rietveld refinement of the XRD pattern confirmedthe p63mc space group and the hexagonal wurtzite structureof the samples, with no formation of secondary phases. X-ray photoelectronspectroscopy analysis revealed that, in Fe- and La-doped ZnO, zincexists as Zn2+, iron as Fe3+, and lanthanumas La3+. These substances have substantial surface oxygendefects, which account for the visible emission bands. FTIR spectraconfirm the presence of a hexagonal wurtzite structure and of thechemical bonds and functional groups in the sample. UV–visDRS spectroscopy revealed a decrease in the band gap due to Fe doping.Fe and La doping reduce the band gap of ZnO, causing a redshift thatenhances interaction with visible light. This makes Fe, La-doped ZnOa potential photocatalyst. The PL spectra exhibit UV emission fromexcitonic recombination and visible emissions, including violet lightfrom zinc vacancies and green light from zinc–oxygen divacancydefect transitions. The correlated color temperature values are 6425–6503K, which closely match ideal cool white light. This makes it idealfor outdoor white LED applications due to its enhanced visual acuityand brightness.

Transparent conductive materials still face significant challenges in simultaneously achieving high optical transmittance, broadband electromagnetic interference (EMI) shielding, and excellent environmental stability. In this work, a hexagonal-Voronoi composite metal mesh (HV-CMM) is proposed by integrating a periodic hexagonal framework with stochastic Voronoi substructures, which effectively suppresses optical diffraction while maintaining structural stability. By tuning the characteristic size of the Voronoi features, a synergistic optimization of optical and electromagnetic performance is achieved. The fabricated HV-CMM exhibits high optical transmittance of 78-83% and low haze of 4.5-4.8% in the visible range. Owing to the disruption of long-range periodicity, coherent diffraction is effectively suppressed, leading to improved visual uniformity. In the 1-18 GHz frequency range, the samples demonstrate stable EMI shielding performance, with an average shielding effectiveness of 38.5 dB and a maximum value of 47.8 dB at 12 GHz. In addition, the HV-CMM shows rapid and uniform electrothermal response, reaching a temperature of 143 °C within 150 s under an applied voltage of 1 V. The introduction of a Ni passivation layer significantly enhances environmental stability, reducing the variation in sheet resistance from 152.9% for pure Cu to 42.4% after 240 h under 85 °C/85% RH conditions. This work presents a structure-material co-design strategy, providing a new pathway for multifunctional transparent conductive meshes in applications such as optical windows, defogging/deicing systems, and electromagnetic protection.

Two ternary liquid crystalline mixtures are formulated and investigated by differential scanning calorimetry, polarizing optical microscopy, X-ray diffraction, and broadband dielectric spectroscopy. Paraelectric smectic A*, ferroelectric smectic C*, and antiferroelectric smectic CA* phases are detected. The glass of the smectic CA* phase is formed at moderate cooling rates. Vitrification prevents the approaching transition to a hexatic smectic phase. One mixture shows a strong thermochromic effect in the smectic CA* phase and selectively reflects blue light in the glassy state. Both mixtures reflect either green or red light in the smectic C* phase, depending on temperature treatment: whether the sample is cooled or heated, or at which rate the temperature changes.

The Conform process (Continuous Rotary Extrusion, CRE) enables the production of magnesium alloy wires like Mg-Zn-Al-Ca (ZAX210) with refined microstructures and tailored textures, but also introduces cross-sectional inhomogeneities that affect the final material response. In this work, a combined experimental and finite element (FE) simulation approach was used to analyse these inhomogeneities in terms of microstructure, texture, and deformation conditions. Optical and electron backscatter diffraction (EBSD) analyses revealed an overall fine grain structure (∼5.7 μm), with slightly smaller grains in the surface layers due to enhanced dynamic recrystallization. Texture development is governed by extrusion- and shear-induced deformation, resulting in a rotated B-fibre (basal plane parallel to shear plane) as the global texture component. Local variations include a B-fibre with weak C 1 -fibre component (c-axis is fibre axis first rotated 90° in shear direction, then 30° in shear plane direction) in the upper region, a strong B-fibre in the middle region, and C 1 /C 2 -fibres in the lower region caused by shear reversal. A fiber texture describes preferred crystallographic orientation, where most grains align a specific crystal direction with a common axis. Twinning activity reflects the heterogeneous deformation state, with ( tension twins dominating overall but being suppressed in high-shear regions. FE simulations confirmed the asymmetric shear stress distribution and complex flow near the abutment, providing a mechanistic link between local strain, recrystallization, and texture evolution. The middle region, representing ∼62 % of the cross-sectional area, was found to dominate the global microstructure and texture.

Far-field femtosecond laser etching of sub-diffraction-limit nanogrooves on copper using high purity longitudinal field enhancement

Hyperspectral sensing allows for the capture of spatially resolved spectral data, a capability critical for applications spanning from remote sensing to biomedical diagnostics. Nevertheless, the widespread adoption of this technology is hindered by the bulk and complexity of traditional systems based on diffractive optics. To overcome these hurdles, substantial research efforts have been dedicated to system miniaturization via component scaling and computational imaging. This review outlines the technological progression of compact hyperspectral imaging, ranging from miniaturized dispersive elements and tunable filters to computational snapshot designs using optical multiplexing. Although these approaches decrease system volume, they generally treat the sensor as a passive intensity recorder requiring external encoding. Therefore, we focus here on the rising paradigm of sensor-level integration made possible by nanomanufacturing. We examine optics-free architectures where spectral discrimination is embedded directly into the pixel, distinguishing between pixel-level nanophotonic filtering and intrinsic material-based selectivity. We specifically highlight emerging platforms such as compositionally engineered and cavity-enhanced perovskites, as well as electrically tunable organic or two-dimensional (2D) material heterostructures. To conclude, this review discusses persistent challenges regarding fabrication uniformity and stability, providing an outlook on the future of scalable and fully integrated hyperspectral vision systems.

In the era of increasing generation of various waste streams, the possibility of utilizing them as secondary resources is of utmost importance and fully corresponds to the goals of the circular economy. Industrial residues from the pulp and paper industry, such as biomass combustion ash (FARP) and sludge from industrial wastewater treatment (PPWS), together with natural zeolite as a modifying additive, represent valuable sources enabling their integrated valorization. The present study aims to investigate the potential for their reuse through the development of sustainable material blends. A comprehensive analysis of the chemical composition and morphology of the obtained mixtures was carried out using inductively coupled plasma optical emission spectroscopy (ICP-OES), X-ray diffraction (XRD), and scanning electron microscopy (SEM). The results indicate a tendency for the formation of mineral matrices dominated by calcium-sulfur-oxygen (Ca-S-O) phases, with the presence of calcium sulfate and aluminosilicate structures. The blends are associated with the formation of stable crystalline structures exhibiting potential pozzolanic activity. In this way, carbon is captured and fixed in a stable mineral form. The obtained results suggest the potential of these blends for use in low-carbon systems focused on waste valorization and carbon retention. The materials may be suitable for applications in construction, soil remediation, and environmental technologies, contributing to closing the resource loop "from farm to table and back again".

Studying plasma dynamics is crucial for understanding processes like inertial confinement fusion, material damage, and shockwave formation from intense laser or current interactions. While pump-probe methods are standard for capturing these dynamics, single-shot experiments using high-power, low-repetition-rate systems with custom targets are challenging. We present a novel, to the best of our knowledge, imaging technique, using a synchronized GHz-rate spectrally tagged probe laser, which can capture multiple time-resolved snapshots from a single pump event. Diffraction optics spatially separate the pulses, yielding nanosecond-resolved images. Traditional pump-probe experiments with tantalum and borosilicate glass show shockwave velocities consistent with literature, validating the method's accuracy and utility in plasma diagnostics.

Mitochondrial morphology is a critical indicator of cellular metabolic status and disease pathogenesis, requiring high-resolution visualization and precise segmentation in electron microscopy (EM) images. While fully supervised deep learning models have achieved significant progress, their reliance on dense pixel-wise annotations presents a major bottleneck due to the labor-intensive labeling process and expert variability near the optical diffraction limit. Existing weakly supervised methods, primarily designed for densely packed instances, often fail to generalize to the sparse distribution of mitochondria in EM data. In this paper, we propose WeakMitoSAM, a novel weakly supervised framework for high-precision mitochondria segmentation using sparse point annotations. Our approach introduces the competitive aggregation of multiple prompts strategy, which employs a Bias-augmented Softmax mechanism to reconcile semantic ambiguities and suppress background noise, effectively converting sparse priors into high-fidelity pseudo-labels. Subsequently, segment anything model is specialized for mitochondrial ultrastructures via low-rank adaptation, ensuring parameter-efficient domain adaptation. Experimental results across four public EM datasets demonstrate that WeakMitoSAM achieves state-of-the-art performance in point-supervised scenarios and even outperforms several fully supervised benchmarks, providing an efficient and robust solution for large-scale mitochondrial morphofunctional analysis.

Two-dimensional (2D) semiconductors such as monolayer WSe2 have attracted significant interest for their quantum properties and potential as scalable single-photon emitters. However, conventional microphotoluminescence (μ-PL) techniques are fundamentally limited by optical diffraction, hindering access to critical nanoscale features such as strain gradients and localized quantum confinement. In this study, we utilize tip-enhanced photoluminescence (NanoPL) with a spatial resolution of ≈10 nm to directly image the emission landscape of monolayer WSe2 on top of nanopillars at room temperature. Our results reveal two distinct localization regimes associated with leading theoretical models for single-photon activation and provide guidelines for deterministic nanoengineering of quantum light sources.