Search

This study investigates the effects of varying durations of aerated irrigation, administered at a consistent frequency, on the growth of greenhouse grape seedlings and the structure of the rhizosphere soil microbial community. Using two-year-old ‘Flame Seedless’ grape seedlings as the test material, we established a control group with no aeration (CK) and three treatment groups with aeration durations of 10 min (T1), 20 min (T2), and 30 min (T3), respectively. We determined grape seedling growth under different aerating durations. Additionally, changes in the rhizosphere soil microbial community of the plants were analyzed using 16S and ITS high-throughput genome sequencing to further explore the correlation between microbial diversity and plant growth. The results revealed that: (1) Aerated irrigation significantly enhanced plant growth, with the T2 treatment yielding superior increases in plant height, above-ground dry weight, below-ground dry weight, total root length, and root volume compared to T1 and T3 treatments. (2) Aeration treatments notably elevated the Shannon and Chao1 indices of the rhizosphere soil fungal community, with the T2 treatment exhibiting the most substantial effects, and the Shannon index of the bacterial community was also significantly higher under the T2 treatment. (3) The T2 treatment significantly increased the relative abundance of beneficial aerobic bacterial genera such as Flavobacterium, Ellin6067, and Coniochaeta, while decreasing the relative abundance of detrimental fungal genera like Fusarium and Gibberella. In conclusion, a 20 min aeration duration can effectively promote grape seedling growth, enhance the diversity of rhizosphere soil microbial communities, increase beneficial aerobic microorganisms, and reduce harmful ones. This study provides a theoretical basis for optimizing aerated irrigation practices in facility grape cultivation.

Alfalfa, a crucial forage crop, encounters substantial challenges in seed production in semi-arid regions due to drought and soil salinization. To address this challenge, a five-year field experiment was conducted in northwestern China to evaluate the effects of subsurface drip irrigation (SSDI) at different drip line depths and with different irrigation time treatments on alfalfa seed yield, yield components, irrigation water use efficiency (IWUE) and seed quality. The study indicated that SSDI at a depth of 10 cm resulted in a 48% increase in seed yield compared to surface drip irrigation and also obtained the highest IWUE with minimal soil disturbance. While irrigation during the branch, full bloom and pod set stages led to increasing for seed yield and IWUE, it was susceptible to climatic fluctuations during the growth period. Random forest modeling revealed that the timing and quantity of irrigation were key factors that determined yield components and seed yield. Climatic factors, specifically temperature and precipitation, played a significant role at each location. Irrigation time could have an effect on seed size, chlorophyll, and protein concentration analyzed by multispectral imaging. Linear discriminant analysis modeling indicated no significant difference in overall seed quality among the different irrigation time treatments, but prolonged seed maturation for the optimal irrigation time treatment. Therefore, installing the irrigation line at a depth of 10 cm and ensuring irrigation during the branching and full bloom stages were essential, while irrigation at the pod set stage was optional, for significantly improving the seed yield of alfalfa. RF model combined with the meteorology and irrigation management factors could determine key factors for the effect on seed yield. This research would provide valuable theoretical and practical insights for alfalfa seed production in semi-arid regions.

Abstract Sustainability and adaptability in structural design of the organic cathodes present promises for applications in alkali metal ion batteries. Nevertheless, a formidable challenge lies in their high solubility in organic electrolytes, particularly for small molecular materials, impeding cycling stability and high capacity. This study focuses on the design and synthesis of organic small molecules, the isomers of (E)‐5,5′‐difluoro‐[3,3′‐biindolinylidene]‐2,2′‐dione (EFID) and 3,9‐difluoro‐6,12‐dihydrodibenzo [c, h][2,6]naphthyridine‐5,11‐dione (FBND). While EFID, characterized by a less π‐conjugated structure, exhibits subpar cycling stability in lithium‐ion batteries (LIBs), intriguingly, another isomer, FBND, demonstrates exceptional capacity and cycling stability in LIBs. FBND delivers a remarkable capacity of 175 mAh g−1 at a current density of 0.05 A g−1 and maintains excellent cycling stability over 2000 cycles, retaining 90% of its initial capacity. Furthermore, an in‐depth examination of redox reactions and storage mechanisms of FBND are conducted. The potential of FBND is also explored as an anode in lithium‐ion batteries (LIBs) and as a cathode in sodium‐ion batteries (SIBs). The FBND framework, featuring extended π‐conjugated molecules with an imide structure compared to EFID, proves to be an excellent material template to develop advanced organic small molecular cathode materials for sustainable batteries.

Abstract Hollow structuring has been identified as an effective strategy to enhance the cycling stability of electrodes for rechargeable batteries due to the outstanding volume expansion buffering efficiency, which motivates ardent pursuing on the synthetic approaches of hollow materials. Herein, an intriguing route, combining solid precursor transition and Ostwald ripening (SPTOR), is developed to craft nano single‐crystal (SC)‐constructed MnCO3 submicron hollow spindles homogeneously encapsulated in a reduced graphene oxide matrix (MnCO3 SMHSs/rGO). It is noteworthy that the H‐bonding interaction between Mn3O4 nanoparticles (NPs) and oxygen‐containing groups on GO promotes uniform anchoring of Mn3O4 NPs on GO, mild reductant ascorbic acid triggers the progressive solid‐to‐solid transition from Mn3O4 NPs to MnCO3 submicron solid spindles (SMSSs) in situ on GO, and the Ostwald ripening process induces the gradual dissolution of interior polycrystals of MnCO3 SMSSs and subsequent recrystallization on surface SCs of MnCO3 SMHSs. Remarkably, MnCO3 SMHSs/rGO delivers a 500th lithium storage capacity of 2023 mAh g−1 at 1000 mA g−1, which is 10 times higher than that of MnCO3 microspheres/rGO fabricated from a conventional Mn2+ salt precursor (202 mAh g−1). The ultrahigh capacity and ultralong lifespan of MnCO3 SMHSs/rGO can be primarily attributed to the superior reaction kinetics and reversibility combined with exceptional interfacial and capacitive lithium storage capability, enabled by the fast ion/electron transfer, large specific surface area, and robust electrode pulverization inhibition efficacy. Moreover, fascinating in‐depth lithium storage reactions of MnCO3 are observed such as the oxidation of Mn2+ in MnCO3 to Mn3+ in charge process after long‐term cycles and the further lithiation of Li2CO3 in discharge process. As such, the SPTOR approach may represent a viable strategy for crafting various hollow functional materials with metastable nanomaterials as precursors.

Abstract Sodium iron hexacyanoferrate (FeHCF) is one of the most promising cathode materials for sodium‐ion batteries (SIBs) due to its low cost theoretical capacity. However, the low electrochemical activity of FeLS(C) in FeHCF drags down its practical capacity and potential plateau. Herein, FeHCF with high FeLS(C) electrochemical activity (C‐FeHCF) is synthesized via a facile citric acid‐assisted solvothermal method. As the cathode of SIBs, C‐FeHCF shows superior cycling stability (ca. 87.3% capacity retention for 1000 cycles at 10 C) and outstanding rate performance (ca. 68.5% capacity retention at 50 C). Importantly, the contribution of FeLS(C) to the whole capacity was quantitatively analyzed via combining dQ/dV and discharge curve for the first time, and the index reaches 44.53% for C‐FeHCF, close to the theoretical value. In‐situ X‐ray diffraction proves the structure stability of C‐FeHCF during charge–discharge process, ensuring its superior cycling performance. Furthermore, the application feasibility of the C‐FeHCF cathode in quasi‐solid SIBs is also evaluated. The quasi‐solid SIBs with the C‐FeHCF cathode exhibit excellent electrochemical performance, delivering an initial discharge capacity of 106.5 mAh g−1 at 5 C and high capacity retention of 89.8% over 1200 cycles. This work opens new insights into the design and development of advanced cathode materials for SIBs and the beyond.

Abstract Comprehensive research is conducted on the design and control of the unmanned systems for electric vehicles. The environmental risk prediction and avoidance system is divided into the prediction part and the avoidance part. The prediction part is divided into environmental perception, environmental risk assessment, and risk prediction. In the avoidance part, according to the risk prediction results, a conservative driving strategy based on speed limit is adopted. Additionally, the core function is achieved through the target detection technology based on deep learning algorithm and the data conclusion based on deep learning method. Moreover, the location of bounding box is further optimized to improve the accuracy of SSD target detection method based on solving the problem of imbalanced sample categories. Software such as MATLAB and CarSim are applied in the system. Bleu-1 was 67.1, bleu-2 was 45.1, bleu-3 was 29.9 and bleu-4 was 21.1. Experiments were carried out on the database flickr30k by designing the algorithm. Bleu-1 was 72.3, bleu-2 was 51.8, bleu-3 was 37.1 and bleu-4 was 25.1. From the comparison results of the simulations of unmanned vehicles with or without a system, it can provide effective safety guarantee for unmanned driving.

Apparently, plant leaf surface particulate matter (PM) can be effectively removed by rainfall, leaving space on the leaf surface to adsorb and retain PM again. At present, most of the relevant studies adopt the method of artificial rainfall simulation to quantify rainfall characteristics in terms of rainfall intensity, and mostly focus on one category of plants. Studies of rainfall intensity on different categories of plants are lacking. Therefore, in this study, common urban greenery plants were classified into four categories, namely, trees, shrubs, herbs, and aquatic plants. Artificial rainfall was used and three different gradients of rainfall intensity, 30 mm/h, 45 mm/h and 60 mm/h, were set. The mass of per unit leaf area PM removal was calculated using the elution weighing method and the filter membrane method was used to classify the PM into three particle sizes: coarse (10–100-μm), fine (3–10-μm) and ultrafine (0.4–3-μm). It was devoted to investigating the differences in the effect of rainfall intensity on the removal of PM from the leaf surfaces of different categories of common urban greenery. The results showed that the removal of coarse particles by rainfall was the highest under different rainfall intensities. At the same time, the removal effects of rainfall on leaf surface PM of herbs were the highest under different rainfall intensity, while that of trees was the lowest. Among the same category of plants, Salix matsudana had better particle retention capacity among trees, Buxus sinica among shrubs, Poa pratensis among herbs, and Acorus calamus among aquatic plants. In addition, all tested plants had the highest mass of PM removed from leaf surface units at high rainfall intensity (60 mm/h). However, at a higher rainfall intensity (45 mm/h), the mass of PM on plant unit leaf surface removed was lower than the minimum rainfall intensity (30 mm/h). The results of the above study can provide a basis and theoretical support for the selection of species for urban green space restoration, as well as a reference for the establishment of urban cleaning systems from the perspective of the relationship between rainfall intensity and PM on plant leaf surfaces.

Wetland ecosystem, with their precious natural resources and important ecological functions, is an integral part of the global ecosystem. Preferential flow is a form of water and solute transport that is widely present in all types of soils and has a great impact on nutrient transport and environmental pollution in soils. In this paper, we observe the phenomenon of preferential flow within a wetland ecosystem and discuss the possible effects of preferential flow within a wetland on the wetland ecosystem as a background. We conducted dye tracing experiments outdoors. The preferential flow was qualitative analysis using soil composition. It was found that two types of preferential flow existed in the experimental area, namely finger flow and macropore flow. Quantitative analysis of the preferential flow was performed using PS and Image-Pro Plus software to obtain the intensity data of the preferential flow. The results show that the preferential flow phenomenon in the experimental area is obvious and the preferential-flow intensity data is high. We also found a clear correlation between initial soil–water content, which is an environmental factor characteristic of wetlands, and the preferential-flow data (p = 0.04

Though solar cells are one of the promising technologies to address the energy crisis, this technology is still far from commercialization. Thermoelectric materials offer a novel opportunity to convert energy between thermal and electrical aspects, which show the feasibility to improve the performance of solar cells via heat management and light harvesting. Polymer–inorganic thermoelectric nanocomposites consisting of inorganic nanomaterials and functional organic polymers represent one kind of advanced hybrid nanomaterials with tunable optical and electrical characteristics and fascinating interfacial and surface chemistry. During the past decades, they have attracted extensive research interest due to their diverse composition, easy synthesis, and large surface area. Such advanced nanomaterials not only inherit low thermal conductivity from polymers and high Seebeck coefficient, and high electrical conductivity from inorganic materials, but also benefit from the additional interface between each component. In this review, we provide an overview of interfacial chemistry engineering and electrical feature of various polymer–inorganic thermoelectric hybrid nanomaterials, including synthetic methods, properties, and applications in thermoelectric devices. In addition, the prospect and challenges of polymer–inorganic nanocomposites are discussed in the field of thermoelectric energy.

Graphene is a promising platform for configurable terahertz (THz) devices due to its reconfigurability, but most researches focus on its electrical tunability. Here, we propose a graphene-based THz metasurface comprised of graphene cut-wire arrays for magnetic manipulation of the THz wave. With the external magnetostatic field applied, the resonant currents of the graphene cut-wire can be effectively affected by the Lorentz force, leading to an evident tuning of the response of the metasurface. The simulated results fully demonstrate that the resonance frequencies of the graphene THz metasurface can be efficiently modulated under a vertical magnetostatic field bias, resulting in the manipulation of the transmittance and phase of the THz wave. As a new method of the tunable THz metasurface, our structure shows promising applications in the THz regime, including the ultracompact THz modulators and magnetic field sensors.

Summary: Oxidation of formate to CO2 is catalyzed via the donation of electrons from formate dehydrogenase (FDH) to nicotinamide adenine dinucleotide (NAD+), and thus the charge transport characteristics of FDH become essential but remain unexplored. Here, we investigated the charge transport through single-enzyme junctions of FDH using the scanning tunneling microscope break junction technique (STM-BJ). We found that the coupling of NAD+ with FDH boosts the charge transport by ∼2,100%, and the single-enzyme conductance highly correlates with the enzyme activity. The combined flicker noise analysis demonstrated the switching of the coenzyme-mediated charge transport pathway and supported by the significantly reduced HOMO-LUMO gap from calculations. Site-specific mutagenesis analysis demonstrated that FDH-NAD+ stably combined own higher bioactivity and boosts charge transport, and the coupling has been optimized via the natural selection. Our work provides evidence of hydrogen bond coupling in bioactivity but also bridges the charge transport through single-enzyme junctions and enzyme activities. : Analytical Chemistry; Biotechnology; Molecular Biology Subject Areas: Analytical Chemistry, Biotechnology, Molecular Biology

This paper focuses on planning a three-dimensional (3-D) path for the autonomous underwater vehicle in ocean environment with complicated static and dynamic obstacles as well as the ocean current. Imitating the principle of natural flow avoiding rocks, we develop a submerged path planning method based on improved interfered fluid dynamical system (IIFDS). In view of the particular feature of ocean environment, the obstacles and ocean current are modeled first. The flow field weight coefficient is then proposed to add the current into the confluence of IIFDS, so that the planned path could make use of the current. In order to obtain the energy-optimal path, the improved genetic algorithm whose mutation operator is modified by grey wolf optimizer is proposed to optimize the repulsive and tangential reaction coefficient, tangential direction coefficient, and flow field weight coefficient. Furthermore, a reverse-avoidance strategy is applied to real-time path planning to avoid dynamic obstacles, combined with IIFDS. Finally, the good performance of our proposed method is verified by simulations in various scenarios.

Accurate prediction of remaining useful life (RUL) of lithium-ion battery plays an increasingly crucial role in the intelligent battery health management systems. The advances in deep learning introduce new data-driven approaches to this problem. This paper proposes an integrated deep learning approach for RUL prediction of lithium-ion battery by integrating autoencoder with deep neural network (DNN). First, we present a multi-dimensional feature extraction method with autoencoder model to represent battery health degradation. Then, the RUL prediction model-based DNN is trained for multi-battery remaining cycle life estimation. The proposed approach is applied to the real data set of lithium-ion battery cycle life from NASA, and the experiment results show that the proposed approach can improve the accuracy of RUL prediction.

A series of supported phosphotungstic acid (H3PW12O40, HPW) catalysts, including HPW/β, HPW/Sn-β, HPW/H-Y, HPW/H-ZSM-5, HPW/USY, HPW/ReUSY, and HPW/SBA-15, were prepared using an impregnation method for alcoholysis of fructose to ethyl levulinate in ethanol. Among these catalysts, HPW/H-ZSM-5 showed the highest catalytic activity, and the yield of ethyl levulinate from fructose increased with increasing phosphotungstic acid loading. The yield of ethyl levulinate reached 43.1% at 160 °C for 2 h over 20 wt.% HPW/H-ZSM-5, and the solid catalyst could be reused at least three times. EL yields of 19.1%, 27.3%, 37.4%, and 8.7% could be obtained from glucose, sucrose, inulin, and cellulose, respectively. Furthermore, the catalysts were characterized by BET surface area, X-ray diffraction, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy. HPW/H-ZSM-5 showed good catalytic activity for the direct production of ethyl levulinate from fructose.

The article presents a research on cross-plane transport in a single-molecule two-dimensional van der Waals heterojunction. Topics discussed include Two-dimensional van der Waals heterojunctions (2D-vdWHs) stacked from atomically thick 2D materials are predicted to be a diverse class of electronic materials with unique electronic properties; and development in cross-plane break junction technique, combined with density functional theory calculations.

A series of metal-modified phosphotungstates were prepared and performed for direct synthesis of ethyl levulinate from fructose in ethanol. Considering the cost of catalysts, catalytic activity of catalysts, and easy separation of catalysts together, K-HPW-1 was chosen as the most suitable catalyst for synthesis of ethyl levulinate from fructose. A high ethyl levulinate yield of 64.6 mol% was obtained at 150 °C within 2 h in ethanol. The introduction of low polar toluene as a co-solvent improved the yield of ethyl levulinate to 68.7 mol%. The recovered catalyst remained high activity with the yield of ethyl levulinate converted from fructose above 50 mol% after being used five times. Moreover, the generality of the catalyst was further demonstrated by glucose, sucrose, inulin, and cellulose with ethyl levulinate yielding 14.5, 35.4, 52.3, and 14.8 mol%, respectively. [ABSTRACT FROM AUTHOR]

The article presents a new van der Waals heterojunction strategy to fabricate layer-by-layer single-molecule switches.It mentions that the method involves incorporating a single molecule between two single-layer graphene electrodes, which enables the fabrication of smaller devices, including the ability to control conformation and cross-plane charge transport, resulting in reversible switches.