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Abstract Due to its high energy density and low interface impedance, in situ polymerized gel electrolytes were considered as a promising electrolyte candidate for lithium metal batteries (LMBs). In this work, a new flame‐retardant gel electrolyte was prepared via in situ ring‐opening polymerization of DOL and TEP. The PDOL–TEP electrolyte exhibits excellent room temperature ionic conductivity (0.38 mS cm−1), wide electrochemical window (4.4 V), high Li+ transference number (0.57), and enhanced safety. Thus, the NCM811||Li cells with PDOL–TEP electrolyte exhibit excellent cycle stability (82.7% of capacity retention rate after 300 cycles at 0.5 C) and rate performance (156 and 119 mAh g−1 at 0.5 and 1 C). Furthermore, phosphorus radicals decomposed from TEP can combine with hydrogen radicals to block the combustion reaction. This work provides an effective method for the preparation of solid‐state LMBs with high voltage, high energy density, and high safety.

Abstract The development of advanced perovskite emitters has considerably improved the performance of perovskite light-emitting diodes (LEDs). However, the further development of perovskite LEDs requires ideal device electrical properties, which strongly depend on its interfaces. In perovskite LEDs with conventional p-i-n structures, hole injection is generally less efficient than electron injection, causing charge imbalance. Furthermore, the popular hole injection structure of NiO x /poly(9-vinylcarbazole) suffers from several issues, such as weak interfacial adhesion, high interfacial trap density and mismatched energy levels. In this work, we insert a self-assembled monolayer of [2-(9H-carbazol-9-yl)ethyl]phosphonic acid between the NiO x and poly(9-vinylcarbazole) layers to overcome these challenges at the organic/inorganic heterointerfaces by establishing a robust interface, passivating interfacial trap states and aligning the energy levels. We successfully demonstrate blue (emission at 493 nm) and green (emission at 515 nm) devices with external quantum efficiencies of 14.5% and 26.0%, respectively. More importantly, the self-assembled monolayer also gives rise to devices with much faster response speeds by reducing interfacial capacitance and resistance. Our results pave the way for developing more efficient and brighter perovskite LEDs with quick response, widening their potential application scope.

BackgroundNon-suicidal self-injury (NSSI) has become a significant public health issue, especially prevalent among adolescents. The complexity and multifactorial nature of NSSI necessitate a comprehensive understanding of its underlying causal factors. This research leverages the causal discovery methodology to explore these causal associations in children.MethodsAn observational dataset was scrutinized using the causal discovery method, particularly employing the constraint-based approach. By integrating machine learning and causal inference techniques, the study aimed to determine direct causal relationships associated with NSSI. The robustness of the causal relationships was evaluated using three methods to construct and validate it: the PC (Peter and Clark) method, Fast Causal Inference (FCI) method, and the GAE (Graphical Autoencoder) method.ResultsAnalysis identified nine nodes with direct causal relationships to NSSI, including life satisfaction, depression, family dysfunction, sugary beverage consumption, PYD (positive youth development), internet addiction, COVID-19 related PTSD, academic anxiety, and sleep duration. Four principal causal pathways were identified, highlighting the roles of lockdown-induced lifestyle changes, screen time, positive adolescent development, and family dynamics in influencing NSSI risk.ConclusionsAn in-depth analysis of the factors leading to Non-Suicidal Self-Injury (NSSI), highlighting the intricate connections among individual, family, and pandemic-related influences. The results, derived from computational causal analysis, underscore the critical need for targeted interventions that tackle these diverse causative factors.

Abstract The underlying surface was the important media of air-lake interaction by transferring energy. The deployment of photovoltaic arrays on the lake has formed a new underlying surface type. But the new underlying surface is different from the natural lake. The impact of fishery complementary photovoltaic (FPV) power plants on the radiation, energy flux, and driving force is unclear. Therefore, the analysis of radiation, energy flux, and driving force by comparing the difference in the two sites under various synoptic conditions. The results indicated that the radiation components are not significantly different in the two sites under diverse synoptic conditions. The downward shortwave radiation (DSR) and net radiation ( $${R}_{n}$$ R n ) were presented with one peak on a sunny day. The daily average DSR and Rn in the two sites were 279.1 W·m−2, 209.3 W·m−2, respectively. The daily average (cloudy day and rainy day) sensible heat flux in the two sites was 39.5 W·m−2 (FPV site), 19.2 W·m−2 (REF site), respectively. The latent heat flux was 53.2 W·m−2 and 75.2 W·m−2 on counterpart. The water body generally absorbs heat from the air (daily average ∆Q was 16.6 W·m−2) in the FPV site on a sunny day. The driving force of sensible heat flux in the FPV site was governed by the temperature of the FPV panel under sunny and cloudy conditions. The latent heat flux was determined by the product between wind speed and water-atmosphere temperature difference.

The complex pore structure of unconventional oil and gas reservoirs is one of the reasons for the difficulties in resource evaluation and development. Therefore, it is crucial to comprehensively characterize the pore structure, understand reservoir heterogeneity from multiple perspectives, and gain an in-depth understanding of fluid migration and accumulation mechanisms. This review outlines the methods and basic principles for characterizing microporous systems in unconventional reservoirs, summarizes the fractal analysis corresponding to the different methods, sorts out the relationship between the fractals and reservoir macroscopic physical properties (porosity, permeability, etc.) with the reservoir microscopic pore structures (pore structure parameters, pore connectivity, etc.). The research focuses on cutting-edge applications of characterization techniques, such as improved characterization accuracy, calibration of PSD ranges, and identification of different hydrogen compositions in pore systems for dynamic assessment of unconventional reservoirs. Fractal dimension analysis can effectively identify the quality level of the reservoir; complex pore-throat structures reduce permeability and destroy free fluid storage space, and the saturation of removable fluids is negatively correlated with Df. As for the mineral composition, the fractal dimension is positively correlated with quartz, negatively correlated with feldspar, and weakly correlated with clay mineral content. In future qualitative characterization studies, the application and combination of contrast agents, molecular dynamics simulations, artificial intelligence techniques, and 4D imaging techniques can effectively improve the spatial resolution of the images and explore the adsorption/desorption of gases within the pores, and also help to reduce the computational cost of these processes; these could also attempt to link reservoir characterization to research on supercritical carbon dioxide-enhanced integrated shale gas recovery, carbon geological sequestration, and advanced underground hydrogen storage.

Abstract Shallow soil refers to the soil layer within the 50 cm depth. Shallow soil temperature (ST) directly or indirectly affects many processes in the soil, such as seed germination, plant growth, and water evaporation. Therefore, the study of shallow ST is of great significance in understanding the surface energy, water cycle, ecology and climate change. This work collected observational data from 141 meteorological stations on the Qinghai-Tibet Plateau from 1981 to 2020 and ERA5 reanalysis data, used the “Moving Surface Spline Interpolation Algorithm Based on Green’s Function” and “Fuzzy C-means algorithm”, and analyzed the temporal and spatial change characteristics of ST at different levels. The results showed that 1) the temperature increase of 0–20 cm (the surface layer of the shallow soil) was roughly the same. The average annual ST was 9.15–9.57°, and the interdecadal variabilities were 0.49–0.53 K/10a. The average annual ST of 40 cm (the bottom layer) was 8.69°, and the interdecadal variability reached 0.98 K/10a. 2) Considering the 7 regions, the warming trend was obvious, and there were certain regional differences. The average annual ST in different regions ranged from 5.2 (northeastern Plateau) to 17.1 °C (western Sichuan Plateau), with a difference of nearly 12 K. The standard deviation ranged from 0.40 (western Sichuan Plateau) to 0.61 K (Qiangtang Plateau), with a difference of 0.21 K. 3) The errors of the obtained grid data were basically less than 3%, which were much smaller than the errors obtained from the ERA5 reanalysis data. This work is significant for understanding the characteristics of ST evolution and land‒atmosphere interactions on the Qinghai-Tibet Plateau and provides important data support for improving the underlying surface boundary conditions of models.

Air pollution is one of the most important factors affecting the solar radiation reaching the earth’s surface under the clear (cloudless) sky conditions. In this work, six typical cities with serious pollution located in the north, northeast, eastern, central, southwest, and southern regions of China: Beijing, Shenyang, Shanghai, Wuhan, Wenjiang and Guangzhou were selected. The influence of air pollution on global and diffuse solar radiation (Rsand Rd) under clear sky condition was quantitatively analyzed, based on the historical daily meteorological data from January 2014 to December 2020. The results showed that the highest Rsattenuation ratio of the above six cities appeared in spring, autumn, winter, summer, autumn and winter, respectively. The largest Rdincrement ratio of the six cities appeared in summer, spring, autumn, summer, autumn and spring, respectively. From 2014 to 2020, the relative attenuation of Rscaused by air pollution (AQI > 100) was largest in Beijing (6.03%), followed by Shanghai (4.21%), Wenjiang (4.15%), Shenyang (3.28%) and Wuhan (3.14%), while Guangzhou (1.32%) had the smallest relative attenuation. Additionally, the Rdrelative increment was largest in Beijing (16.21%), followed by Shanghai (8.78%), Wenjiang (8.13%), Shenyang (7.76%) and Guangzhou (5.96%), while Wuhan (2.57%) had the smallest relative increment.

The construction and operation of photovoltaic （PV） power stations have changed the surface characteristics of the natural underlying surface， which may cause changes in land surface process factors such as surface albedo and surface roughness， affecting the characteristics of material exchange and energy distribution.In order to explore the influence of the construction of Gobi photovoltaic power station on the underlying land surface parameters and improve the land surface process model， this paper studied the characteristics of the underlying land surface parameters of the photovoltaic power station based on the observation data of the photovoltaic power station and reference stations in Wujiaqu.The results showed that the average aerodynamic roughness inside the PV plant is 0.12 m， which is much larger than the roughness of the natural Gobi underlying surface.During the daytime， the friction velocity and momentum flux inside the PV plant are larger than those at the reference site， with the maximum values in the daily variation increased by 18.8% and 38.5%， respectively.The vertical turbulent mixing in the PV plant increased by 22.2% compared to the reference site， while the latitudinal and longitudinal turbulence intensity decreased by 11.8% and 2.9%， respectively.The average soil thermal conductivity of 5~20 cm depth in photovoltaic power station is 0.33 W·（m·K）-1.

With the large-scale construction of photovoltaic power plants， the physical characteristics of the near-surface layer change accordingly.The turbulence activity as the way of interaction between the earth and the atmosphere is also affected by it.As a new form of solar power generation， lake photovoltaic power plant plays a vital role in energy application.In order to understand the characteristics of local turbulence in lake photovoltaic power plants， the observed data of the photovoltaic power plant from July to November 2021 in Yingfang Village， Fengyu Town， Yangzhong City， Jiangsu Province， were used in this study to investigate the turbulence characteristics and the variation rules of stability.The results indicate that： the installation of photovoltaic power plant enhanced the turbulence intensity， and showed as Iv>Iu>Iw， which had a certain influence on the local airflow.At the same time， the photovoltaic power plant promoted the enhancement of turbulent kinetic energy and friction velocity， and significantly increased the local momentum and heat transport.The momentum transport coefficient CD=13.36×10-3，and the sensible heat transport coefficient CH=6.01×10-3.The instability of near-ground atmosphere on photovoltaic power plant was enhanced in the daytime， and conversely， it was enhanced stability at night.After the classification of stability， the near-ground atmosphere on photovoltaic power plant was mainly concentrated in neutral and near neutral， accounting for 75.11%.

In the situation of low-carbon energy development， photovoltaic power industry develops rapidly， and photovoltaic power stations in China are mostly built in the Northwest Gobi region.In order to study the influence of Gobi photovoltaic power station on local climate and environment， this paper compared and analyzed the characteristics and differences of meteorological elements between the Gobi photovoltaic power station and the reference station in December 2019 and April， July and October 2020.The results show that the temperature of PV power station at 2 m height is lower than the reference point in all seasons at night， and the cooling effect weakens with the increase of height.The temperature of PV power station is higher than that of the reference site at 2 m height in the daytime of spring， summer and autumn， but lower than that of the reference site in the daytime of winter.With the increase of height， the warming effect weakens in spring and summer in daytime， and strengthens in autumn and winter.Because the specific heat capacity of photovoltaic panel is lower than that of soil， the temperature of photovoltaic panel is higher than the surface temperature of reference station in daytime， and the difference increases with the enhancement of solar radiation.Compared with the reference station， the wind direction in the photovoltaic power station is single and the wind speed is lower due to the shielding effect of the photovoltaic array on the wind.With the increase of height， the influence of pv array on wind field decreases.

A single-phase voltage source inverter (VSI) still suffers from a long settling time and significant voltage overshoot/undershoot under the abrupt step-change of load current. This article analyzes the comprehensive large-signal dynamic process and limitation of the linear controller during step change in load current. The combination of linear and nonlinear control is presented which is a realistic, simple, and low-cost technique for enhancing the dynamic response of the single-phase VSI. A nonlinear controller based on the simplified capacitor charge balance algorithm is employed to drive the inductor current and capacitor voltage to attain the target value by precisely following the projected optimal trajectory during the transient process in a brief period. A linear PI controller is utilized during the steady-state operations such as input voltage variations, temperature drifts, and component ageing. The complete mathematical derivation as well as a design method is presented to guide the practical hardware implementation for the given main circuit parameters and identified load step change. Even though accurate time instants can be obtained using off-line numerical calculations, reasonable simplifications are provided for real-time practical engineering applications in DSP. Finally, simulation and experimental verifications prove that the single-phase VSI achieves a substantial settling time decrease and reduced voltage oscillations.

Halide perovskite based light-emitting diodes attracted intensive research interest recently but the efficiency of blue diodes is much lower than the green and red ones. Here Li et al. push up the efficiency of blue diodes through composition engineering and vertical morphology control.

In this work, a molecular dynamics simulation was conducted to study the microscopic mechanism of how nitrogen bubbles affect the formation of THF hydrates at the molecular level. The results obtained reveal that the nitrogen bubble can promote the formation of THF hydrates. In the system with a nitrogen bubble, more THF-filled cages were generated, and the crystal structure was more orderly. The promotion of nitrogen bubbles on hydrate crystallization comes from the dissolution of nitrogen molecules. Some of dissolved nitrogen molecules can be enclosed in small hydrate cages near the nitrogen bubble, which can serve as stable sites for hydrate crystal growth, resulting in the fact that THF-filled cages connected with N2-filled cages are much more stable and have a long lifetime. The results in this work can help to understand the promotion effect of micro- and nano-air bubbles on the crystallization of THF hydrates.

Summary: Low-band-gap metal halide perovskite semiconductor based on mixed Sn/Pb is a key component to realize high-efficiency tandem perovskite solar cells. However, the mixed perovskites are unstable in air due to the oxidation of Sn2+. To overcome the stability problem, we introduced N-(3-aminopropyl)-2-pyrrolidinone into the CH3NH3Sn0.5Pb0.5IxCl3-x thin film. The carbonyl group on the molecule interacts with Sn2+/Pb2+ by Lewis acid coordination, forming vertically oriented 2D layered perovskite. The 2D phase is seamlessly connected to the bulk perovskite crystal, with a lattice coherently extending across the two phases. Based on this 2D/3D hybrid structure, we assembled low-band-gap Sn-based perovskite solar cells with power conversion efficiency greater than 12%. The best device was among the most stable Sn-based organic-inorganic hybrid perovskite solar cells to date, keeping 90% of its initial performance at ambient condition without encapsulation, and more than 70% under continuous illumination in an N2-filled glovebox for over 1 month. : Materials Science; Optical Materials; Energy Materials Subject Areas: Materials Science, Optical Materials, Energy Materials

Complex dielectric constant (CDC) of bound water determines the accuracy of the complex dielectric constant of wet soil. According to electrical double-layer structure and dielectric properties, the bound water on clay particle surface is divided into strongly bound water and weakly bound water. Based on this classification, models for the complex dielectric constants of bound water and soil are established taking into consideration factors such as temperature, moisture, texture, and microwave frequency. The results show that the fundamental reason why the complex dielectric constant of bound water is between that of ice and free water is the adsorption force which forms the electrical double-layer structure on the surface of clay particles. Low-concentration cationic solution could exist in free soil water and was found as the reason for the higher salinity and conductivity of free soil water, as compared to the measured soil solution. Results of soil CDC model are in good agreement with measured data across a wide range of microwave frequencies and soil temperature, moisture, and texture. The absolute root mean square error analysis also shows that the soil CDC model in this paper compared to the other models is more accurate.

An algorithm to forecast very short-term (30–180 min) surface solar irradiance using visible and near infrared channels (AGRI) onboard the FengYun-4A (FY-4A) geostationary satellite was constructed and evaluated in this study. The forecasting products include global horizontal irradiance (GHI) and direct normal irradiance (DNI). The forecast results were validated using data from Chengde Meteorological Observatory for four typical months (October 2018, and January, April, and July 2019), representing the four seasons. Particle Image Velocimetry (PIV) was employed to calculate the cloud motion vector (CMV) field from the satellite images. The forecast results were compared with the smart persistence (SP) model. A seasonal study showed that July and April forecasting is more difficult than during October and January. For GHI forecasting, the algorithm outperformed the SP model for all forecasting horizons and all seasons, with the best result being produced in October; the skill score was greater than 20%. For DNI, the algorithm outperformed the SP model in July and October, with skill scores of about 12% and 11%, respectively. Annual performances were evaluated; the results show that the normalized root mean square error (nRMSE) value of GHI for 30–180 min horizon ranged from 26.78% to 36.84%, the skill score reached a maximum of 20.44% at the 30-min horizon, and the skill scores were all above 0 for all time horizons. For DNI, the maximum skill score was 6.62% at the 180-min horizon. Overall, compared with the SP model, the proposed algorithm is more accurate and reliable for GHI forecasting and slightly better for DNI forecasting.

Using data collected from a specially designed experiment at the Dunhuang Station (40°10′N, 94°31′E, 1150 m) from September 2017 to September 2018, we have characterized the influences of soil moisture and solar altitude on surface spectral albedo in an arid area. The specific settings of our experiment allowed us to minimize the influences of underlying surface, cloud cover, aerosol and weather conditions, and thus highlight the influence of soil moisture and solar altitude. During the timespan of the experiment, we observed the annual mean surface albedo of global radiation (GR), ultraviolet radiation (UV), visible radiation (VIS) and near-infrared radiation (NIR) to be 0.24, 0.11, 0.24 and 0.25. A significantly negative linear correlation between surface albedo and soil moisture was identified, with the correlation coefficients between GR, UV, VIS, NIR and soil moisture being −0.68, −0.75, −0.70 and −0.61. In addition, we identified an exponential relationship between surface albedo and solar altitude. The exponential regression coefficients are −0.21, −0.077, −0.53 and −0.21, respectively. From these analyses, we derived a new two-factor parametric formula for depicting the influence of soil moisture and solar altitude on surface spectral albedo. Using observation data, we demonstrate that the formula recapitulates the real-world relationship between soil moisture, solar altitude and surface spectral albedo with little deviation. These findings may help us gain a deeper understanding of improving land surface parameterizations and have potential implications for solar energy research and applications.

The accurate prediction of surface solar irradiance is of great significance for the generation of photovoltaic power. Surface solar irradiance is affected by many random mutation factors, which means that there are great challenges faced in short-term prediction. In Northwest China, there are abundant solar energy resources and large desert areas, which have broad prospects for the development of photovoltaic (PV) systems. For the desert areas in Northwest China, where meteorological stations are scarce, satellite remote sensing data are extremely precious exploration data. In this paper, we present a model using FY-4A satellite images to forecast (up to 15−180 min ahead) global horizontal solar irradiance (GHI), at a 15 min temporal resolution in desert areas under different sky conditions, and compare it with the persistence model (SP). The spatial resolution of the FY-4A satellite images we used was 1 km × 1 km. Particle image velocimetry (PIV) was used to derive the cloud motion vector (CMV) field from the satellite cloud images. The accuracy of the forecast model was evaluated by the ground observed GHI data. The results showed that the normalized root mean square error (nRMSE) ranged from 18.9% to 21.6% and the normalized mean bias error (nMBE) ranged from 3.2% to 4.9% for time horizons from 15 to 180 min under all sky conditions. Compared with the SP model, the nRMSE value was reduced by about 6%, 8%, and 14% with the time horizons of 60, 120, and 180 min, respectively.

This study uses the brightness temperature at the given microwave frequency (18.7 GHz) from the Microwave Radiation Imager (MWRI) on-board the Fengyun-3B (FY-3B) satellite to improve the τ-ω model by considering the radiative contribution from waterbody in the pixels over the wetland of the Yellow River source region, China. In order to retrieve vegetation optical depth (VOD), a dual-polarization slope parameter is defined to express the surface emissivity in the τ-ω model as the sum of soil emissivity and waterbody emissivity. In the regions with no waterbody, the original τ-ω model without considering waterbody impact is used to derive VOD. With use of the field observed vegetation water content (VWC) in the source region of the Yellow River during the summer of 2012, a regression relationship between VOD and VWC is established and then the vegetation parameter b is estimated. The relationship is employed to derive the spatial VWC during the entire vegetation growing period. The VOD retrieved is invalid and failed in some part of the study area by using the previous τ-ω model, while the results from the improved τ-ω model indicate that the VOD is in the range of 0.20 to 1.20 and the VWC is in the range of 0.20kg/m2 to 1.40kg/m2 in the entire source region of the Yellow River in 2012. Both VOD and VWC exhibit a pattern of low values in the west part and high values in the east part. The largest regional variations appear along the Yellow River. The comparison between the remote-sensing-estimated VWC and the ground-measured VWC gives the root mean square error of 0.12kg/m2. These assessments reveal that with considering the fractional seasonal wetlands in the source region of the Yellow River, the microwave remote sensing measurements from the FY-3B MWRI can be successfully used to retrieve the VWC in the source region of the Yellow River.

The total atmospheric water vapor content (TAWV) and land surfacetemperature (LST) play important roles in meteorology, hydrology, ecology and some otherdisciplines. In this paper, the ENVISAT/AATSR (The Advanced Along-Track ScanningRadiometer) thermal data are used to estimate the TAWV and LST over the Loess Plateauin China by using a practical split window algorithm. The distribution of the TAWV isaccord with that of the MODIS TAWV products, which indicates that the estimation of thetotal atmospheric water vapor content is reliable. Validations of the LST by comparingwith the ground measurements indicate that the maximum absolute derivation, themaximum relative error and the average relative error is 4.0K, 11.8% and 5.0%respectively, which shows that the retrievals are believable; this algorithm can provide anew way to estimate the LST from AATSR data.

Under the goal of “Carbon Emission Peak and Carbon Neutralization”, the integrated development between various industries and renewable energy (photovoltaic, wind power) is of great significance in China. This paper summarizes the relevant policies, integration schemes and typical cases of the integrated development between renewable energy and other industries. First, the development status of wind and solar generation in China is introduced. Second, we summarize the relevant policies issued by the National Development and Reform Commission, National Energy Administration and other departments to promote the integrated development in photovoltaic and wind power generation in China. Third, eight kinds of photovoltaic three-dimensional development models are described, including “photovoltaic + agriculture, industry, environmental protection, transportation, architecture, communication, hydrogen and ecology”. Fourth, eight kinds of wind power three-dimensional development models are summarized, including “Offshore wind power + marine ranch, marine energy, marine tourism, marine oil and gas, hydrogen, communication, Energy Island” and “Onshore wind power + courtyard”. In the future, the promotion and application of the above integrated development projects will be accelerated. This overview aims to provide reference for the design in photovoltaic and wind energy systems and help potential investors to make decisions. [ABSTRACT FROM AUTHOR]