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Irrigated cotton (Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content (θ), soil temperature (Tsoil°) and plant transpiration (T), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and Tsoil°, as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha−1) and net income (US $3165 ha−1), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha−1 mm−1) and net water production (0.94 $ m−3). These results provided farmers guidelines to adopt deficit irrigation strategies.

A precisely timed irrigation schedule to match crop water demand is vital to improving water use efficiency in arid farmland. In this study, a real-time irrigation-scheduling infrastructure, Decision Support System for Irrigation Scheduling (DSSIS), based on water stresses predicted by an agro-hydrological model, was constructed and evaluated. The DSSIS employed the Root Zone Water Quality Model (RZWQM2) to predict crop water stresses and soil water content, which were used to trigger irrigation and calculate irrigation amount, respectively, along with forecasted rainfall. The new DSSIS was evaluated through a cotton field experiment in Xinjiang, China in 2016 and 2017. Three irrigation scheduling methods (DSSIS-based (D), soil moisture sensor-based (S), and conventional experience-based (E)), factorially combined with two irrigation rates (full irrigation (FI), and deficit irrigation (DI, 75% of FI)) were compared. The DSSIS significantly increased water productivity (WP) by 26% and 65.7%, compared to sensor-based and experience-based irrigation scheduling methods (p < 0.05), respectively. No significant difference was observed in WP between full and deficit irrigation treatments. In addition, the DSSIS showed economic advantage over sensor- and experience-based methods. Our results suggested that DSSIS is a promising tool for irrigation scheduling.

An important but rarely studied aspect of crop modeling is the uncertainty associated with model calibration and its effect on model prediction. Biomass and grain yield data from a four-year maize experiment (2008−2011) with six irrigation treatments were divided into subsets by either treatments (Calibration-by-Treatment) or years (Calibration-by-Year). These subsets were then used to calibrate crop cultivar parameters in CERES (Crop Environment Resource Synthesis)-Maize implemented within RZWQM2 (Root Zone Water Quality Model 2) using the automatic Parameter ESTimation (PEST) algorithm to explore model calibration uncertainties. After calibration for each subset, PEST also generated 300 cultivar parameter sets by assuming a normal distribution of each parameter within their reported values in the literature, using the Latin hypercube sampling (LHS) method. The parameter sets that produced similar goodness of fit (11−164 depending on subset used for calibration) were then used to predict all the treatments and years of the entire dataset. Our results showed that the selection of calibration datasets greatly affected the calibrated crop parameters and their uncertainty, as well as prediction uncertainty of grain yield and biomass. The high variability in model prediction of grain yield and biomass among the six (Calibration-by-Treatment) or the four (Calibration-by-Year) scenarios indicated that parameter uncertainty should be considered in calibrating CERES-Maize with grain yield and biomass data from different irrigation treatments, and model predictions should be provided with confidence intervals.

Wearable electronic devices with multifunctions such as flexible, integrated, and self-powered play a crucial role in the fields of health monitoring, motion monitoring, and human-computer interaction. However, their core basic components, flexible pressure sensors, face challenges including poor long-term stability and insufficient real-time sensing accuracy. In order to solve the challenges of long-term, stable, and accurate sensing of the sensor, this paper prepares polydimethylsiloxane (SHPDMS) with intrinsic self-healing property and designs a high-sensitivity self-healing capacitive flexible pressure sensor with dual microstructures (grating microstructured electrodes and microporous dielectric layer) as the substrate based on SHPDMS. Specifically speaking, the self-healing of the sensor under mild conditions was realized by introducing reversible imine bonds with low bonding energy into the polydimethylsiloxane (PDMS) flexible substrate, which solved the problem of the material's long-term service durability. A grating-like microstructure was introduced into the flexible electrode by using a spotted bamboo taro leaf as a template, and a dual microstructure sensor was constructed by combining it with a microporous dielectric layer doped with single-walled carbon nanotubes. This way reduces the elastic modulus of the dielectric layer, improves the dielectric constant of the sensor under loading, and thus significantly improves the sensor's sensitivity and extends the measurement accuracy in a low-stress range. The prepared self-healing flexible sensor achieves a sensitivity of 3.6 kPa -1 , a minimum detection limit of 5 Pa, a response recovery time of less than 80 ms, and stability over 5000 cycles, which exceeds most previously reported silicone rubber-based capacitive flexible sensors.

Small defects induce concentrated electrical stress in dielectric polymers, leading to premature failure of materials. Existing sensing methods fail to effectively visualize these defects owing to the invisible-energy state of the electric field. Thus, it is necessary to establish a nondestructive method for the real-time detection of small defects in dielectric polymers. In this study, a self-reporting microsensor (SRM) inspired by Noctiluca scintillans is designed to endow materials with the ability of self-detection for defects and electrical stress. The SRM leverages the energy of a nearby electric field to emit measurable fluorescence, enabling defect localization and diagnosis as well as electrical-stress visualization. A controllable dielectric microsphere is constructed to achieve an adjustable electroluminescence threshold for the SRM, thereby increasing its detection accuracy while decreasing the electroluminescence threshold. The potential degradation in the polymer performance owing to SRM implantation is addressed by assembling long molecular chains on the SRM surface to spontaneously generate an interpenetrating network. Results of finite element analyses and experiments demonstrate that the SRM can effectively realize nondestructive visualization and positioning of small defects and concentrated electrical stress in polymers, positioning it as a promising sensing method for monitoring the electric field and charge distribution in materials., (© 2024 Wiley‐VCH GmbH.)

The long-term operation of power equipment and power electronics can cause local overheating and discharges in the insulation material, resulting in irreversible insulation damage. Further development of such damage can eventually lead to equipment failure, but this problem is very difficult to solve. In this paper, inspired by how the petals of morning glory change color with the environment due to the presence of pigmented globules, a dual-function heat alert in the form of a self-healing (HASH) microcapsule with a nested structure is prepared by using microfluidic technology. By combination of the microcapsule with the insulation material, the local overheating in equipment can be detected promptly under live operating conditions without manual external intervention, and the defects that occur can be repaired autonomously. These HASH microcapsules can be pre-embedded in places at which the material is prone to overheating using artificial magnetic targeting. The doping of the matrix material with microcapsules does not cause any deterioration in its electrical or mechanical properties. This technology is expected to be applied to electrical equipment and electronic devices to allow for the early detection of local overheating and the autonomous repair of defects, thereby ensuring the safety of the equipment and improving its service life.

Long-term intensive cultivation has led to serious N loss and low N fertilizer utilization efficiency (NUE) in black soil areas. The lost N is not only a waste of resources but also a serious pollution threat to the environment, leading to the decline in water quality and food safety and the greenhouse effect. In the present study, a stable dual slow-release model, CPCS-Urea, was prepared by in situ polymerization using nitrapyrin, urea and melamine-formaldehyde resin as raw materials. The effect of the dual slow-release model was systematically evaluated using two consecutive years of field experiments. Five treatments were established in the field experiment: no N fertilizer (N0), urea (N180), 1 % CPEC-Urea, 0.5 % CPCS-Urea, and 1 % CPCS-Urea. The results showed that the new dual slow-release CPCS-Urea model outperformed both the use of urea and the traditional slow-release CPEC-Urea model in reducing N losses and improving NUE. The application of CPCS-Urea reduced nitrate (NO 3 - ) leaching by 28.2 %-47.2 % and N 2 O emissions by 36.5 %-42.4 % and increased NUE by 20.7 %-28.5 % compared to urea application. The CPCS-Urea model modulated the activity of ammonia-oxidizing bacteria (AOB) and dissimilatory nitrate reduction to ammonium (DNRA) bacteria in soil, showing a significant decrease in AOB activity and an increase in DNRA activity. This results in a lower soil NO 3 - -N yield and a 53.1 %-72.0 % increase in NH 4 + -N content, providing sufficient N for the entire growth and development cycle of maize. In short, the dual slow-release CPCS-Urea model has great application prospects for promoting agricultural development in black soil areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Strong electromagnetic and heat flux stresses can induce severe damage to solid insulation materials, leading to faults in power equipment and power electronics devices. However, in the absence of suitable in situ imaging methods for observing the development and morphology of electrical damage within insulation materials, the mechanism of insulation failure under high-frequency electric fields has remained elusive. In this work, a recently discovered fluorescence self-excitation phenomenon in electrical damage channels of polymers is used as the basis for a laser confocal imaging method that is able to realize three-dimensional (3D) in situ imaging of electrical tree channels in silicone gel through nondestructive means. Based on the reconstructed morphology of the damaged area, a spatial equivalent calculation model is proposed for analysis of the 3D geometric features of electrical trees. The insulation failure mechanism of silicone gel under electric fields of different frequencies is analyzed through ReaxFF molecular dynamics simulations of the thermal cracking process. This work provides a new method for in situ nondestructive 3D imaging of micro/nanoscale damage structures within polymers with potential applications to material analysis and defect diagnosis.

The development of high-precision, non-destructive, and three-dimensional (3D) in situ imaging of micro-scale damage inside polymers is extremely challenging. Recent reports suggest that 3D imaging technology based on micro-CT technology causes irreversible damage to materials and is ineffective for many elastomeric materials. In this study, it is discovered that electrical trees inside silicone gel induced by an applied electric field can induce a self-excited fluorescence effect. Based on this, high-precision, non-destructive, and 3D in situ fluorescence imaging of polymer damages is successfully achieved. Compared with the current methods, the fluorescence microscopic imaging method enables slicing of the sample in vivo with high-precision operation, realizing the precise positioning of the damaged area. This pioneering discovery paves the way for high-precision, non-destructive, and 3D in situ imaging of polymer internal damage, which can solve the problem of internal damage imaging in insulating materials and precision instruments., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Despite the proposal of nanodielectrics in 1994, the impact of nano- and microstructures on composite performance is still not completely understood. A key reason for this knowledge gap is the lack of in situ characterization of micro- and nanoscale structures within materials. In this study, we observed the self-excited fluorescence of a microscale-damaged microchannel inside a composite under the influence of an electric field. Furthermore, we conducted in situ imaging of the internal microstructures and discharge channels in the composite utilizing external laser excitation. The imaging results reveal that the electrical treelike damage in the composites grows with a single channel under the guidance of the nanoskeleton embedded in the matrix, which demonstrates that the three-dimensional (3D) nano-order skeleton hinders the development of electrical trees. Furthermore, we analyzed the nanoskeleton intervention's enhancement mechanism on the insulation properties of the composites. This work aids in the precision imaging-guided structural design of nanodielectrics.

Repairing the micro-scale damage of insulating materials under a strong electric field has long been a highly desired but challenging task. Among all kinds of damage, water tree damage in the insulating materials of electrical equipment and electronic devices working in humid environments has long been considered irreparable. The main challenge is that residual water prevents the healing agent from filling the water tree branch channel. To solve this problem, this work reports a magnetically targeted, water-triggered, self-healing microcapsule (MTWTSH-MC) that makes a breakthrough against water tree damage based on microfluidic techniques. Targeted microcapsules driven by a directional magnetic field are concentrated to the vulnerable area of the insulating materials, exerting very limited effects on the dielectric. When damage breaks the microcapsules, the healing agent releases and quickly fills the damage channel and then reacts with water in the air or in the branch channel of the water tree, achieving solidification of the healing agent and self-healing of the damage channels. In this way, we can realize self-perception, self-triggering, and self-healing for both mechanical damage and water tree damage in insulation materials without any external stimulation.

During the long-term operation of solid insulation materials, strong electric fields and mechanical stress cause electrical trees and cracks that are undetectable and irreversible, leading to the failure of electronic and electrical devices. A promising means of protecting against these problems is to endow the insulating materials with some self-healing capability alongside their excellent intrinsic properties. However, this has proved extremely challenging. In this paper, we describe an ultraviolet light, moisture, and magnetic field triple-response microcapsule that enables epoxy resin materials to heal themselves against various forms of damage without affecting the intrinsic performance of the matrix. In particular, microcapsules wrapped inside functional shells containing Fe 3 O 4 nanoparticles are precisely controlled by a targeted magnetic field and distributed in the vulnerable area of the insulation materials, resulting in a high healing rate at low doping concentrations. Using the in situ ultraviolet light emitted by the electrical trees, artificial ultraviolet light, and moisture in the operating environment, it is possible to induce active or passive curing of the healing agent, thus realizing the intelligent, non-contact, and targeted self-healing of mechanical cracks and electrical tree damage. This method opens an avenue toward the development of self-healing insulation materials for electrical and electronic applications.

It remains challenging to promptly inhibit and autonomically heal electrical trees inside insulating dielectrics, which are caused by sustained strong electrical fields and substantially shorten electronic device lifetimes and even cause premature failure of electrical equipment. Therefore, we demonstrate a magnetically targeted ultraviolet (UV)-induced polymerization functional microcapsule (MTUF-MC) to endow insulating materials with physical and electrical dual-damage self-healing capabilities. Specifically, Fe 3 O 4 @SiO 2 and TiO 2 nanoparticles, which serve as magnetic targets and UV shields (thereby preventing the healing agent from prematurely triggering), constitute a functional microcapsule shell, ensuring a low dopant concentration and excellent self-healing ability of the epoxy composites without affecting the intrinsic performance of the matrix. By exploiting in situ electroluminescence originating from electrical trees, UV-induced polymerization of healing agent is handily triggered without any applying external stimuli to intelligently, contactlessly, and autonomously self-healing electrical trees inside insulating dielectrics.

In this work, the novel technology was used to remove heavy metal from sludge. The coupled with biodegradable ethylenediamine disuccinic acid (EDDS) and approaching anode electrokinetic (AA-EK) technique was used to enhance heavy metal removing from sludge. Electric current, sludge and electrolyte characteristics, heavy metal removal efficiency and residual content distribution, and heavy metal fractions percentage of variation were evaluated during the electrokinetic remediation process. Results demonstrated that the coupled with EDDS and AA-EK technique obtain a predominant heavy metal removal efficiency, and promote electric current increasing during the enhanced electrokinetic remediation process. The catholyte electrical conductivity was higher than the anolyte, and electrical conductivity of near the cathode sludge achieved a higher value than anode sludge during the coupled with EDDS and AA-EK remediation process. AA-EK technique can produce a great number of H + , which caused the sludge acidification and pH decrease. Cu, Zn, Cr, Pb, Ni and Mn obtain the highest extraction efficiency after the coupled with EDDS and AA-EK remediation, which were 52.2 ± 2.57%, 56.8 ± 3.62%, 60.4 ± 3.62%, 47.2 ± 2.35%, 53.0 ± 3.48%, 54.2 ± 3.43%, respectively. Also, heavy metal fractions analysis demonstrated that the oxidizable fraction percentage decreased slowly after the coupled with EDDS and AA-EK remediation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The effects of harmful algal blooms (HABs) on nutrient dynamics have been extensively studied; however, the response of nitrogen to continuous HAB degradation and subsequent reoccurrence is not well understood. Here, a small-scale experiment was conducted to assess how nitrogen in the sediment-water interface (SWI) responds to HAB degradation and subsequent reoccurrence at different initial algal densities. The results showed that during the algae decomposition stage, the NH 4 + -N flux of the SWI remained positive but decreased with the increase in algal density from 3.5 × 10 7 to 2.3 × 10 8 cells per L, indicating that the sediment was the source of NH 4 + -N. In contrast, the deposit was a sink of NO 3 - -N. However, during the reoccurrence of HAB, the distribution of NH 4 + -N and NO 3 - -N fluxes was completely converted. Nitrogen flux analysis throughout algae decomposition and reoccurrence indicated that although the sediment acted as a sink of nitrogen, the flux was dependent on the initial algal density. Our results confirmed that algae decomposition and reoccurrence would greatly affect the nitrogen cycle of the SWI, during which dissolved oxygen (DO) and initial algal density dominated. This study is the first to show that the regulation of nitrogen flux and migration changes during continuous HAB decomposition and subsequent reoccurrence., Competing Interests: The authors declare no competing financial interests., (This journal is © The Royal Society of Chemistry.)

Under operational conditions of high electric fields and elevated temperatures, the accumulation of space charges at multilayer insulation interfaces is often considered as an important factor affecting insulation performance. This study experimentally explored the influence of different thermal aging degrees (110 °C for 0, 720, 1600, 2100, and 2900 h) on physicochemical characteristics. The space charge dynamics in two-layered thermally aged PET-PET films were measured using the pulsed electro-acoustic (PEA) method and simulated on the basis of a one-dimensional modified bipolar charge transport model. The parameterization for key parameters involved in the model was analyzed through parameter sensitivity. Results indicated that the molecular structure, crystallinity, and dielectric spectra of the PET films are affected by thermal aging. The thermalization process also has noticeable effect on the surface state characteristics, which are characterized by deeper trap depth and larger trap density. Several experimental phenomena measured by the PEA method were observed on the basis of numerical simulation.

It has been proved that the nitrogen can be removed from the sediment in a sediment microbial fuel cell system (SMFCs), but the competition between nitrate and oxygen for electrons would be a key factor that would affect the removal efficiency, and its mechanism is not clear. Based on organic sediment fuel, an SMFC was constructed, and the influence of dissolved oxygen (DO) on nitrogen transformation and cathodic microbial communities was investigated. The results showed that the best total nitrogen removal efficiency of 60.55% was achieved at DO level of 3 mg/L. High DO concentration affected the removal efficiency through the electrons' competition with nitrate, while low DO concentration suppressed the nitrification. Comamonas, Diaphorobacter and Brevundimonas were the three dominant genera responsible for denitrification at DO concentration of 3 mg/L in this study. The establishment of SMFCs for nitrogen removal by regulating DO level would offer a promising method for sediment treatment.

Despite being discovered more than 20 years ago, nanofluids still cannot be used in the power industry. The fundamental reason is that nano-insulating oil has poor stability, and its electrical performance decreases under negative impulse voltage. We found that C 60 nanoparticles can maintain long-term stability in insulating oil without surface modification. C 60 has strong electronegativity and photon absorption ability, which can comprehensively improve the electrical performance of insulating oil. This finding has great significance for the industrial application of nano-insulating oil. In this study, six concentrations of nano-C 60 modified insulating oil (CMIO) were prepared, and their breakdown strength and dielectric properties were tested. The thermally stimulated current (TSC) curves of fresh oil (FO) and CMIO were experimentally determined. The test results indicate that C 60 nanoparticles can simultaneously improve the positive and negative lightning impulse and power frequency breakdown voltage of insulating oil, while hardly increasing dielectric loss. At 150 mg/L, the positive and negative lightning impulse breakdown voltages of CMIO increased by 7.51% and 8.33%, respectively, compared with those of FO. The AC average breakdown voltage reached its peak (18.0% higher compared with FO) at a CMIO concentration of 200 mg/L. Based on the test results and the special properties of C 60 , we believe that changes in the trap parameters, the strong electron capture ability of C 60 , and the absorption capacity of C 60 for photons enhanced the breakdown performance of insulating oil by C 60 nanoparticles.

Nano-modification is a prospective method for improving the electrical properties of transformer oil. In most situations, transformer oil combined with cellulose paper is used to construct an insulation system for power equipment, such as power transformers. However, the influence of nanoparticles on the electrical performance of oil-impregnated paper is still unclear. Therefore, in this paper, we identify the failure characteristics of both fresh and nano-modified oil/paper. Specifically, the accumulative failure characteristics of nano-oil-impregnated paper (NOIP) are experimentally determined. The space charge distribution and trap characteristics of fresh paper and NOIP were measured, and the effect of nanoparticles on the space charge behavior are then analyzed. Finally, we measure the microstructure of fresh paper and NOIP subjected to repeated impulses. The test results indicate that nano-titanium oxide (TiO₂) particles have a limited effect on the breakdown voltage of NOIP. However, the particles can dramatically improve the resistant ability of NOIP against repeated impulses. For the NOIP with a nano-concentration of 0.25 g/L, the improvement reaches 62.5% compared with fresh paper. Under repeated applications of impulse voltages, the space charge density of NOIP is much lower than that of fresh paper. The deep trap density of NOIP is much higher than that of fresh OIP, whereas shallow trap density is relatively lower. Micropores are generated in paper insulation subjected to repeated impulses. The amount of the generated micropores in NOIP is lower than that in fresh paper. Nano-TiO₂ particles suppress the accumulation of space charge in the oil paper insulation, which weakens the electric field distortion in the dielectric. However, nanoparticles reduce the accumulative damage caused by repeated impulses. The above two points are considered the main reasons to improve the resistant ability against repeated impulses.

Many hybrid proline-rich protein (HyPRP) genes respond to biotic and abiotic stresses in plants, but little is known about their roles other than as putative cell-wall structural proteins. A HyPRP1 gene encodes a protein with proline-rich domain, and an eight-cysteine motif was identified from our previous microarray experiments on drought-tolerant tomato. In this study, the expression of the HyPRP1 gene in tomato was suppressed under various abiotic stresses, such as drought, high salinity, cold, heat, and oxidative stress. Transgenic functional analysis showed no obvious changes in phenotypes, but enhanced tolerance to various abiotic stresses (e.g., oxidative stress, dehydration, and salinity) was observed in RNAi transgenic plants. Interestingly, several SO2 detoxification-related enzymes, including sulfite oxidase, ferredoxins (Fds), and methionine sulfoxide reductase A (Msr A), were revealed in HyPRP1-interacting proteins identified by Yeast Two-Hybrid screening. More sulfates and transcripts of Msr A and Fds were accumulated in HyPRP1 knockdown lines when wild-type plants were exposed to SO2 gas. Our findings illustrate that the tomato HyPRP1 is a negative regulator of salt and oxidative stresses and is probably involved in sulfite metabolism.