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Simulation and experimental investigation of homogeneity measurement in side-polished transparent cylindrical materials
Zechuan Wei, Liwei Zhang, Sen Han, Yuhang Sheng, Ying Yang, et al.
Published Published online: 29 April 2026 , doi: 10.37188/lam.2026.053
Characterizing the optical homogeneity of side-polished cylindrical transparent materials remains challenging. To address this challenge, a four-step absolute measurement method based on a Fizeau interferometer is proposed for cylindrical transparent materials. The refractive index distribution is derived from wavefront data obtained through four sequential measurements: empty-cavity interference, transmission interference, front-surface interference, and back-surface interference. A homogeneity error of 1 × 10−5 was introduced in MATLAB simulations, yielding a result of 9.9999 × 10−6 with a residual error of 8.0319 × 10−11, confirming the method’s validity. Two repeated measurements performed at different times yielded homogeneity values of hom1 = 9.5802 × 10−6 and hom2 = 9.3331 × 10−6 (2.7% deviation), demonstrating good robustness. The uncertainties of the two measurements were 1.0997 × 10−6 and 0.8767 × 10−6, respectively, and the expanded uncertainties were 2.1994 × 10−6 and 1.7534 × 10−6, respectively. This method effectively isolates surface errors from material homogeneity, providing a practical approach for the accurate characterization of cylindrical optical components.
Precise motion tracking and velocimetry using chirped power oscillation wave
Wei Du, Yujia Li, Hao Wu, Lei Chen, Lei Gao, et al.
Published Published online: 29 April 2026 , doi: 10.37188/lam.2026.033
Precise high-speed motion tracking and velocimetry are critical underlying technologies in various areas such as advanced manufacturing, robotics, and modern physics. Mature detection methods such as Doppler velocimetry and dual-comb interferometry measurements cannot achieve directional unambiguity detection without a trade-off between speed and precision due to the inherent limitations of their system mechanisms. In this study, we propose an innovative high-speed and precise motion detection method based on chirped power oscillation waves (CPOW) generated by dispersion-controlled dual-swept lasers. Our results demonstrate that the displacement and velocity of the target can be directly identified via the power oscillation of the zero-frequency point on the interference signals after carefully controlling for the difference in group delay dispersion between the two beams of the swept lasers. We achieved sub-micrometer-scale displacement measurement accuracy with an update frame rate on the order of MHz and a relative velocity measurement error of better than 0.1%. Furthermore, the proposed method can also be used to reveal the unpredictable operational states of motion-control equipment influenced by mechanical vibrations. This dynamic displacement measurement and velocimetry method based on CPOW opens the door to advanced, fast, and high-precision ranging systems.
SGARNet: a deep artifact removal approach for lensless multi-core fiber imaging
Zewen Ma, Jinwen Wei, Juergen W Czarske, Jiachen Wu, Liangcai Cao
Published Published online: 15 April 2026 , doi: 10.37188/lam.2026.050
Multi-core fiber (MCF) imaging is essential for minimally invasive endoscopy in medicine and industrial inspection. However, the bulky distal optics increase the diameter and invasiveness, causing tissue damage. Its applications are further constrained by low spatial resolution and prominent honeycomb artifacts. We present a lensless MCF imaging approach based on Spectral-Guided Artifact Removal Network (SGARNet). In this framework, a physics-informed prior is embedded in a lightweight SpectralGate module to suppress lattice-frequency artifacts in the feature domain. The experimental results show a 12.12 dB improvement in PSNR and 0.4064 increase in SSIM, indicating superior performance over previous methods. The robustness and generalizability are confirmed by successful reconstructions across diverse textural complexities and biological tissue samples. These results demonstrate potential for practical deployment in compact and safer biomedical endoscopes.
Multi-prior physics-enhanced neural network for high-fidelity arbitrary-path optical particle manipulation
Yuxiang Yun, Wenyu Gao, Yuan Zhou, Xiaohao Xu, Xuan Tian, et al.
Published Published online: 28 April 2026 , doi: 10.37188/lam.2026.051
Phase gradient force-driven particle transport provides a powerful route for steering microparticles along prescribed trajectories. However, conventional designs typically rely on explicit parametric equations to define optical paths, which limits flexibility and often leads to phase-design errors that degrade field uniformity and transport stability. Although physics-enhanced neural networks (PNs) have recently emerged as a promising tool for light-field manipulation, existing approaches are largely built on scalar diffraction models and therefore fail to fully capture the vectorial nature of tightly focused fields. Moreover, relying solely on a single PN prior to solve ill-posed inverse problems often leads to suboptimal solutions and nonuniform phase gradients. Here we introduce MPPN-RW, a multi-prior physics-enhanced neural network built on Richards-Wolf vector diffraction theory. By embedding the physical forward model, phase periodicity, smoothness regularization, and deep image prior into an untrained deep neural network, MPPN-RW jointly optimizes phase holograms for incident-field modulation. Experiments show that the proposed framework generates arbitrarily complex optical trajectories without parametric equations, while improving intensity uniformity and phase uniformity by factors of 8.9 and 6.1, respectively, over conventional methods. These advances markedly improve the flexibility and robustness of optical particle transport and establish a versatile strategy for microscale particle-transport applications.
Curvature-optimised multilevel SERS substrates formed by femtosecond laser shaping based on electrons dynamics control
Jianqi Dou, Lan Jiang, Xiaowei Li, Xibiao Li, Yanfeng Li, et al.
Published Published online: 23 April 2026 , doi: 10.37188/lam.2026.027
Surface-enhanced Raman scattering (SERS) is widely used for trace detection and compositional analysis of biochemical samples. Constructing multidimensionally ordered hotspots with high densities and intensities is crucial for achieving superior SERS substrate performance. Here, we propose a multilevel SERS substrate based on curvature and structural optimisation strategies. We fabricated microlenses with various curvatures via modification and etching using a temporally-shaped femtosecond laser. These lenses were decorated with wrinkles and Ag nanoparticles (AgNPs) via sequential pre-strain application and chemical deposition. Experimental and simulation results demonstrated that the coupling of the wide-field electric field induced by the microlens with the localised plasmonic hot spots on the AgNPs and wrinkles enhanced the localised surface electric field. Curvature-optimised microlenses can increase the wide-field electric fields. The fabricated SERS substrates achieved a low minimum detection limit of 10−11 M and an enhancement factor of approximately 1.22 × 107. These substrates can be employed to detect thiram fungicide on crops using two different methods (in situ detection and solution-assisted detection), demonstrating potential for operating efficiently under different usage conditions.
Ultracompact Wide-FOV near-infrared camera with a wafer-level manufactured meta-aspheric lens
Chuirong Chi, Qichao Hou, Guangyuan Zhao, Qiang Song, Shengyuan Xu, et al.
Published Published online: 22 April 2026 , doi: 10.37188/lam.2026.045
Overcoming the trade-off between a wide field of view (FOV) and compactness remains a central challenge for integrating near-infrared (NIR) imaging into smartphones and AR glasses. Existing refractive NIR optics cannot simultaneously support ultrawide angles above 100° and ultrathin total track lengths (TTL) below 5 mm, fundamentally limiting their integration into portable devices. Herein, we present a wafer-level-manufactured meta-aspheric lens (MAL) that simultaneously achieves a 101.5° FOV, 3.39 mm TTL, and F/1.64 aperture within a compact volume of 0.02 cm3. Unlike previous hybrid systems that rely on separate refractive and diffractive components, the proposed MAL introduces a fully integrated architecture that provides a compact form factor. This integration also simplifies fabrication by enabling high-throughput production via micrometre-level precision alignment and bonding on a single wafer, which requires only one dicing step and no additional mechanical fixtures. Furthermore, the design process incorporates manufacturability and enables metalens dispersion modelling, ensuring that the experimental performance matches simulation results. We validated the MAL method using both direct and computational imaging experiments. Despite its small form factor, our scalable MAL demonstrated strong NIR imaging performance in eye tracking, blood vessel imaging, and computational pixel super-resolution tasks. This scalable MAL technology establishes a new benchmark for high-performance miniaturised NIR imaging, and opens the door for next-generation smartphones and AR optical systems.
Conformal metamaterial inspired contact lenses−designing, 3d printing and characterization for ocular applications
Haider Butt, Mohammed Ayaz Uddin, Muhammed Hisham, Valentyn S. Volkov
Published Published online: 21 April 2026 , doi: 10.37188/lam.2026.039
3D printed contact lenses have emerged as promising candidates for advanced ocular applications due to their customizable design and functional versatility. In this study, a novel conformal auxetic-inspired metamaterial ocular disc architecture was developed using digital light processing (DLP), a high-resolution vat photopolymerization technique, and fabricated using an in-house hydrogel formulation. The printed disc was systematically evaluated for its mechanical, optical, and physicochemical performance. Mechanical testing confirmed excellent elasticity and durability, with the hydrated hydrogel exhibiting a tensile modulus of ~0.71 MPa, matching the range of commercial soft contact lenses. Laser profilometry revealed a smooth surface topology essential for user comfort, achieving a root mean square roughness (Rq) of 1.78 µm, a nearly 98% reduction compared to conventionally printed hemispherical lenses. Contact angle measurements (64° hydrated) indicated favorable wettability. Optical characterization exhibited high light transmittance, averaging ~83% across the visible spectrum in the hydrated state. Hydration related properties, including swelling kinetics, water content, and gel fraction, confirmed effective water uptake and retention, supporting oxygen permeability. FTIR spectroscopy validated the chemical integrity of the polymer network, while DSC/TGA analysis confirmed thermal stability up to 300  °C. Furthermore, rheological evaluation indicated a stable viscoelastic profile with notable self-healing behavior. Collectively, this study establishes a 3D printed hydrogel-based conformal metamaterial contact lens platform, offering a promising pathway for the development of next-generation smart ocular devices via additive manufacturing.
Artificial intelligence-generated photonics: mapping optical properties to subwavelength structures directly via a diffusion model
Shijie Rao, Kaiyu Cui, Jiawei Yang, Yali Li, Shengjin Wang, et al.
Published Published online: 20 April 2026 , doi: 10.37188/lam.2026.037
Subwavelength photonic structures and metamaterials provide revolutionary approaches for controlling light. The inverse design methods proposed for fabricable subwavelength structures are vital for the development of new photonic devices. However, most existing inverse design methods cannot realise direct mapping from optical properties to photonic structures; instead, they rely on forward simulation methods to perform iterative optimization. In this study, we exploit the powerful generative abilities of artificial intelligence and propose a practical inverse design method based on latent diffusion models. Our method directly maps the optical properties to structures without requiring forward simulation and iterative optimization. In this case, the given optical properties can serve as ‘prompts’ and guide the constructed model to ‘draw’ the required photonic structures correctly. Simulations and experiments show that our direct-mapping-based inverse design method can generate fabricable subwavelength photonic structures with high fidelity while following the given optical properties, such as the transmission power, phase, and polarisation responses. This may influence the methods used for optical design and significantly accelerate the research and manufacturing of new photonic devices.
Deep-nanohole-clad waveguides with depth-to-diameter ratio up to 50 000 in single crystals via femtosecond laser writing
Bowen Fan, Yuying Wang, Jiacheng Hu, Xuhu Han, Lijing Zhong, et al.
Published Published online: 17 April 2026 , doi: 10.37188/lam.2026.040
Femtosecond laser writing offers exceptional flexibility and spatial selectivity, enabling the customization of multifunctional integrated devices with nano-scale resolution. This study introduces a novel approach for fabricating nanohole-clad waveguides with ultra-high depth-to-diameter ratios using femtosecond laser writing combined with spherical-aberration-enhanced focal stretching and selective wet etching. This technique not only achieves record depth-to-diameter ratios (>50 000:1) with nanoholes (diameter: 30-500 nm, depth: 1 500 μm) but enables the creation of functional photonic waveguides. The integration of nanoholes into the waveguide structure provides a platform for multi-functional integrated devices, demonstrating significant tunable optical properties. By adjusting pulse energy and axial focal stitching, the diameter of the nanoholes can be tuned from 30 nm to 500 nm with high precision. Further, fluorescent probes embedded within the nanoholes provide a demonstration of optical sensing capabilities, as the waveguide effectively guides light to excite the probes, generating strong detectable signals. The submicron precision achieved through the process ensures high-quality waveguiding with 10.9 dB mode purity, while centimeter-scale periodic arrays exhibit excellent phase uniformity (deviation <3.9%). This work demonstrates the potential of femtosecond laser writing to directly fabricate high-aspect-ratio nanostructures and integrate functional photonic devices on substrates, opening up new possibilities for multi-functional photonics and sensor applications.
Microcavity-enhanced optoelectronic fiber photoacoustic spectroscopy for ppb-level trace gas sensing
Yanyu Jiang, Minghui Du, Xile Han, Zhuobei Deng, Jie Mao, et al.
Published Published online: 16 April 2026 , doi: 10.37188/lam.2026.028
Photoacoustic spectroscopy is a highly sensitive analytical technique for trace chemical detection in gaseous and liquid phases. Conventional systems relying on free-space optics face limitations in light-matter interaction efficiency and electronic integration. To address this, we developed a miniaturized, ultrasensitive photoacoustic spectroscopy gas sensor by integrating a thermally drawn multi-material optoelectronic fiber, a T-type resonant photoacoustic cell, and a MEMS microphone at the fiber tip. This system enables amplified light-gas interactions and simultaneous electrical signal acquisition, achieving ppb-level detection within seconds using sub-microliter sample volumes (0.02 mL). By leveraging mass-producible optoelectronic fibers and MEMS technology, this work establishes a new class of optical sensors featuring compact size, ultrahigh sensitivity, environmental robustness, and scalable multiplexed detection capabilities for harsh environments.
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