We demonstrated a three-dimensional (3D) dental scanning apparatus based on structured illumination. A liquid lens was used for tuning focus and a piezomotor stage was used for the shift of structured light. A simple algorithm, which detects intensity modulation, was used to perform optical sectioning with structured illumination. We reconstructed a 3D point cloud, which represents the 3D coordinates of the digitized surface of a dental gypsum cast by piling up sectioned images. We performed 3D registration of an individual 3D point cloud, which includes alignment and merging the 3D point clouds to exhibit a 3D model of the dental cast.

In this study, we present lateral scanning white light interferometry (LS-WLI), where phase-shifting algorithms are applied to inspect the topography of a large field of view (FOV) with high-speed measurements. At a point, the interference signal must be acquired with a specific condition to adapt the phase-shifting algorithm. This means that all points have two points, of which the phase difference is π/2, when the number of points acquired in a phase period is multiple of 4, despite increasing the data points in a period. Consequently, stretching the fringe spacing in LS-WLI facilitates the application of phase-shift techniques, thereby enhancing stage speed, even with a fixed camera speed. Using the proposed method, we can successfully obtain a laterally expended topographic image as 5.25 mm × 1.25 mm, where the step height of the microstructure is 140 nm.

Transition metal dichalcogenides (TMDs) are promising candidates for ultrathin functional semiconductor devices. In particular, incorporating plasmonic nanoparticles into TMD-based devices enhances the light-matter interaction for increased absorption efficiency and enables control of device performance such as electronic, electrical, and optical properties. In this heterohybrid structure, manipulating the number of TMD layers and the aggregate size of plasmonic nanoparticles is a straightforward approach to tailoring device performance. In this study, we use photoluminescence (PL) spectroscopy, which is a commonly employed technique for monitoring device performance, to analyze the changes in electronic and optical properties depending on the number of MoS₂ layers and the size of the gold nanoparticle (AuNP) aggregate under nonresonant and resonant excitation conditions. The PL intensity in monolayer MoS₂/AuNPs increases as the size of aggregates increases irrespective of the excitation conditions. The strain induced by AuNPs causes a red shift, but as the aggregates grow larger, the effect of p-doping increases and the blue shift becomes prominent. In multilayer MoS₂/AuNPs, quenched PL intensity is observed under nonresonant excitation, while enhancement is noted under resonant excitation, which is mainly contributed by p-doping and LSPR, respectively. Remarkably, the alteration in the spectral shape due to resonant excitation is evident solely in small aggregates of AuNPs across all layers.

Scanning thermal microscopy (SThM) enables to obtain thermal characteristic information such as temperature and thermal conductivity from the signals obtained by scanning a thermometer probe over a sample surface. Particularly, the precise control of the thermometer probe makes it possible to study near-field radiative heat transfer by measuring the near-field thermal energy, which implies that when light is used as a local heat source, photothermal energy can be detected from the optical near-field by approaching the probe in the near-field region. In this study, SThM is applied to generate sub-wavelength near-field optical image in the plasmonic grating coupler. Herein, by controlling the surface plasmon polariton generation, we show that the dominant component of SThM signal is from the optical response rather than the thermal response. The obtained near-field optical images have a spatial resolution of 40 nm and signal to noise ratio of up to 19.8. In addition, field propagation images in the Z-direction can be visualised with the precise control of the distance between the thermometer probe and the sample

Schematic representation of Au loading on the surface of HAp doped Mn conjugated with FA and ICG fluorescence dye for enhanced cancer cell eradication through PTT/PDT.

Heart rate monitoring (HRM) serves as a fundamental component of healthcare systems, providing essential insight into cardiovascular function and overall physiological status. Conventional HRM systems commonly rely on contact-based sensing modalities, such as electrocardiography (ECG) and photoplethysmography (PPG) wearables, which require direct skin contact and complex wiring. This work presents a noncontact ballistocardiogram (NCBCG) bed sensor system integrated with tiny machine learning (TinyML) to provide on-chip processing for noncontact HRM. The proposed system incorporates a polyvinylidene fluoride (PVDF) film sensor placed beneath the mattress, enabling comfortable, nonintrusive, and continuous monitoring. We design a TinyML model that offers on-chip processing on a microcontroller unit (MCU), reducing dependency on cloud-based or external. Experimental findings demonstrate that the system achieves accurate heart rate (HR) estimation, which is compliant with the AAMI standard. These results highlight the feasibility and reliability of accurate HR estimation using embedded artificial intelligence (AI). The work demonstrates potential for real-world applications in long-term remote healthcare and home-based monitoring.