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The effective extraction of water-leaving reflectance using atmospheric correction (AC) algorithms is essential for accurately retrieving ocean color parameters. However, existing AC approaches designed for specific water types often struggle with the varying optical properties of open and coastal waters. This study proposes an efficient multi-layer stacking method for AC (MSM AC) that is suitable for both clear and turbid waters. The implementation and validation of the method were conducted using Himawari-8 imagery. To address the lack of training data, 10,000 Rayleigh-corrected reflectance samples were synthesized for six Himawari-8 bands, using simulated water-leaving, which cover different optically complex water properties through a radiative transfer, and aerosol reflectance data under different geometrical conditions. Following the principle of heterogeneous integration, various meta-learners were preselected for model training, and the preliminary model was fine-tuned using in situ data. A weighted integration strategy was then employed to develop an MSM AC tailored to Himawari-8 image data. For comparative analysis, a near-infrared–shortwave infrared AC method and a general machine learning AC method were also implemented. Model evaluation and validation were performed using a test subset of simulated data and in-situ datasets. Validation results indicate that the MSM AC exhibits strong performance in the validation bands (470 nm, 510 nm, and 640 nm) on the in-situ dataset, with R2 values of 0.64, 0.91, and 0.82 and root-mean-square logarithmic deviation (RMSLD) values of 0.007 sr−1, 0.004 sr−1, and 0.005 sr−1, respectively. Additionally, water bodies with varying optical complexities were simulated by restructuring the ocean color component content in the simulated data. The correction performances of MSM and comparative algorithms were evaluated using the median absolute error (MedAE) between the predicted and simulated water-leaving reflectance data. The results demonstrate that the MSM AC exhibits strong adaptability to the optical characteristics of complex water bodies, achieving low MedAE values across all types of optically complex water bodies. Furthermore, the spatial mapping of MSM-corrected reflectance exhibits a high agreement with the MODIS and Himawari-8 Advanced Himawari Imagery water-leaving reflectance products, further confirming its superiority. In conclusion, the algorithm developed in this study enables consistent AC for both open and near-shore waters, offering an ideal solution for the AC of Himawari-8 satellite images.

Abstract The quest for mechanoluminescence (ML) in zinc sulfide (ZnS) spans more than a century, initially sparked by observations of natural minerals. There has been a resurgence in research into ML materials in recent decades, driven by advances in optoelectronic technologies and a deeper understanding of their luminescent properties under mechanical stress. ZnS, in particular, has garnered attention owing to its remarkable ability to sustain luminescence after more than 100,000 mechanical stimulations, positioning it as a standout candidate for optoelectronic applications. In contrast to conventional photoluminescent and electroluminescent light sources, ZnS composite elastomers have emerged as flexible, stretchable self‐powered light sources with considerable practical implications. This review introduces the development history, ML mechanisms, prototype ML devices, ZnS‐based ML material preparation methods, and their diverse applications spanning environmental mechanical‐to‐optical energy conversion, E‐signatures, anti‐counterfeiting, wearable information sensing devices, advanced battery‐free displays, biomedical imaging, and optical fiber sensors for human–computer interactions, among others. By integrating insights from ML‐optics, mechanics, and flexible optoelectronics, and by summarizing pertinent perspectives on current scientific challenges, application technology hurdles, and potential solutions for emerging scientific frontiers, this review aims to furnish fundamental guidance and conceptual frameworks for the design, advancement, and cutting‐edge application of novel mechanoluminescent materials.

Abstract Mechanoluminescence is a smart light‐emitting phenomenon in which applied mechanical energy is directly converted into photon emissions. In particular, mechanoluminescent materials have shown considerable potential for applications in the fields of energy and sensing. This study thoroughly investigates the mechanoluminescence and long afterglow properties of singly doped and codoped Sr2MgSi2O7(SMSO) with varying concentrations of Eu2+ and Dy3+ ions. Subsequently, a comprehensive analysis of its multimode luminescence properties, including photoluminescence, mechanoluminescence, long afterglow, and X‐ray‐induced luminescence, is conducted. In addition, the density of states mapping is acquired through first‐principles calculations, confirming that the enhanced mechanoluminescence properties of SMSO primarily stem from the deep trap introduced by Dy3+. In contrast to traditional mixing with Polydimethylsiloxane, in this study, the powders are incorporated into optically transparent wood to produce a multiresponse with mechanoluminescence, long afterglow, and X‐ray‐excited luminescence. This structure is achieved by pretreating natural wood, eliminating lignin, and subsequently modifying the wood to overall modification using various smart phosphors and epoxy resin composites. After natural drying, a multifunctional composite wood structure with diverse luminescence properties is obtained. Owing to its environmental friendliness, sustainability, self‐power, and cost‐effectiveness, this smart mechanoluminescence wood is anticipated to find extensive applications in construction materials and energy‐efficient displays.

The dynamic visualization of ocean dynamics data is essential for effectively presenting oceanic information data. However, with the increasing spatial resolution of ocean remote sensing data, performing global-scale visualization in a single pass has become challenging. Directly rendering ocean data with high spatial resolution can result in problems such as increased communication time, blocked resource loading, and page lag. To address this issue, this paper proposes a common ocean data standard based on the characteristics of massive ocean element data, constructs an efficient three-level LOD model for ocean dynamic field rendering, and achieves particle rendering of ocean dynamic data by converting ocean data into image slices to complete the rendering of high-volume ocean data on the Web side. Compared with traditional methods, the proposed method significantly improves rendering performance. The average window construction time (FT) is reduced to 51.77ms, enhancing the overall rendering speed by approximately 64%. Meanwhile, the average frames per second (FPS) increase to 57.45fps, augmenting rendering stability and smoothness by around 18%. The peak memory consumption of the highest resolution data used in this paper is about 90MB, which is only 1/4 of the original. The proposed method effectively compensates for the disadvantage of slow rendering of large-scale ocean data visualization in some systems, enabling fast rendering of dynamic ocean data on the Web.

Mechanoluminescence (ML) materials, which directly convert mechanical energy into light emission, have emerged as an emerging class of light-emitting materials with various applications. Although significant progress has been made in the development of new ML materials and devices, their practical application is limited by their low intensity and homogenously structured host structures. Thus, multiple-structured host ML materials with high ML intensity and reproducibility are needed, particularly for wearable and printable ML light sources with high brightness. In this study, various Mn-doped ternary heterojunction ML materials, CaZnOS-ZnS-SrZnOS, are synthesised by high-temperature solid-phase reactions, and their luminescence properties are systematically tested. The result indicates that the ternary heterojunction materials have a higher ML intensity over 60 times stronger than the state-of-art SrZnOS: Mn2+, which is currently the brightest sample we have obtained. ML linearly depends on the magnitude of the applied force. Based on the synthesised ternary ML heterojunctions, repetitive self-driving luminescence of the zipper is achieved for the first time through powder modification and inlay; the clothes composed of our prepared zippers are pulled and bent when worn on the body to emit bright visible light. Additionally, a Velcro that can achieve light emission is developed; it provides a new idea for the development of wearable flexible self-luminous devices in the future. Simultaneously, movement-driven stress luminous printable objects that can be printed on the surface of various commodities or their packaging are demonstrated. The preparation of self-driven, battery-free, and electrode-free stress luminescence wearable low light sources has an important application trend, which can avoid the interference of the circuit and improve the stability of the devices, thus promising a wide range of applications in smart wear, energy-saving displays, safety and rescue, robotic skin, and information security.

Abstract In recent years, flexible stress sensors capable of monitoring diverse body movements and physiological signals have been attracting great attention in the fields of healthcare systems, human–machine interfaces, and wearable electronics. Inspired by the structure of natural eggshell inner membrane (ESIM), we developed a pressure sensor based on MXene (Ti3C2Tx)/Ag NWs (silver nanowires) composite electrodes and the micro-structured dielectric layer to meet the application requirements of wide detection range and long-term stability for the sensors. In the light of the nanoscale-microarray of the dielectric layer and the rough surface of electrode materials, this pressure sensor is expected to allow great and persistent deformation during the loading process. As a result, the device is characterized by an improved sensitivity, fast response (in the millisecond range), wide detection range (0–600 kPa), and long-term stability. The outstanding performance of the proposed sensor makes it possible to detect various human activities, such as speaking, air blowing, clenching, walking, finger/knee/elbow bending, and striking, demonstrating its good application prospects in wearable and flexible electronic devices.