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Published
, Published online: 03 April 2026
, doi: 10.37188/lam.2026.056
Employing optical microscopy for visualisation and quantification of dielectric analytes in the near-field area has been a persistent objective, connecting nanoscale dynamics with macroscopic phenomena. Surface plasmon resonance holographic microscopy (SPRHM) leverages evanescent-field interactions and digital holography to enable label-free wide-field quantitative intensity and phase imaging of the near-field area, emerging as a flexible optical tool for high-throughput visualisation and characterization of chemical reactions. However, current SPRHM demodulation methods remain insufficient to meet the growing demand for a higher measurement sensitivity. Here, we introduce an optimised Ag–Au bilayer SPR excitation configuration and angle-scanning thickness demodulation workflow, designed to achieve ultrahigh-sensitivity Refractive index (RI) and thickness measurements, respectively. Experiment results demonstrate the superior performance of the proposed methods: monitoring of RI variations of ethanol-water evaporation dynamics with a resolution of 2.58 × 10−7 RIU and thickness profiling of a graphene terrace specimen with a step-height accuracy of 0.56 nm. Integrated with these advanced methods, we present a versatile SPR holographic microscope prototype that features minimal opto-mechanical complexity, and exceptional stability, enabling unprecedented observations of biomolecular interactions, nanomaterial optics, electrochemical dynamic processes, etc.
Published
, Published online: 15 May 2026
, doi: 10.37188/lam.2026.064
In nature, certain insects possess specialised compound eye structures that provide an ultra-wide field-of-view (FoV) and rapid response capabilities, enabling them to capture prey and avoid obstacles. Herein, inspired by compound eyes, a planar intelligent nanophotonic sensor (PINS) based on a metalens array, which possesses an ultrawide horizontal FoV exceeding 135°, is demonstrated. By leveraging a deep neural network, meta-motion sense (MMS), accurate optical flow can be extracted from PINS-captured wide-FoV scenes, enabling a comprehensive characterisation of the motion velocities and directions of all dynamic objects. Compared to traditional machine-vision-based object recognition algorithms, the proposed approach exhibits significantly higher accuracy and robustness, particularly in detecting small, slow, or background-blended moving targets, and offers an intelligent predictive capability for forecasting the motion trajectories of objects. The proposed device combines the advantages of high compactness, superior motion-detection performance, and intelligent functionality, offering a promising foundation for next-generation applications in autonomous navigation, situational awareness, and military surveillance.
Published
, Published online: 13 May 2026
, doi: 10.37188/lam.2026.059
Diatoms are single-celled microalgae with highly ordered nano- and microstructured silicon dioxide shells (silica frustules), which function as natural photonic crystals for efficient light management. One of the predicted optical phenomena in diatom frustules is near-field Talbot interference, which provides localised focusing of incident radiation within a cell. In this work, we employed geometric scaling in the terahertz (THz) regime, where the Talbot distance increases to millimetres, allowing direct visualisation of the longitudinal self-imaging process. Scaled-up biomimetic models of diatom frustules were produced using liquid crystal display (LCD) 3D printing, and optical characterisation was performed at a wavelength of λ = 911 µm. The size of the holes in the structure ranged from 100 µm to 1 mm, corresponding to approximately a 2,000-fold geometric scale-up relative to natural diatom features. At a distance of 4.6 mm from the structure, the intensity at the focal points was half that of the original beam. The experimental results are consistent with numerical simulations carried out using the Fourier modal method. This work demonstrates a bioinspired approach to low-dimensional diffractive photonic structures with controllable optical properties by translating diatom-inspired nanophotonic concepts into manufacturable polymers. The designs obtained provide a scalable route to fabricating THz components that can function as flat focusing optics, tunable resonant filters, and wavefront modulators when integrated into devices. Compatibility with additive manufacturing enables large-scale, cost-effective production by allowing the combination of natural photonic architectures with modern fabrication techniques, thereby supporting applications in photonic systems, light harvesting, and smart sensing.
Published
, Published online: 13 May 2026
, doi: 10.37188/lam.2026.042
High-resolution, high-throughput, and minimally invasive imaging is in increasing demand in modern biomedical research. However, conventional single-modality optical microscopy often fails to satisfy these requirements. In this paper, we present a highly integrated multimodal fluorescence-phase microscopy (MFPM) system. By leveraging illumination pattern encoding, a unified wide-field detection configuration, and an integrated computational algorithm, MFPM achieves five imaging modes: optical-sectioning structured illumination microscopy (OS-SIM), super-resolution structured illumination microscopy (SR-SIM), polarisation dipole analysis, fast differential phase contrast (fDPC), and quantitative differential phase contrast (qDPC) imaging. By incorporating dark channel prior-based background removal, MFPM achieves improved imaging depth, whereas the frame-reduction strategy enables a higher imaging speed. Consequently, only ten raw frames are required to reconstruct multidimensional information. This integrated platform enables co-registered multimodal imaging for diverse biomedical applications, including the subcellular visualisation of U2OS cells, quantitative auxiliary diagnosis of pathological tissue sections, and analysis of zebrafish heartbeats. With its compact design and multidimensional imaging capabilities, MFPM offers a unified solution for structural and functional imaging. Its scalability toward intelligent event-triggered imaging, and virtual staining integration makes it a promising platform for next-generation automated biomedical imaging.
Published
, Published online: 13 May 2026
, doi: 10.37188/lam.2026.054
A novel dual-gas light-induced thermoelastic spectroscopy (DG-LITES) sensor based on mixed-frequency heterodyne demodulation (MHD) is reported. The DG-LITES sensor exploits the fundamental and first overtone vibration modes of a single self-designed low-frequency quartz tuning fork to achieve the high-performance simultaneous detection of methane (CH4) and acetylene (C2H2). Using a frequency-division multiplexing mechanism, this technique creates dual detection channels based on a single sensing element. Furthermore, it uses the MHD method to convert photothermal signals at different frequencies into a unified intermediate frequency, thereby enabling synchronous demodulation with only one correlation demodulation unit. The DG-LITES sensor not only maintains system compactness but also effectively suppresses inter-channel crosstalk below 0.057%. Experimental results demonstrated that the DG-LITES sensor exhibited excellent linear responses to both CH4 and C2H2 (R2 > 0.999), with maximum nonlinearity errors as low as 1.39% and 1.48% full-scale span, respectively. The mean relative systematic errors were 0.95% and 0.93%, respectively, whereas the maximum relative errors were 1.8% and 2.5%, respectively. Allan deviation analysis validated the excellent long-term operational stability of both the CH4 and C2H2 channels. The minimum detection limits for both channels were 0.13 and 2.93 ppm, with normalised noise-equivalent absorption coefficients of 2.73 × 10−9 and 9.61 × 10−8 cm−1·W·Hz−1/2, respectively. This paper presents a universal sensing architecture that offers a novel solution to the long-standing trade-off between performance and system complexity in multi-gas detection.
Published
, Published online: 12 May 2026
, doi: 10.37188/lam.2026.046
Beyond conventional thermo-optic (TO) devices, this study introduces a hybrid photonic platform integrating a polymer micro-ring resonator (MRR), fabricated via two-photon printing and functionalized with Ag2Te quantum dots (QDs), onto a fibre end. By leveraging advanced two-photon micro-printing, we precisely fabricated complex hybrid MRR structures, thereby facilitating unprecedented on-chip integration and intricate three-dimensional geometries that remain unattainable using traditional methods. The proposed platform utilises an Ag2Te QD-functionalized polymer film, wherein controlled interfacial engineering in conjunction with the intrinsic localised surface plasmon resonance (LSPR) of the QDs amplifies the local optical field by 300% and fundamentally reconfigures photon–thermal–carrier interactions. An innovative two-dimensional (2D) synergistic all-optical modulation strategy is employed, leading to substantial performance improvements, including a 19.77-fold enhancement in tuning sensitivity over standard polymer MRRs and 50-fold improvement in modulation speed, reaching up to 100 kHz, which significantly exceeds those of conventional TO platforms. This compact fibre-integrated architecture, enabled by precision additive manufacturing, delivers a robust, energy-efficient, and high-speed solution for dynamically reconfigurable on-chip TO modulation and represents a transformative step forward for integrated photonic circuits.
Published
, Published online: 12 May 2026
, doi: 10.37188/lam.2026.049
As semiconductor manufacturing advances towards finer feature sizes, mask optimization (MO) has become increasingly critical in optical lithography to ensure pattern fidelity. In extreme ultraviolet (EUV) lithography, full-chip MO encounters significant challenges in terms of computational accuracy and efficiency, which are exacerbated when employing curvilinear patterns. Herein, we propose a full-chip curvilinear MO framework for EUV lithography that integrates deep-learning-enabled forward modelling with gradient-based inverse optimization. We represent the forward model using a tuneable U-net trained on data generated by an accurate and efficient modified Born series method. This model achieves a significantly lower complexity by describing the 3D mask effect through amplitude and phase perturbations. For inverse optimization, gradients are calculated via the adjoint method using slices of the 3D mask field as input—a significantly more efficient approach than utilising the entire 3D field. Evaluated under typical scenarios, the proposed framework demonstrates a four-order-of-magnitude speedup compared with MO based on the finite-difference time-domain method without compromising accuracy. Leveraging this framework, the MO for a 1 mm2 wafer area with 19.41 nm critical dimensions can be completed in 31.7 h using 1,000 GPUs, highlighting its potential for full-chip EUV curvilinear mask optimization.
Published
, Published online: 11 May 2026
, doi: 10.37188/lam.2026.060
The exceptional mechanical and thermal properties of silicon carbide (SiC) make it vital for advanced optics; however, its hardness and brittleness cause subsurface defects (SSDs) during machining that impair performance and longevity. Current detection methods remain destructive and inefficient, whereas conventional optical coherence tomography (OCT) struggles with limited penetration, surface scattering interference, and poor defect contrast in this highly scattering material. We propose a non-destructive off-axis bright- and dark-field synchronous OCT (BADF-OCT) method that captures complementary scattered signals at dual angles to enhance weak subsurface feature detection. The broadband 1100–1500 nm near-infrared spectral-domain OCT system provides high axial resolution with adequate SiC penetration. Experimental validation on reaction-bonded SiC demonstrates clear discrimination between surface fracture and subsurface crack layers, providing reliable detection of micrometre-scale defects at depths up to ~200 μm. Three-dimensional volumetric imaging combined with bright/dark-field data fusion effectively distinguishes true SSDs from surface contaminants, significantly improving the recognition accuracy. This study is expected to contribute to the development of high-energy lasers, large-scale scientific facilities for light sources, and advanced optical manufacturing.
Published
, Published online: 06 May 2026
, doi: 10.37188/lam.2026.036
Direct-write multi-photon laser lithography (MPL) combines highest resolution on the nanoscale with essentially unlimited 3D design freedom. The groundbreaking potential of this technique has been demonstrated in various application fields, including micromechanics, material sciences, microfluidics, life sciences, as well as photonics, where in-situ printed optical coupling elements offer new perspectives for package-level system integration. However, millimeter-wave (mmW) and terahertz (THz) devices did not yet leverage the unique strengths of MPL, even though the underlying devices and structures could also greatly benefit from 3D freeform microfabrication. A key challenge is that functional mmW and THz structures require materials with high electrical conductivity and low dielectric losses, which are not amenable to structuring by multi-photon polymerization. In this work, we introduce and experimentally demonstrate a novel approach that leverages MPL for fabricating high-performance mmW and THz structures with hitherto unachieved functionalities. Our concept exploits in-situ printed polymer templates that are selectively coated through highly directive metal deposition techniques in combination with precisely aligned 3D-printed shadowing structures. The resulting metal-coated freeform structures (MCFS) offer high surface quality, low dielectric losses, and conductivities comparable to bulk material values, while lending themselves to in-situ fabrication on planar mmW and THz circuits. We experimentally show the viability of our concept by demonstrating functional THz structures such as ultra-broadband chip-chip interconnects, THz probe tips, and suspended THz antennas. We believe that our approach offers disruptive potential in the field of mmW and THz technology and may unlock an entirely new application field for laser-based 3D manufacturing.
Published
, Published online: 06 May 2026
, doi: 10.37188/lam.2026.052
The weak scattering and overwhelming background of periodic structures fundamentally hinder the inspection of subwavelength defects embedded in dense nanopatterns. Herein, we introduce an actively tunable photothermal modulation scheme that leverages the temperature-dependent resonance shifts of silicon nanostructures to engineer their far-field scattering signatures. Localised optical heating induces a redshift in the underlying resonances, producing a strongly nonlinear change in both the defect and background scattering. This modification amplifies defect-induced perturbations and suppresses background contributions, substantially enhancing the inspection sensitivity for deep-subwavelength defects. A coupled optical-thermal model quantitatively captures the temperature rise and transient thermal evolution and predicts the resonance modulation achievable under the given pump conditions. This study establishes reversible, non-destructive photothermal resonance modulation as a general mechanism for dynamically engineering optical contrast in patterned media, offering a pathway towards high-sensitivity wafer inspection and tunable nanophotonic sensing.
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