Surface Reflectance Research Articles

Steering the Site Distance of Atomic Cu‐Cu Pairs by First‐Shell Halogen Coordination Boosts CO2‐to‐C2 Selectivity

Electrocatalytic reduction of CO2 into C2 products of high economic value provides a promising strategy to realize resourceful CO2 utilization. Rational design and construct dual sites to realize the CO protonation and C‐C coupling to unravel their structure‐performance correlation is of great significance in catalysing electrochemical CO2 reduction reactions. Herein, Cu‐Cu dual sites with different site distance coordinated by halogen at the first‐shell are constructed and shows a higher intramolecular electron redispersion and coordination symmetry configurations. The long‐range Cu‐Cu (Cu‐I‐Cu) dual sites show an enhanced Faraday efficiency of C2 products, up to 74.1%, and excellent stability. In addition, the linear relationships that the long‐range Cu‐Cu dual site is accelerated to C2H4 generation and short‐range Cu‐Cu (Cu‐Cl‐Cu) dual site is beneficial for C2H5OH formation are disclosed. In situ electrochemical attenuated total reflection surface enhanced infrared absorption spectroscopy, in situ Raman and theoretical calculations manifest that long‐range Cu‐Cu dual sites can weaken reaction energy barriers of CO hydrogenation and C‐C coupling, as well as accelerating deoxygenation of *CH2CHO. This study uncovers the exploitation of site‐distance‐dependent electrochemical property to steer the CO2 reduction pathway, as well as a potential generic tactic to target C2 synthesis by constructing the desired Cu‐Cu dual sites.

Steering the Site Distance of Atomic Cu-Cu Pairs by First-Shell Halogen Coordination Boosts CO2-to-C2 Selectivity.

Electrocatalytic reduction of CO2 into C2 products of high economic value provides a promising strategy to realize resourceful CO2 utilization. Rational design and construct dual sites to realize the CO protonation and C-C coupling to unravel their structure-performance correlation is of great significance in catalysing electrochemical CO2 reduction reactions. Herein, Cu-Cu dual sites with different site distance coordinated by halogen at the first-shell are constructed and shows a higher intramolecular electron redispersion and coordination symmetry configurations. The long-range Cu-Cu (Cu-I-Cu) dual sites show an enhanced Faraday efficiency of C2 products, up to 74.1 %, and excellent stability. In addition, the linear relationships that the long-range Cu-Cu dual sites are accelerated to C2H4 generation and short-range Cu-Cu (Cu-Cl-Cu) dual sites are beneficial for C2H5OH formation are disclosed. In situ electrochemical attenuated total reflection surface enhanced infrared absorption spectroscopy, in situ Raman and theoretical calculations manifest that long-range Cu-Cu dual sites can weaken reaction energy barriers of CO hydrogenation and C-C coupling, as well as accelerating deoxygenation of *CH2CHO. This study uncovers the exploitation of site-distance-dependent electrochemical properties to steer the CO2 reduction pathway, as well as a potential generic tactic to target C2 synthesis by constructing the desired Cu-Cu dual sites.

A complete 3D-printed tool kit for Solid-State NMR sample and rotor handling

Solid state NMR (SSNMR) is a highly versatile and broadly applicable method for studying the structure and dynamics of biomolecules and materials. For scientists entering the field of SSNMR, the many quotidian activities required in the workflow to prepare samples for data collection can present a significant barrier to adoption. These steps include transfer of samples into rotors, marking the reflective surfaces for high sensitivity tachometer signal detection, inserting rotors into the magic-angle spinning (MAS) stator, achieving stable spinning, and removing and storing rotors to ensure reproducibility of data collection conditions. Even experienced spectroscopists experience occasional problems with these operations, and the cumulative probability of a delay to successful data collection is high enough to cause frequent disruptions to instrument schedules, particularly in the context of large facilities serving a diverse community of users. These problems are all amplified when utilizing rotors smaller than about 4 mm in diameter. Therefore, to improve the reliability and robustness of SSNMR sample preparation workflows, here we describe a set of tools for rotor packing, unpacking, tachometer marking, extraction and storage. Stereolithography 3D printing was employed as a cost-effective and convenient method for prototyping and manufacturing a full range of designs suitable for several types of probes and rotor geometries.

Global Landslide Finder: Detecting the Time and Place of Landslides with Dense Earth Observation Time Series

This paper presents a remote sensing approach for rapidly and automatically generating maps of surface disturbances caused by landslides on the global scale. Our approach not only identifies the locations of these disturbances but also pinpoints the estimated time of their occurrence. Using the Continuous Change Detection and Classification (CCDC) algorithm within the Google Earth Engine (GEE) platform, we analyzed two decades of Landsat 5, 7, and 8 surface reflectance data. We tested this approach in five landslide-prone regions: Iburi (Japan), Kashmir (Pakistan), Karnataka (India), Porgera (Papua New Guinea), and Pasang Lhamu (Nepal). The results were promising, with R2 values ranging up to 0.85, indicating a robust correlation between detected disturbances and actual landslide events compared to manually made inventories. The accuracy metrics further validated our method, with a producer’s accuracy of 75%, a user’s accuracy of 73%, and an F1 score of 75%. Furthermore, the method proved well transferable across different locations. These findings demonstrate the method’s potential as a valuable tool for near real-time and historical analysis of landslide activity, thereby contributing to global disaster management and mitigation efforts.

Room-temperature DBR-free VCSEL operation on an InGaN/GaN thin-film platform with a monolithic surface grating.

Vertical-cavity surface-emitting lasers (VCSELs) are pivotal in various applications ranging from data communication to sensing technologies. This study introduces a VCSEL design featuring a monolithic top surface high contrast grating (HCG) reflector on a thin-film substrate, aimed at improving lasing performance while reducing fabrication costs by omitting the use of distributed Bragg reflectors (DBRs). We fabricated the proposed VCSEL with the surface grating and characterized its performance through micro-photoluminescence measurements. The laser demonstrated room-temperature lasing at 436.2 nm with a Q factor of 4600 and a lasing threshold of 5.5 kW/cm2 under optical pumping. The implementation of the surface grating reflector was instrumental in facilitating vertical lasing, significantly improving surface reflectivity compared to conventional flat GaN/air interfaces. This innovative design holds significant promise for the development of cost-effective, DBR-free VCSELs, with potential applications extending to photonic integrated circuits and light detection and ranging (LiDAR) systems.

Retrieval of Aerosol and Surface Properties at High Spatial Resolution: Hybrid Approach and Demonstration Using Sentinel‐5p/TROPOMI and PRISMA

AbstractSatellite remote sensing of aerosol is largely conducted at moderate or coarse spatial resolution around 1–10 km. Nevertheless, at urban areas with high human activity, aerosol can originate from complex emission sources and may also vary strongly in space. Therefore, aerosol characterization at fine spatial resolution is essential for air quality study and assessment of anthropogenic pollution as well as climate effects. However, space‐borne instruments with high spatial resolution are usually limited in swath width or spectral coverage which result in lowering information content required for aerosol and surface retrieval. Based on the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm, we propose a hybrid approach by combining fine and coarse spatial resolution measurements to retrieve aerosol and surface properties simulataneously at fine spatial resolution. The instruments with coarse spatial resolution and high revisting time can provide advanced aerosol characterization. At the same time, the instruments with fine spatial resolution are sensitive to spatial variability of aerosol nearby sources. In this study, the GRASP/Hybrid approach is demonstrated and tested based on the European Space Agency Sentinel‐5p/TROPOMI together with the Italian Space Agency PRISMA satellite data. Specifically, the detailed aerosol microphysical properties from Sentinel‐5p/TROPOMI 10 km retrievals are used as a priori information for PRISMA to derive aerosol loading and surface properties at 100 meter (m) spatial resolution. The PRISMA 100 m aerosol and surface retrieval based on the developed GRASP/Hybrid approach are evaluated using available ground‐based and satellite measurements, including AERONET, VIIRS/DB aerosol and PRISMA Level 2 surface reflectance products.

Exploring the potential of multi-source satellite remote sensing in monitoring crop nutrient status: A multi-year case study of cranberries in Wisconsin, USA

A timing and precise diagnosis of crop nutrient status is essential for optimizing management practices that promote environmentally friendly and enhanced crop yields. Although plant tissue analysis has conventionally been employed to evaluate the nutritional status of crops, this method cannot capture the spatial variability of crop nutrients. In contrast, satellite-based remote sensing can monitor the nutrient status of crops across expansive areas. This study explored the capability of multi-source satellite images (PlanetScope-4: 3 m, 4 bands; PlanetScope-8: 3 m, 8 bands; Sentinel-2: 10–60 m, 13 bands; PRISMA: 30 m, 239 bands) in mapping 12 foliar nutrients in cranberries. Three machine learning approaches, including partial least squared regression (PLSR), support vector regression (SVR), random forest regression (RFR), were used to relate foliar nutrients to different types of satellite-derived features (SR: surface reflectance; VI: vegetation indices; TF: texture features) or their combinations (SR+VI, VI+TF and SR+VI+TF). Model performance was compared across different foliar nutrients, modelling approaches and combinations of model input features using R2 (the coefficient of determination) and RRMSE (relative root mean square error, = root mean square error/nutrient range × 100 %). Input features that were important to foliar nutrient modelling were identified. The model performance difference among nutrients was consistent between Planet-4 and Sentinel-2, as well as between Planet-8 and PRISMA. In the Planet-4 and Sentinel-2 derived models, N was best predicted (average R2 = 0.77, average RRMSE=15 %), followed by macronutrients S (0.60–0.63, 11 %), Mg (0.58–0.65, 10–11 %), Ca (0.49–0.51, 9 %), Na (0.69, 22 %), P (0.49, 9 %) and K (0.20, 8 %), and then by all micronutrients(i.e., Fe, Mn, B, Cu and Zn: R2 = 0.04–0.61; RRMSE=16–28 %). In the Planet-8 and PRISMA derived models, macronutrients (i.e., N, P, K, Mg, Ca, S and Na) had lower R2 and RRMSE (R2 = 0.06–0.59; RRMSE=7–57 %) than micronutrients (i.e., Fe, Mn, B, Cu and Zn: R2 = 0.18–0.60; RRMSE=19–66 %). The successful retrieval of foliar nutrients from satellite imagery was influenced by many factors, including the intercorrelation between nutrients and model input features, the data availability at critical growth stages, and satellite images characteristics (e.g., spatial and spectral resolutions). Except for foliar nitrogen, foliar nutrients typically do not exhibit distinct absorption features associated with C, H, N, or O molecular bonds in the 400–2500 nm range. Our results indicate that their successful retrieval can be primarily attributed to the association between foliar nutrients and other leaf components (e.g., pigments, water, and dry matter) that do display spectral features within this range. Our study demonstrated the potential of integrating multi-source satellite data for precise nutrient monitoring over large scales.

Toward Large‐Scale Riverine Phosphorus Estimation Using Remote Sensing and Machine Learning

AbstractPhosphorus pollution is a major water quality issue impacting the environment and human health. Traditional methods limit the frequency and extent of total phosphorus (TP) measurements across many rivers. However, remote sensing can accurately estimate riverine TP; nevertheless, no large‐scale assessment of riverine TP using remote sensing exists. Large‐scale models using remote sensing can provide a fast and consistent method for TP measurement, important for data generalization and accessing extensive spatial‐temporal change in TP. Our study uses remote sensing and machine learning to estimate the TP in rivers in the contiguous United States (CONUS). Initially, we developed a national scale matchup data set for Landsat detectable rivers (river width >30 m) using in situ TP and surface reflectance. We used in situ data from the Water Quality Portal (WQP), alongside water surface reflectance data from Landsat 5, 7, and 8 spanning from 1984 to 2021. Then, we used this data set to develop a machine learning (ML) model using different preprocessing methods and algorithms. We found that using high‐level vegetation in the clustering approach and over‐sampling or under‐sampling our training data in the sampling approach improved our model estimation accuracy. We compared XGBLinear, XGBTree, Regularized Random Forest (RRF), and K‐Nearest neighbors ML algorithms and selected XGBLinear as the best model with an R2 of 0.604, RMSE of 0.103 mg/L, mean average error of 0.83, and NSE of 0.602. Finally, we identified human footprint, elevation, river area, and soil erosion as the main attributes influencing the accuracy of estimated TP from the ML model.

Research on the outdoor thermal comfort of children in Hangzhou and Its influence on the underlying surface reflectance.

The outdoor thermal comfort (OTC) of children is more specific than that of adults, and the complex influence of outdoor activity spaces on children's thermal comfort warrants further investigation. To investigate the outdoor thermal comfort baseline (OTCB) of children in Hangzhou and explore the thermal impact of outdoor surfaces on children, a survey was conducted in six typical outdoor activity spaces in Hangzhou, China, during spring and summer utilizing physical measurements, questionnaire surveys, and the universal thermal climate index (UTCI). This study analyzed the differences in thermal perception among children in Hangzhou in different seasons, their OTCB, and the impact of surface reflectance (Rs) on children's OTC. The results indicated the following: 1) In spring, children in Hangzhou generally felt comfortable, but their discomfort with heat noticeably increased in summer. 2) The neutral UTCIs (NUTCIs) for Hangzhou children were 11.6°C (spring) and 27.7°C (summer), and the NUTCI ranges (NUTCIRs) were 9.7-17.5°C (spring) and 25.7-30.0°C (summer); additionally, the thermal acceptability ranges (TARs) were 13.2-25.2°C (spring) and 11.8-34.8°C (summer). 3) A high Rs made children feel more uncomfortable with heat, which was primarily due to the space's total shortwave and longwave radiation, which peaked between 14:00 and 15:00. 4) Based on the research findings, corresponding bioclimatic design strategies were proposed. Recommendations include using high Rs underlays with shading, composite underlays, or the future adoption of thermochromic coatings. Keeping permeable underlays moist is essential for activating their cooling mechanisms. Fundamental safety measures are imperative. This study provides valuable data for urban planners and landscape designers to create public spaces suitable for children's outdoor activities, contributing to a harmonious and unified living environment.

Physics-Based Efficient Full Projector Compensation Using Only Natural Images.

Achieving practical full projector compensation requires the projection display to adapt quickly to textured projection surfaces and unexpected movements without interrupting the display procedure. A possible solution to achieve this involves using a projector and an RGB camera and correcting both color and geometry by directly capturing and analyzing the projected natural image content, without the need for additional patterns. In this study, we approach full projector compensation as a numerical optimization problem and present a physics-based framework that can handle both geometric calibration and radiometric compensation for a Projector-camera system (Procams), using only a few sampling natural images. Within the framework, we decouple and estimate the Procams' factors, such as the response function of the projector, the correspondence between the projector and camera, and the reflectance of projection surfaces. This approach provides an interpretable and flexible solution to adapt to the changes in geometry and reflectance caused by movements. Benefitting from the physics-based scheme, our method guarantees both accurate color calculation and efficient movement and reflectance estimation. Our experimental results demonstrate that our method surpasses other state-of-the-art end-to-end full projector compensation methods, with superior image quality, reduced computational time, lower memory consumption, greater geometric accuracy, and a more compact network architecture.

Cooling air flow field in the primary mirror temperature control system of a solar telescope

The temperature distribution and the difference with the ambient temperature of the primary mirror are crucial factors affecting the observational quality of the solar telescope. We designed a flow field structure of the primary mirror temperature control system based on the 2.5-meter Wide-field and High-resolution Solar Telescope(WeHoT), analyzed the flow conditions and heat transfer capacity of the overall flow field, and then carried out five stages of optimization iteration and simulation guided by the analysis results. A flow field structure for the primary mirror temperature control system with high efficiency and high uniformity is summarized. The simulation results for the final solution indicate an average surface temperature of the primary mirror at 20.064°C, with a maximum temperature difference within the reflective surface of 0.809°C, and a reduced difference with the ambient temperature of 0.411°C. Surface thermal deformation is less than 0.2 μm, with an RMS value of 18.05 nm, achieving the ideal state. This work can provide a theoretical foundation and valuable insights for future research on the temperature control system of the primary mirror in large-aperture solar telescopes.

Phase shifter intelligent reflective surface design for 2.4 GHz

In this study, an intelligent reflective surface (IRS) design consisting of a 3x4 patch surface that intentionally changes the phase angles of incoming signals for the 2.4 GHz operating frequency is presented. In the design of this IRS, FR-4 is chosen as the dielectric material, and copper is used to create both the reflecting elements and the ground plane. Phase shifting characteristic is achieved by using varactor diodes on the designed two-dimensional surface. In order to test the behaviour of the IRS, a horn antenna is also designed to be used as a source with the ANSYS HFSS (v21) program. The obtained results are presented in terms of return loss and gain values of the IRS. The results of the simulations reveal that the phase angles of the incoming signals can be adjusted as expected by changing the capacity values of the varactor diodes modelled by their equivalent circuits on the IRS.

A High-Gain Millimeter-Wave Fabry–Perot Cavity Antenna With Phase Correction on a Meta-Ground Reflective Surface

A High-Gain Millimeter-Wave Fabry–Perot Cavity Antenna With Phase Correction on a Meta-Ground Reflective Surface

Intelligent Reflecting Surface Aided MIMO With Cascaded LoS Links: Joint Beamforming and Array Orientation Optimization

Intelligent Reflecting Surface Aided MIMO With Cascaded LoS Links: Joint Beamforming and Array Orientation Optimization

Intelligent Reflective Surface Resource Allocation Algorithm Based on Deep Reinforcement Learning in Internet of Vehicles System

Intelligent Reflective Surface Resource Allocation Algorithm Based on Deep Reinforcement Learning in Internet of Vehicles System

Anti-Jamming Precoding Against Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks

Anti-Jamming Precoding Against Disco Intelligent Reflecting Surfaces Based Fully-Passive Jamming Attacks

Analysis of CeO2/SiO2 double-layer thin film stack with antireflection effect for silicon solar cells

This study introduces CeO2/SiO2 double-layer film stacks and its antireflection coating effect. Optical properties were analyzed by spectrophotometer measurements; surface morphology and cross-sections were observed by Scanning Electron Microscopy (SEM); elemental distributions and crystallographic properties were determined by Energy Dispersive Spectroscopy (EDS) and X-ray Diffraction (XRD) measurements. Average reflectance of single-layer 0.3MSiO2, 0.6MSiO2, and 0.3MCeO2 thin films were 30.54%, 20.12%, and 14.23%, respectively. Average reflectance was decreased significantly down to 5.9% by 0.3MCeO2/0.6MSiO2 double-layer thin films comparing to those of the results of single-layer films and bare silicon surface reflection (~40%). Antireflective effect of the films on solar cells was estimated by simulation using the measured reflection data. Simulated solar cells indicate that 0.3MCeO2/0.6MSiO2 double-layer antireflective coatings are capable to increase the efficiency significantly and conversion efficiency of 21.7% could be achieved.

A Stable-Gain Millimeter-Wave Fabry-Perot Antenna Based on Circular Polarizer-Integrated PRS with Positive Reflective Phase Gradient

In this paper, we present a millimeter-wave Fabry-Perot antenna with dual resonances, circular polarization, and stable gain. To achieve circularly polarized radiation, we integrate a receiver-transmitter circular polarizer into the partially reflective surface (PRS) of the antenna. The PRS is specifically designed with a positive reflective phase gradient, which contributes to a stable gain in the dual-resonance frequency band. For the radiation source, we adopt a linearly-polarized substrate-integrated waveguide cavity-backed slot fed by a printed ridge gap waveguide. Experimental measurements conducted on a fabricated prototype of the proposed antenna demonstrate its impedance and axial ratio bandwidths of 28.6–30.0 GHz and 28.6–29.6 GHz, respectively. Furthermore, the antenna exhibits a peak gain of 12.1 dBi and a gain fluctuation lower than 0.6 dB within the operational frequency band.

A Low-Complexity Solution for Optimizing Binary Intelligent Reflecting Surfaces towards Wireless Communication

Intelligent Reflecting Surfaces (IRSs) enable us to have a reconfigurable reflecting surface that can efficiently deflect the transmitted signal toward the receiver. The initial step in the IRS usually involves estimating the channel between a fixed transmitter and a stationary receiver. After estimating the channel, the problem of finding the most optimal IRS configuration is non-convex, and involves a huge search in the solution space. In this work, we propose a novel and customized technique which efficiently estimates the channel and configures the IRS with fixed transmit power, restricting the IRS coefficients to {1,−1}. The results from our approach are numerically compared with existing optimization techniques.The key features of the linear system model under consideration include a Reconfigurable Intelligent Surface (RIS) setup consisting of 4096 RIS elements arranged in a 64 × 64 element array; the distance from RIS to the access point measures 107 m. NLOS users are located around 40 m away from the RIS element and 100 m from the access point. The estimated variance of noise NC is 3.1614 × 10−20. The proposed algorithm provides an overall data rate of 126.89 (MBits/s) for Line of Sight and 66.093 (MBits/s) for Non Line of Sight (NLOS) wireless communication.

SPATIAL TEMPORAL ANALYSIS OF LAND SURFACE TEMPERATURE CHANGES IN AMBON ISLAND FROM LANDSAT 8 IMAGE DATA USING GEOGLE EARTH ENGINE

This study aims to analyze land surface temperature changes on Ambon Island using Landsat 8 imagery data and Google Earth Engine. The research method involves the use of Ambon Island boundary data from the Geospatial Information Agency (BIG) as well as Landsat 8 Collection 2 Tier 1 and Real-Time satellite image data that have been calibrated to reflect the reflectance of the Earth's surface to the atmosphere. The analysis steps include temperature conversion from Kelvin to Celsius, land surface temperature classification, and data export to Arc GIS software. The results showed an increase in land surface temperature associated with urban development in Ambon City, highlighting the importance of sustainable urban planning and good resource management to mitigate the negative impacts of land surface temperature increase and support adaptation to climate change. Keywords: Ambon Island, Geogle Earth Engine, Land Surface Temperature