Solar Illumination Conditions Research Articles

MXene@polydopamine/oxidized sodium alginate modified collagen composite aerogel as sustainable bio-adsorbent for heavy metal ion adsorption and solar driven water evaporation

The design of an environmentally friendly bio-adsorbent for the removal of heavy metal ions from aqueous media is a sustainable strategy to ensure water safety. Herein, a three-dimensional macroscopic aerogel with photothermal conversion and heavy metal wastewater treatment capability was designed using leather collagen, MXene@polydopamine and oxidized sodium alginate as raw materials, named as MPAC composite aerogel. The applicability of the developed MPAC composite aerogel in water evaporation and heavy metal wastewater treatment was studied. MPAC composite aerogel had good Cr(VI) adsorption capacity. This article focused on the study of adsorption kinetics, isotherms and thermodynamics. The adsorption equilibrium time of MPAC composite aerogel was 60 min, and the equilibrium adsorption capacity of MPAC composite aerogel for Cr(VI) reached 80.73, 100.80 and 112.86 mg/g when the initial Cr(VI) concentration was 30, 70 and 100 mg/L, respectively. The adsorption process of Cr(VI) by MPAC composite aerogel conformed to the two-level dynamics model and the Freundlich adsorption isotherm model, and was a spontaneous endothermic reaction. Additionally, the composite aerogel had good solar-driven water evaporation ability and could enhance the water evaporation rate of Cr(VI) solution. Furthermore, the MPAC composite aerogel had high adsorption performance for Cr(VI) under solar illumination conditions. This new aerogel has the advantages of low cost, environmental friendliness, strong adsorption capacity and photothermal conversion performance and is a promising heavy metal ion adsorbent.

Seasonal optimisation of drone‐based photogrammetry in a heterogeneous boreal landscape

AbstractAimsUncrewed aerial vehicles (UAV), or drones, have become more affordable and easier to use, resulting in increased UAV applications in ecology and conservation. However, solar illumination, vegetation phenology and prevailing weather conditions will impact the quality of the derived products to differing degrees. In this study, we investigate how seasonal differences in solar illumination, tree foliage and weather conditions impact the accuracy of digital elevation models (DEM) and canopy height models (CHM) in a heterogeneous boreal landscape.MethodsWe compared DEMs and CHMs derived from drone photogrammetry with DEMs and CHMs produced from a drone‐mounted laser scanner across three seasons with different solar illumination, tree foliage and weather conditions during leaf‐off and leaf‐on seasons. Photogrammetric height models were evaluated across three land‐cover classes consisting of open areas, sparse‐forest and forest. The most accurate CHM for sparse‐forest was produced during summer under overcast conditions, whereas for the forest class, summer under clear skies was best.ResultsStructure from motion (SfM) photogrammetry performed well against the LiDAR survey in most cases with correlations between sampled points of up to R2 = 0.995. Root mean square errors (RMSEs) were <1.5 m in all DEMs and as low as 0.31 m in autumn clear‐sky data over open terrain. CHM RMSEs were somewhat higher in all cases except under winter overcast conditions when the RMSE for sparse‐forest reached 6.03 m.ConclusionsWe have shown that SfM photogrammetry is surprisingly robust to variations in vegetation type, tree phenology and weather, and performs well in comparison with a reference LiDAR data set. Our results show that, in boreal forests, autumn is the preferred season under clear‐sky conditions for DEM generation from SfM photogrammetry across all land‐cover classes, whereas summer is preferred for CHM modelling with a small trade‐off between overcast and clear‐sky conditions over different vegetation types. These results can help potential SfM users in ecology and forestry plan missions and review the quality of products derived from drone photogrammetry products.

A new snow cover mapping algorithm for Chinese geostationary meteorological satellite FY-4A AGRI data

ABSTRACT China’s second generation of geostationary meteorological satellites Fengyun-4 (FY-4) are equipped with the Advanced Geosynchronous Radiation Imager (AGRI) which has the advantages of large number of spectral bands and high temporal resolution. To fully leverage these features, a new snow cover (SC) mapping algorithm was proposed, which firstly derives SC map from a single scene image and then combines multi-temporal SC results within one day into a daily SC composite. The novelty of the proposed algorithm includes the utilization of small spatial and temporal divisions to avoid the use of complex kernel-driven models for the correction of bidirectional effects of surface reflectance and a novel framework to merge multi-temporal SC maps by weighting the solar illumination conditions. The SC results were validated against in-situ snow depth measurements, Landsat 8 derived SC data and MODIS SC products. Results indicate that merging multi-temporal SC data can reduce cloud obscuration with the average daily cloud coverage percentage decreasing from about 47.03% for single scene to 35.62% for merged one and slightly improve snow detection accuracy. The overall accuracy (OA) ranges from 95.00% to 96.19%, and the F-score (FS) varies from 77.78% to 87.14% when compared to different reference data, suggesting an overall good performance.

Validation of cloud mask product from multi-channel satellite INSAT-3DR

The Indian National Satellite-3DR (INSAT-3DR) provides half-hourly multispectral images over the Indian region from a geostationary position. It observes diurnal variations highly relevant for variety of application areas, including weather forecasting. This work assesses the performance of the cloud mask product of INSAT-3DR new algorithm developed by Indian Space Research Organization (ISRO) by comparison with Moderate Resolution Imaging Spectrometer radiometer (MODIS) cloud mask data for the months from July 2019 to July 2020. The cloud detection algorithm employs nine different tests, considering solar illumination, satellite angle and surface type conditions to get pixel-resolution cloud mask. Our validation results indicate that the probability of detection (POD) of cloudy (clear) sky is 86 % (82 %) with 83 % hit rate for INSAT-3DR cloud mask, using MODIS cloud mask as a reference. When the INSAT-3DR cloud mask algorithm is also implemented on similar channels of MODIS, the POD of cloudy (clear) sky is 76 % (74 %) with 85 % hit rate. Our findings indicate the reliability of the INSAT-3DR cloud mask retrieved product for research and other applications. This is one of the important parameter of satellite derived products, which plays major role in daily operational weather forecasting.

Speckle Noise Reduction via Linewidth Broadening for Planetary Laser Reflectance Spectrometers

The low obliquity of the Moon leads to challenging solar illumination conditions at the poles, especially for passive reflectance measurements aimed at determining the presence and extent of surface volatiles. A nascent alternate method is to use active laser illumination sources in either a multispectral or hyperspectral design. With a laser spectral source, however, the achievable reflectance precision may be limited by speckle noise resulting from the interference effects of a coherent beam interacting with a rough surface. Here, we have experimentally tested the use of laser linewidth broadening to reduce speckle noise and, thus, increase reflectance precision. We performed a series of speckle imaging tests with near-infrared laser sources of varying coherence, compared them to both theory and speckle pattern simulations, and measured the reflectance precision using calibrated targets. By increasing the laser linewidth, we observed a reduction in speckle contrast and the corresponding increase in reflectance precision, which was 80% of the theoretical improvement. Finally, we discuss methods of laser linewidth broadening and spectral resolution requirements for planetary laser reflectance spectrometers.

Study on the variation characteristics of ionospheric F2 layer in Qinghai-Tibet plateau and surrounding areas

The Qinghai-Tibet Plateau (QTP) region is the largest plateau in China and the highest altitude in the world, with a unique geographical environment. Based on the observation data of the 24th solar cycle from six sites on the QTP and its surrounding areas, the multi-station joint detection method is adopted to analyze the temporal variation and spatial distribution characteristics of the critical frequency of the F2 layer(foF2) and the bottom height of the F2 layer (h'F2). The results indicate that the critical frequency of the ionospheric F layer in the QTP is controlled by solar illumination conditions, and conforms to the ionospheric variation law of middle and low latitudes. The height of the F layer has significant regional characteristics, and the F layer height variation in Kunming and Chongqing is particularly drastic, and the average height of the F layer in Chongqing is significantly higher than that in Kunming, which is at a lower latitude, and Lhasa, which is at the same latitude as Chongqing. This phenomenon may be attributed to the unique geographical environment of the QTP, which has an influential effect on the motion of the lower atmosphere, and through the coupling mechanism between the lower and upper atmosphere, has a substantial impact on the F2 layer. The research findings of this article are of great interest to the study of the coupling mechanism between the upper and lower atmosphere.

Recovery policies for safe exploration of lunar permanently shadowed regions by a solar-powered rover

The success of a multi-kilometre drive by a solar-powered rover at the lunar south pole depends upon careful planning in space and time due to highly dynamic solar illumination conditions. An additional challenge is that the rover may be subject to random faults that can temporarily delay long-range traverses. The majority of existing global spatiotemporal planners assume a deterministic rover-environment model and do not account for random faults. In this paper, we consider a random fault profile with a known, average spatial fault rate. We introduce a methodology to compute recovery policies that maximize the probability of survival of a solar-powered rover from different start states. A recovery policy defines a set of recourse actions to reach a safe location with sufficient battery energy remaining, given the local solar illumination conditions. We solve a stochastic reach-avoid problem using dynamic programming to find an optimal recovery policy. Our focus, in part, is on the implications of state space discretization, which is required in practical implementations. We propose a modified dynamic programming algorithm that conservatively accounts for approximation errors. To demonstrate the benefits of our approach, we compare against existing methods in scenarios where a solar-powered rover seeks to safely exit from permanently shadowed regions in the Cabeus area at the lunar south pole. We also highlight the relevance of our methodology for mission formulation and trade safety analysis by comparing different rover mobility models in simulated recovery drives from the LCROSS impact region.

Application of a temporal decorrelation model using Sentinel-1 SAR data to Detect volcanic ash deposits related to the 2020 Taal volcano eruption

Volcanic ash deposits affect buildings, vegetation, and population. After a volcanic eruption, it is critical to detect the areas affected by ash deposits to achieve an advisable management of the emergency. Optical sensors have been widely used to carry out this task, but they are limited by solar illumination and weather conditions. As an alternative, Synthetic Aperture Radar (SAR) data are not affected by those limitations. Recently, a Temporal Decorrelation Model (TDM) that uses SAR data was proposed for detecting and mapping ash deposits, but it has only been applied to L-band data. Today there is available a huge quantity of C-band data acquired by the Sentinel-1 constellation. In this study we applied the TDM to Sentinel-1 data in order to assess its performance for detecting volcanic ash deposits after an eruption. We selected the eruption of Taal volcano in The Philippines on January 12, 2020, as our case study. We computed more than 4000 interferometric pairs from a dataset of 93 images acquired before, during, and after the eruption. Our results show that TDM can be applied to C-band data, despite the higher temporal decorrelation suffered by them. Our final probability map is consistent with the field evidence reported by the Philippines Institute of Volcanology and Seismology (PHILVOLCS) and the isopachs map reported in the literature. This new application provides a novel framework for the coherence exploitation of C-Band data. Also, this approach could be applied to detection and monitoring of other natural disasters.

Enhancing Photovoltaic Performance and Stability of Perovskite Solar Cells through Single-Source Evaporation and CsPbBr3 Quantum Dots Incorporation

This study investigates the potential of inorganic perovskite CsPbBr3 as a photovoltaic material, highlighting its superior stability compared to that of organic–inorganic hybrid perovskite materials. Conventional methods for preparing CsPbBr3 perovskite films, such as the two-step method and the dual-source thermal evaporation method, face challenges in obtaining high-purity films due to the decomposition of precursor films and the formation of multiple heterogeneous phases. To address this issue, we synthesized CsPbBr3 powder material using thermal evaporation deposition, which effectively suppressed decomposition and the formation of heterogeneous phases. Consequently, we achieved uniform and dense CsPbBr3 perovskite films. By incorporating energy-band engineering modification with CsPbBr3 quantum dots (QDs), the all-inorganic perovskite solar cells (PSCs) attained a power conversion efficiency (PCE) of 7.01% under standard solar illumination conditions. The device PCE remained at 93% of its initial efficiency under 30% relative humidity conditions for over 100 days, showcasing its durability. The developed method produced an average grain size of 800 nm, resulting in a smooth and uniform film surface, thereby demonstrating the method’s high repeatability. Additionally, the optimized PSCs exhibited a high open-circuit voltage (VOC) with the champion device reaching a VOC of 1.38 V and a PCE of 7.01%. This research presents a robust, efficient, and cost-effective approach for fabricating high-quality all-inorganic PSCs.

An Adaptive Method for the Estimation of Snow-Covered Fraction with Error Propagation for Applications from Local to Global Scales

Snow can cover over 50% of the landmass in the Northern Hemisphere and has been labelled as an Essential Climate Variable by the World Meteorological Organisation. Currently, continental and global snow cover extent is primarily monitored by optical satellite sensors. There are, however, no large-scale demonstrations for methods that (1) use all the spectral information that is measured by the satellite sensor, (2) estimate fractional snow and (3) provide a pixel-wise quantitative uncertainty estimate. This paper proposes a locally adaptive method for estimating the snow-covered fraction (SCF) per pixel from all the spectral reflective bands available at spaceborne sensors. In addition, a comprehensive procedure for root-mean-square error (RMSE) estimation through error propagation is given. The method adapts the SCF estimates for shaded areas from variable solar illumination conditions and accounts for different snow-free and snow-covered surfaces. To test and evaluate the algorithm, SCF maps were generated from Sentinel-2 MSI and Landsat 8 OLI data covering various mountain regions around the world. Subsequently, the SCF maps were validated with coincidentally acquired very-high-resolution satellite data from WorldView-2/3. This validation revealed a bias of 0.2% and an RMSE of 14.3%. The proposed method was additionally tested with Sentinel-3 SLSTR/OLCI, Suomi NPP VIIRS and Terra MODIS data. The SCF estimations from these satellite data are consistent (bias less than 2.2% SCF) despite their different spatial resolutions.

Probing the Genuine Carrier Dynamics of Semiconducting Perovskites under Sunlight.

Understanding the nature of photogenerated carriers and their subsequent dynamics in semiconducting perovskites is important for the development of solar cell materials and devices. However, most ultrafast dynamic measurements on perovskite materials were conducted under high carrier densities, which likely obscures the genuine dynamics under low carrier densities in solar illumination conditions. In this study, we presented a detailed experimental study of the carrier density-dependent dynamics in hybrid lead iodide perovskites from femtosecond to microsecond using a highly sensitive transient absorption (TA) spectrometer. From the dynamic curves with low carrier density in the linear response range, we observed two fast trapping processes that occurred in less than 1 ps and tens of picoseconds, attributed to the shallow traps, and two slow decays with lifetimes of hundreds of nanoseconds and longer than 1 μs, related to the trap-assisted recombination and trapping at deep traps. Further TA measurements clearly show that PbCl2 passivation can effectively reduce both shallow and deep trap densities. These results provide insights into the intrinsic photophysics of semiconducting perovskites with direct implications for photovoltaic and optoelectronic applications under sunlight.

Magnetic field modulation of photocurrent in BiFeO<sub>3</sub> film

BiFeO<sub>3</sub> (BFO) is a kind of room temperature multiferroic material with bulk photovoltaic effect, and it has been a research hotspot in the field of multifunctional materials in recent years. The coexistence of the coupling among magnetic, optical, electrical properties brings rich and complex physical connotations. In this work, BiFeO<sub>3</sub> thin film is deposited on FTO substrate by pulsed laser deposition, and the solar cell structure with BiFeO<sub>3</sub> film used as light absorption layer and Au film serving as electrode is constructed. X-ray diffraction and Raman spectra indicate that the BFO film grown on FTO substrate has a pure phase structure. The experimental results of physical properties indicate that the BFO film possesses good ferromagnetic and ferroelectric properties and obvious photoelectric effect. According to the hysteresis loop, the remanence (<i>M</i><sub>r</sub>) of the sample is 0.8 emu/cm<sup>3</sup>, and the coercivity (<i>H</i><sub>c</sub>) is 200 Oe at 300 K. In terms of ferroelectricity, the saturation polarization intensity of the sample can reach 0.997 μC/cm<sup>2</sup>, the residual polarization intensity is 0.337 μC/cm<sup>2</sup>, and the coercive electric field is 12.45 kV/cm. The above results show that the BFO film has good multiferroic properties. Under solar illumination conditions, the photocurrent density up to 208 mA/cm<sup>2</sup> is obtained when a bias voltage 1 V is applied. More importantly, magneto-photocurrent (MPC) effect is found in the BFO film. No matter whether the magnetic field starts to increase from the positive direction or the negative direction, the MPC usually changes with the magnitude of magnetization. When a 1.3 kOe magnetic field is applied, the magneto-photocurrent change rate up to 232.7% is observed under standard solar illumination condition. The results show that the photocurrent of BFO films is greatly improved by a positive magnetic field and negative magnetic field. This magneto-photocurrent effect in BFO thin film comes from the photo-magnetoresistance effect, that is, the photogenerated electrons become spin photoelectrons under the action of an external magnetic field and receive spin-dependent scattering during moving in the conductive band of the material, thus producing the photo-magnetoresistance effect. In addition, the magneto-photocurrent effect is further enhanced by weakening the domain wall scattering of the spin electrons by the magnetic field. This work provides a reference for the modulation effect of magnetic field and light field on the magnetic, optical and electrical properties in multiferroics, and presents a foundation for the research and application of devices in the field of multifunctional optoelectronic materials.

Boosting Photoelectrochemical Ethanol Evolution on Reduced Graphene Oxide Functionalized Photocathode

AbstractHerein, a reduced graphene oxide (rGO) functionalized photocathode is studied for selective production of solar liquid fuels depending on dark and solar light illumination condition. rGO functionalized photocathode with p–n junction at the core–shell interface of ZnO@ZnTe is prepared with a three‐step synthetic process. Preparation of ZnO nanorod, formation of ZnTe on ZnO nanorod by anion‐exchange and then, finally, rGO layers are functionalized on the surface of ZnO@ZnTe photocathode. The photoelectrochemical (PEC) system of BiVO4∥KHCO3∥ZnO@ZnTe@rGO combination is introduced for selective solar liquid fuel production by CO2 reduction reaction (CO2RR). Functionalization of rGO layers on photocathode enables the multi‐electron shuttling function for the enhanced charge transfer efficiency due to its large charge capacitance, which results in producing liquid fuels such as HCHO and EtOH selectively as solar liquid fuels. These results in this work clearly demonstrate a possibility of solar liquid fuel product selectivity by PEC CO2RR.

Effect of Ag-Decorated BiVO4 on Photoelectrochemical Water Splitting: An X-ray Absorption Spectroscopic Investigation.

Bismuth vanadate (BiVO4) has attracted substantial attention on account of its usefulness in producing hydrogen by photoelectrochemical (PEC) water splitting. The exploitation of BiVO4 for this purpose is yet limited by severe charge recombination in the bulk of BiVO4, which is caused by the short diffusion length of the photoexcited charge carriers and inefficient charge separation. Enormous effort has been made to improve the photocurrent density and solar-to-hydrogen conversion efficiency of BiVO4. This study demonstrates that modulating the composition of the electrode and the electronic configuration of BiVO4 by decoration with silver nanoparticles (Ag NPs) is effective in not only enhancing the charge carrier concentration but also suppressing charge recombination in the solar water splitting process. Decoration with a small number of Ag NPs significantly enhances the photocurrent density of BiVO4 to an extent that increases with the concentration of the Ag NPs. At 0.5% Ag NPs, the photocurrent density approaches 4.1 mA cm−2 at 1.23 V versus a reversible hydrogen electrode (RHE) under solar simulated light illumination; this value is much higher than the 2.3 mA cm−2 of pure BiVO4 under the same conditions. X-ray absorption spectroscopy (XAS) is utilized to investigate the electronic structure of pure BiVO4 and its modification by decoration with Ag NPs. Analytical results indicate that increased distortion of the VO4 tetrahedra alters the V 3d–O 2p hybridized states. Additionally, as the Ag concentration increases, the oxygen vacancy defects that act as recombination centers in BiVO4 are reduced. In situ XAS, which is conducted under dark and solar illumination conditions, reveals that the significantly enhanced PEC performance is attributable to the synergy of modulated atomic/electronic structures and the localized surface plasmon resonance effect of the Ag nanoparticles.

ProbSevere LightningCast: A Deep-Learning Model for Satellite-Based Lightning Nowcasting

Abstract Lightning strikes pose a hazard to human life and property, and can be difficult to forecast in a timely manner. In this study, a satellite-based machine learning model was developed to provide objective, short-term, location-specific probabilistic guidance for next-hour lightning activity. Using a convolutional neural network architecture designed for semantic segmentation, the model was trained using GOES-16 visible, shortwave infrared, and longwave infrared bands from the Advanced Baseline Imager (ABI). Next-hour GOES-16 Geostationary Lightning Mapper data were used as the truth or target data. The model, known as LightningCast, was trained over the GOES-16 ABI contiguous United States (CONUS) domain. However, the model is shown to generalize to GOES-16 full disk regions that are outside of the CONUS. LightningCast provides predictions for developing and advecting storms, regardless of solar illumination and meteorological conditions. LightningCast, which frequently provides 20 min or more of lead time to new lightning activity, learned salient features consistent with the scientific understanding of the relationships between lightning and satellite imagery interpretation. We also demonstrate that despite being trained on data from a single geostationary satellite domain (GOES-East), the model can be applied to other satellites (e.g., GOES-West) with comparable specifications and without substantial degradation in performance. LightningCast objectively transforms large volumes of satellite imagery into objective, actionable information. Potential application areas are also highlighted. Significance Statement The outcome of this research is a model that spatially forecasts lightning occurrence in a 0–60-min time window, using only images of clouds from the GOES-R Advanced Baseline Imager. This model has the potential to provide early alerts for developing and approaching hazardous conditions.

Mapping snow cover in forests using optical remote sensing, machine learning and time-lapse photography

The accurate spatial information of snow cover is useful for understanding the impact of global warming, and it is of high significance for hydrological disaster prediction, water resources management, and climate change research. The Normalized Difference Snow Index (NDSI) based approach has been used extensively around the world for mapping snow, and they displayed high accuracy in open areas. However, capturing snow cover in forests remains problematic due to the obstruction effects of the forest canopy, which causes the snow cover area to be seriously underestimated. In this paper, we present a new algorithm based on machine learning (ML) technology to improve the accuracy of binary snow cover (BSC) mapping in forests, using the remotely sensed surface reflectance and ground truth data. A time-lapse photography network with a two-hour resolution was established in the eastern Qilian Mountains in northwestern China to obtain the ground truth data both in forests and open areas. We trained Random Forests (RF) with the 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data from bands 1–7 to generate BSC results (RF-BSC). Then we evaluated RF-BSC and the NDSI-derived BSC maps with three different NDSI thresholds (i.e., 0.10, 0.29, and 0.40) against ground-truth data. The results indicate that the proposed algorithm has a high performance in forest BSC mapping in this area, compared to the NDSI-threshold approach. The RF-BSC can retrieve 67% of all real forest snow pixels, while the NDSI-based BSC can only detect 8–14%. We also find that the performance of the algorithm seems to be sensitive to changes in solar illumination conditions and forest coverage. This study suggests that machine learning with the fusion of optical remote sensing and ground-based observations is an effective approach for improving the accuracy of forest snow cover mapping at regional scales.

A highly transparent and photothermal composite coating for effective anti-/de-icing of glass surfaces.

Anti-/de-icing of glass surfaces is of great importance in present daily life. The long-standing challenge in this field is largely due to the lack of stable multifunctional coatings that can be conveniently and economically constructed on the glass surface, and more importantly, are capable of retaining the original transparency of glass ranging from the visible to the near infrared spectrum. Herein, a direct spraying sol method on the glass surface to prepare a highly transparent and photothermal composite coating is reported. Such multifunctional coating of Cu7S4 nanoparticles/organo-silicone sols has displayed a good photothermal conversion property and hydrophobic property and therefore yields excellent anti-icing and self-melting ice properties. The condensation time of water droplets can be extended to 86 s even at −10 °C, which is 3.42 times delayed relative to ordinary blank glass. And the adhesion strength of ice is largely reduced to 72 KPa, which is as low as ∼1/3 that of ordinary glass. Meanwhile, the subcooling of adhering droplets is reduced to −12 °C under one solar illumination condition and exhibits a rapid de-icing capability. More impressively, the prepared functional coating glass shows an outstanding transmittance of more than 75% in the visible region, while it is over the minimum glass transmittance limit allowed by Safety Standards for Glass (GB9656-2016, China). In addition, the multifunctional photothermal glass coating exhibits good physical/chemical stability, which facilitates the long-term application of the coating in different environments.

The Regular Features Recorded by the Langmuir Probe Onboard the Low Earth Polar Orbit Satellite CSES

AbstractThis paper presents two kinds of regular features revealed from the observations of the Langmuir probe (LAP) onboard the low‐earth polar orbit satellite ‐ China Seismo‐Electromagnetic Satellite (CSES). The first feature behaves as a sudden drop (SD) in the plasma potential (Vp) and floating potential (Vf) data, while the second one appears as a spike (SP) in the dayside Vp and Vf data. The SD structure occurs at geo‐latitudes from 40°N to 65°N, roughly from mid‐March to mid‐September months but with an apparent yearly growth of its amplitude. The SD is caused by the satellite‐current system adjustment at the terminator transition zone. The SP feature predominately appears at geo‐latitudes from 10°S to 40°N, showing annual recurrence and growing amplitude. Simulation suggests that the SP is caused by instantaneous illumination changes of probe surface when the boom of the electric field detector in the windward panel shades the LAP. According to the analysis of I‐V curves both inside and outside the SD and SP structures, we exclude the possibility of probe contamination and confirm that the scientific data of CSES LAP are reliable. These two regular features depend on the solar illumination conditions and the corresponding adjustment of the satellite‐current system equilibrium. This study provides a valuable reference for validating and pre‐calibrating data from LAP in‐situ measurements onboard similar low‐earth polar orbit satellites.

Spring‐Fall Asymmetry in VLF Amplitudes Recorded in the North Atlantic Region: The Fall‐Effect

AbstractA spring‐fall asymmetry is observed in daytime amplitude values of very low frequency (VLF) radio wave signals propagating over the North Atlantic during 2011–2019. We explore the processes behind this asymmetry by comparing against mesospheric mean temperatures and the semidiurnal solar tide (S2) in mesospheric winds. The solar radiation influence on VLF subionospheric propagation was removed from the daytime VLF amplitude values, isolating the fall‐effect. Similarly, the symmetric background level was removed from mesospheric mean temperatures undertaking comparable analysis. During fall, all three analyzed parameters experience significant deviation from their background levels. The VLF amplitude variation during spring is explained by the seasonal variation in solar illumination conditions, while the fall‐effect can be interpreted as a mean zonal wind reversal associated with both a S2 enhancement, and temperature reductions. Decreases in temperature can produce decreases in collision frequency, reducing VLF signal absorption, driving the observed VLF asymmetry.

Carbon dopants carriers facilitators as agents for improving hole extraction efficiency of cobalt tetraoxide nanoparticles employed in fabrication of photodetectors

(CH3NH3)3Bi2I9 perovskites have attracted enormous attention due to their lower toxic and more stable nature than CH3NH3PbI3 counterparts. However, higher bandgap and lower carrier mobility hinder the application of (CH3NH3)3Bi2I9 in optoelectronics. Hence, we employed carbon doping of Co3O4 hole extractors to reduce the bandgap of (CH3NH3)3Bi2I9, minimize non – radiative recombination rate and improve surface morphology of the (CH3NH3)3Bi2I9 particles. Consequently, photodetectors based on carbon-doped Co3O4 display reduced internal resistance, high photocurrent and low dark current values. The fabricated photodetectors display high responsivity (1.56 × 106 μA/W), high detectivity (5.74 × 1012 Jones), high sensitivity (8.23 × 103) and fast optical switching times (< 10 ms) values under device testing conditions of 2.0 V bias voltage, 10 mW/cm2 power intensity of solar illumination and ambient room conditions. The linearity and stability of the photodetectors over wide range of light intensities and 100 optical switching cycles were also demonstrated respectively.