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Abstract Riemann surfaces inspired chemists to design and synthesize such multidimensional curved carbon architectures. It has been predicted that carbon nanosolenoid materials with Riemann surfaces have unique structures and novel physical properties. Here we report the first synthesis of a nitrogen-doped carbon nanosolenoid (N-CNS) using bottom-up approach with a well-defined structure. N-CNS was obtained by a rational Suzuki polymerization, followed by oxidative cyclodehydrogenation. The successful synthesis of N-CNS was fully characterized by GPC, FTIR, solid-state 13C NMR and Raman techniques. The intrinsic single-strand molecular structures of N-CNS helices can be clearly resolved using low-dose integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM) technique. Possessing unique structural and physical properties, this long π-extended polymer N-CNS can provide new insight towards bottom-up syntheses of curved nanoribbons and potential applications as a metal-free photocatalyst for visible-light-driven H2 evolution and highly efficient photocatalyst for photoredox organic transformations.

Fabrication of large π-conjugated carbon nanosolenoid materials with helicoid topology remains a challenge. Here the authors demonstrate synthesis of a metal-free π-extended carbon nanosolenoid material with a helical structure, exhibiting unique photophysical and magnetic properties.

Autonomous vehicles are gaining popularity, and the development of automatic parking systems is a fundamental requirement. Detecting the parking slots accurately is the first step towards achieving an automatic parking system. However, modern parking slots present various challenges for detection task due to their different shapes, colors, functionalities, and the influence of factors like lighting and obstacles. In this comprehensive review paper, we explore the realm of vision-based deep learning methods for parking slot detection. We categorize these methods into four main categories: object detection, image segmentation, regression, and graph neural network, and provide detailed explanations and insights into the unique features and strengths of each category. Additionally, we analyze the performance of these methods using three widely used datasets: the Tongji Parking-slot Dataset 2.0 (ps 2.0), Sejong National University (SNU) dataset, and panoramic surround view (PSV) dataset, which have played a crucial role in assessing advancements in parking slot detection. Finally, we summarize the findings of each method and outline future research directions in this field.

Objectives: To investigate the predictive factors for successful recanalization based on digital subtraction angiography and three-dimensional T1W sampling perfection with application-optimized contrasts using different flip angle evolutions (3D T1-SPACE) high-resolution magnetic resonance imaging (MRI) signal features.Methods: Consecutive internal carotid artery occlusion cases with ipsilateral ischemic stroke refractory to therapy who visited our institution between February 2017 and August 2020 were retrospectively analyzed. Epidemiology, symptomatology, imaging morphology on angiography and MRI, peri-procedural complications, technical success rate, and follow-up results were summarized. Factors related to technical success were analyzed using univariate and multivariate analyses.Results: In total, 75 cases (53 men, mean age 57.51 ± 9.71 years) were included. The total successful recanalization rate was 72.00% (54/75), with a complication rate of 13.33% (9/75). Through multivariate analysis, first ischemic stroke in

The oxygen evolution reaction (OER) is a crucial reaction in water splitting, metal–air batteries, and other electrochemical conversion technologies. Rationally designed catalysts with rich active sites and high intrinsic activity have been considered as a hopeful strategy to address the sluggish kinetics for OER. However, constructing such active sites in non-noble catalysts still faces grand challenges. To this end, we fabricate a Ni2P@Fe2P core–shell structure with outperforming performance toward OER via chemical transformation of rationally designed Ni-MOF hybrid nanosheets. Specifically, the Ni-MOF nanosheets and their supported Fe-based nanomaterials were in situ transformed into porous Ni2P@Fe2P core–shell nanosheets composed of Ni2P and Fe2P nanodomains in homogenous dispersion via a phosphorization process. When employed as the OER electrocatalyst, the Ni2P@Fe2P core–shell nanosheets exhibits excellent OER performance, with a low overpotential of 238/247 mV to drive 50/100 mA cm−2, a small Tafel slope of 32.91 mV dec−1, as well as outstanding durability, which could be mainly ascribed to the strong electronic interaction between Ni2P and Fe2P nanodomains stabilizing more Ni and Fe atoms with higher valence. These high-valence metal sites promote the generation of high-active Ni/FeOOH to enhance OER activity.

Wearable self-powered electronics receive considerable attention, but development is hindered by bulky designs, energy storage systems, and safety issues. Here the authors demonstrate a flexible solar-charging integrated unit based on printed magnesium ion aqueous asymmetric supercapacitors.

The oxygen evolution reaction (OER) occurs at the anode in numerous electrochemical reactions and plays an important role due to the nature of proton-coupled electron transfer. However, the high voltage requirement and low stability of the OER dramatically limits the total energy converting efficiency. Recently, electrocatalysts based on multi-metal oxyhydroxides have been reported as excellent substitutes for commercial noble metal catalysts due to their outstanding OER activities. However, normal synthesis routes lead to either the encapsulation of excessively active sites or aggregation during the electrolysis. To this end, we design a novel core–shell structure integrating CoMoO4 as support frameworks covered with two-dimensional γ-FeOOH nanosheets on the surface. By involving CoMoO4, the electrochemically active surface area is significantly enhanced. Additionally, Co atoms immerge into the γ-FeOOH nanosheet, tuning its electronic structure and providing additional active sites. More importantly, the catalysts exhibit excellent OER catalytic performance, reducing overpotentials to merely 243.1 mV a versus 10 mA cm−2. The current strategy contributes to advancing the frontiers of new types of OER electrocatalysts by applying a proper support as a multi-functional platform.

In order to reduce the interference noise of ESD current signal, wavelet analysis and adaptive Kalman filter are used in the study of ESD current waveform denoising. The numerical solutions of ESD current of human body-metal model are computed by the Adams prediction-calibration algorithm，and a corresponding noisy ESD current signal model is established. The wavelet denoising method performs denoising performance analysis on this model. Aiming at the measured ESD current waveform, the wavelet threshold denoising method is used to preprocess the ESD current waveforms, and obtain more stable observation data. According to the information of the observed data, the adaptive Kalman filter algorithm proposed by Sage-Husa is used to optimize the data processed the wavelet pretreatment data. The results show that the wavelet analysis and adaptive Kalman filter algorithm can effectively reduce the interference noise of the measured ESD current waveform.

Enhancing the water flux while maintaining the high salt rejection of existing reverse osmosis membranes remains a considerable challenge. Herein, we report the use of a porous carbon nitride (C3N4) nanoparticle to potentially improve both the water flux and salt rejection of the state-of-the-art polyamide (PA) thin film composite (TFC) membranes. The organic–organic covalent bonds endowed C3N4 with great compatibility with the PA layer, which positively influenced the customization of interfacial polymerization (IP). Benefitting from the positive effects of C3N4, a more hydrophilic, more crumpled thin film nanocomposite (TFN) membrane with a larger surface area, and an increased cross-linking degree of PA layer was achieved. Moreover, the uniform porous structure of the C3N4 embedded in the ”ridge” sections of the PA layer potentially provided additional water channels. All these factors combined provided unprecedented performance for seawater desalination among all the PA-TFC membranes reported thus far. The water permeance of the optimized TFN membrane is 2.1-folds higher than that of the pristine PA-TFC membrane, while the NaCl rejection increased to 99.5% from 98.0%. Our method provided a promising way to improve the performance of the state-of-art PA-TFC membranes in seawater desalination.

Straw return is an effective measure to increase soil sustainability. However, few studies have examined the effects of different straw return methods on soil structure, soil organic carbon content and maize yield or the potential relationships between those variables. Therefore, we developed a field orientation experiment to study the effects of different straw return methods on soil porosity, soil aggregate stability, the soil organic carbon content and maize yield. Four treatments were established: flat no-tillage with full straw mulching (FM), ridge no-tillage with full straw mulching (LM), rotary tillage with full straw incorporation (LX), and conventional tillage without straw (CK) as the control treatment. Compared with those of the CK treatment, the soil porosities (f) in the FM, LM and LX treatments significantly increased by 6.7%, 8.8% and 7.9%, respectively; the soil aggregate destruction rates (PAD) decreased by 17.3%, 34.3% and 16.9%, respectively. In addition, the FM, LM and LX treatments effectively increased the mean mass diameters (MWDs) of the soil aggregates and the soil organic carbon content. Compared with those in the CK treatment, the three-year average yields in the FM, LM and LX treatments significantly increased by 5.2%, 7.2% and 4.1%, respectively. Moreover, the f, MWD, soil organic carbon content and corn yield were positively correlated. Our study indicates that the LM treatment was most effective in improving soil structure and increasing soil organic carbon content with corn yield. [ABSTRACT FROM AUTHOR]