Chun-Hung Lin

This study aimed to enhance the sensing performance of nitrogen dioxide (NO₂) gas sensors fabricated using gallium oxide (Ga₂O₃) nanorod sensing membranes. The hydrothermal synthesis method was used to grow GaOOH nanorods on a roughened tin oxide (SnO₂) seed layer with various periods fabricated using a nanoimprint system. Then, the GaOOH nanorods were converted to Ga₂O₃ nanorods by nitrogen annealing treatment. Under 10 ppm NO₂ and operating temperature of 210 °C, the optimal response of the NO₂ gas sensors using Ga₂O₃ nanorods grown on an 800 nm periodic seed layer was 56.2. To further improve the performance attributed to the spillover effect of noble metal, p-type gold-black nanoparticles (NPs) were deposited onto the n-type Ga₂O₃ nanorod surfaces using a vapor cooling condensation system to form p-n heterojunctions. When Ga₂O₃ nanorods were decorated with 1.02 at.% gold content, the optimal response was increased to 143.9 under 10 ppm NO₂ at an operating temperature of 180 °C. To investigate the photo-activation effect on the NO₂ gas sensors, 245 nm UV light was applied to the devices. Under the UV light intensity of 4.8 mW/cm², the response of the resulting NO₂ gas sensors without and with gold-black NPs was increased to 123.1 and 370.5, respectively.

Microcavity lasing in solution‐processed 2D halide perovskites remains a central challenge because intrinsic phase heterogeneity, defect‐assisted scattering, and ambiguous optical feedback obscure the physical origin of coherence. It remains unresolved whether the long‐range coherence reported in quasi‐2D perovskite lasers arises from intrinsic cavity‐mediated photonic feedback or from extrinsic effects, such as interference contributions. Here, we demonstrate that a synergistic combination of alkali‐metal‐assisted phase engineering and thermal imprint‐induced recrystallization enables high‐quality‐factor (High‐ Q) Fabry–Pérot microcavity lasing with long‐range coherence in quasi‐2D perovskites. Incorporation of sodium bromide into PEA ₂ Cs _{n −1} Pb _n Br _{3 n +1} quasi‐2D perovskites effectively modulates the distribution of n ‐phases by reducing nonradiative low‐ n components and suppressing intrinsic crystal defects. The recrystallization process was facilitated by thermal imprinting and enhanced orientational ordering in the selected phases. These advances enabled the formation of low‐optical‐loss FP microcavities that supported lasing with a quality factor reaching up to Q ≈ 6890. Angle‐resolved photoluminescence, combined with parity‐resolved Young's interference measurements, directly revealed the longitudinal mode order and phase locking, providing unambiguous evidence of photonic coherence across the entire microcavity. The observed lasing is attributed to enhanced wavefunction overlap and rapid exciton recombination enabled by spatial confinement within the quasi‐2D perovskite layers, which collectively promote photonic lasing over alternative mechanisms. These findings address a key ambiguity in quasi‐2D perovskite laser physics by positioning thermally imprinted microcavities as scalable and physically interpretable platforms for on‐chip coherent light sources.

Flexible electronic devices are rapidly advancing, bringing innovative applications to optoelectronic technology. However, traditional optoelectronic devices are limited by rigid substrates, making them unsuitable for flexible applications. Due to its excellent optoelectronic properties and low processing temperature, zinc oxide (ZnO) has become an ideal material for flexible photodetectors (PDs). This study aims to integrate grating-patterned ZnO nanograss onto a flexible polyethylene terephthalate (PET) substrate using nanoimprint lithography (NIL) to enhance the broadband photosensing capabilities of ZnO-based PDs. Experimental results show that NIL technology successfully fabricates uniform and well-structured ZnO nanorod gratings on PET substrates, with a linewidth of approximately 600 nm and a pitch of about 1080 nm. Material analyses indicate that the NIL process, assisted by oxygen plasma etching, increases surface oxygen adsorption on ZnO nanorod surfaces, thereby improving device sensitivity. Notably, photosensing measurements demonstrate that, compared to conventional nonpatterned ZnO nanograss PDs, grating-patterned ZnO nanograss PDs exhibit significantly enhanced photoresponse in the visible light region. Absorption spectrum analysis further confirms that the grating structure effectively improves light absorption in the visible wavelength range. This enhanced photoresponse is attributed to the grating structure, which extends the optical path and increases light absorption by ZnO nanorods. Additionally, this study employs artificial intelligence (AI) deep learning techniques to analyze photosensing data, successfully identifying the corresponding light sources. This work demonstrates the potential of NIL technology in improving the broadband photosensing performance of ZnO-nanograss-based PDs and, in combination with AI deep learning, creates a broadband PDs capable of distinguishing different light sources without requiring optical filters. This research paves the way for future development of flexible optoelectronic devices, with ZnO nanograss PDs showing great potential for advanced light sensing applications.

This study successfully fabricated silver-decorated, submicrometer patterned zinc oxide (ZnO) nanograss substrates using nanoimprint lithography (NIL) and hydrothermal synthesis to achieve enhanced surface-enhanced Raman scattering (SERS) sensitivity. The ZnO nanograss structures were precisely patterned via NIL, allowing for controlled spatial arrangement and selective growth, with grating periods ranging from 1000 to 2000 nm and defined area widths between 500 and 1000 nm. Silver nanoparticles were deposited on the substrates through electron beam evaporation. The patterned design of the ZnO nanograss substrates significantly enhanced grating-mediated resonant excitation of localized surface plasmon resonance (LSPR), optimizing the interaction between incident light and the substrate. This resulted in more concentrated and focused light fields, which further amplified the LSPR effects. The impact of substrate hydrophobic characteristics, induced by dark storage for up to 3 months, on SERS performance was thoroughly investigated, with contact angles increasing from 93.5 to 144° during storage. These sticky properties facilitated the concentration of analyte molecules, significantly enhancing Raman signal intensity. Various periodic patterns, including one-dimensional (1D) gratings and two-dimensional (2D) arrays, were optimized to determine the ideal grating period for maximum Raman signal enhancement, achieving an analytical enhancement factor of 6.31 × 10¹⁰. Comprehensive characterization techniques, such as scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS), were used to analyze the substrates' morphology, elemental composition, and structural properties. SERS sensitivity was evaluated using malachite green (MG) molecules, revealing an impressive limit of detection (LOD) of 1.85 × 10^-15. Furthermore, the substrates exhibited excellent long-term stability and signal reproducibility, maintaining consistent SERS performance after extended storage. This research establishes a cost-effective and highly sensitive SERS platform, offering significant potential for applications in chemical, environmental, and biochemical analysis.

Cancer diagnostics often faces challenges, such as invasiveness, high costs, and limited sensitivity for early detection, emphasizing the need for improved approaches. We present a surface-enhanced Raman scattering (SERS)-based platform leveraging inverted pyramid SU-8 nanostructured substrates fabricated via nanoimprint lithography. These substrates, characterized by sharp apices and edges, are further functionalized with (3-aminopropyl)triethoxysilane (APTES), enabling the uniform self-assembly of AuNPs to create a highly favorable configuration for enhanced SERS analysis. Performance testing of the substrates using malachite green (MG) as a model analyte demonstrated excellent detection capabilities, achieving a limit of detection as low as 10⁻¹² M. Building on these results, the SERS platform was adapted for the sensitive and specific detection of hyaluronic acid (HA), a key biomarker associated with inflammation and cancer progression. The system employs a sandwich immunoassay configuration, with substrates functionalized with antibodies to capture HA molecules and 4-MBA-labeled SERS tags for detection. This setup achieved an ultra-sensitive detection limit of 10⁻¹¹ g/mL for HA. Comprehensive characterization confirmed the uniformity and reproducibility of the SERS substrates, while validation in complex biological matrices demonstrated their robustness and reliability, highlighting their potential in cancer diagnostics and biomarker detection.