mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Computation method and control strategy of rotating separation flows in hydraulic machinery

Rotating separation flow(RSF)in hydraulic machinery is characterized by the large flow separations and complex vortical structures induced by the effects of strong rotation, large curvature and multiple wall surfaces, and conducting efficient engineering computation and putting forward effective control strategy for the RSF are important topics in the inner flow theory. To meet these engineering requirements, the studies on computational method and control strategy of the RSF are conducted in this paper. In terms of the computational method, the time-scale-driven(TSD)hybrid unsteady Reynolds-averaged Navier-Stokes/large eddy simulation(URANS/LES)modelling strategy is clarified, and an adaptive TSD hybrid model is established based on the RSF characteristics in hydraulic machinery, thereby avoiding the problem of non-monotonic grid convergence and improving the robustness. Besides, a novel vortex-feature-driven idea suitable for the RSF is further developed inspired by it. In terms of the control strategy, the secondary flow generation mechanism in a rotor domain is revealed, and the relationship between natural secondary flows and blade loading distributions is grasped. On the basis of it, an active control strategy with general significance is proposed, and a general alternate loading technique(GALT)is established. Both aspects can provide generalized paradigms with expandable potential, which are of benefit to the efficient computation and effective control of the RSF in hydraulic machinery.
A Liutex-based subgrid stress model for large-eddy simulation

The concept of vortex is crucial in both understanding and modeling of turbulence. For large eddy simulation(LES), the effect of small-scale eddies onto the large scales or the resolved flow field is modeled by subgrid stress models. Even though the rotating motions of fluids, i.e., vortices or eddies are central in developing turbulent models, vortex identification methods are seldom used in these models. In this study, we develop a new subgrid model based on the Liutex vector, a new quantity introduced to decompose fluid motions into rigid rotation, pure shear and stretching, and thus identify vortices. The new model is then applied in a decaying homogeneous isotropic turbulence(DHIT)and a turbulent channel flow at Reynolds number Re_t = 180. It is shown that the new model can predict accurate energy spectra compared with experiments in DHIT and give a well-matched velocity profile in turbulent channel flow without changing the form of the model. Future directions include improvement of the Liutex based model, for example developing anisotropic subgrid models, and its applications in various turbulent flows.
Flexible micro-supercapacitors fabricated from MnO_2 nanosheet/graphene composites with black phosphorus additive

Supercapacitors are widely used for powering flexible/wearable electronics owing to their excellent charge storage capabilities. In this study, MnO_2 nanosheets were grown on the surface of graphene using a simple water bath method to prepare graphene/MnO_2 composites for fabricating supercapacitors. In addition, two-dimensional black phosphorus was introduced as an additive into the electronic ink based on the as-prepared graphene/MnO_2 composites. The characterization and electrochemical analyses results showed that adding black phosphorus considerably improved the capacitive performance of the material, yielding a high specific capacitance of 241.5 F g~(-1) at 0.1 A g~(-1) and an impressive rate capability improvement from 52.5% to 80.3%. Then the microsupercapacitor having an area-specific capacitance of 20.15 mF cm~(-2) at a scanning rate of 2 mV s~(-1) was utilized to demonstrate the practical applicability of this material. To further evaluate the practical applicability of this micro-supercapacitor, the micro-supercapacitor was integrated with a flexible thin-film pressure sensor on paper and cloth through screen printing.
Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution

Impervious surface mapping is essential for urban environmental studies. Spectral Mixture Analysis(SMA)and its extensions are widely employed in impervious surface estimation from medium-resolution images. For SMA, inappropriate endmember combinations and inadequate endmember classes have been recognized as the primary reasons for estimation errors. Meanwhile, the spectral-only SMA, without considering urban spatial distribution, fails to consider spectral variability in an adequate manner. The lack of endmember class diversity and their spatial variations lead to over/underestimation. To mitigate these issues, this study integrates a hierarchical strategy and spatially varied endmember spectra to map impervious surface abundance, taking Wuhan and Wuzhou as two study areas. Specifically, the piecewise convex multiple-model endmember detection algorithm is applied to automatically hierarchize images into three regions, and distinct endmember combinations are independently developed in each region. Then, spatially varied endmember spectra are synthesized through neighboring spectra using the distance-based weight. Comparative analysis indicates that the proposed method achieves better performance than Hierarchical SMA and Fixed Fourendmembers SMA in terms of MAE, SE, and RMSE. Further analysis suggests that the hierarchical strategy can expand endmember class types and considerably improve the performance for the study areas in general, specifically in less developed areas. Moreover, we find that spatially varied endmember spectra facilitate the reduction of heterogeneous surface material variations and achieve the improved performance in developed areas.
Network Element Placement for Space-Air- Ground Integrated Network: A Tutorial

With the demand for Internet connectivity in remote areas, the space-air-ground integrated network(SAGIN)was proposed to achieve ubiquitous coverage and enhance service capabilities of extant terrestrial networks. The paradigm of virtual network element placement(NEP)is applied into SAGIN. It can save energy and operating costs by placing specific network elements(NEs)as software instances. In addition, it helps to provide services in end-to-end networks with its ability to allocate and manage resources flexibly. However, NEP faces some challenges in SAGIN. The network topologies can be dynamic, and links such as the satellite-to-ground and air-to-ground ones are prone to fail. These will make NEP management more complicated. Moreover, the static NEP schemes are hard to accommodate the time-varying traffic. In this context, this work explains the NEP problem in SAGIN from three aspects, i.e., the SAGIN radio access network(RAN), the SAGIN core network(CN), and the SAGIN barrier network(BN). First, the physical and networking architectures of SAGIN are introduced. Then the status of the network element placement and corresponding challenges are described from these two aspects. Finally, this paper discusses future research directions and key technical challenges.
DeepNoise: Signal and Noise Disentanglement Based on Classifying Fluorescent Microscopy Images via Deep Learning

The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolved during experiments: the interferential technical noises caused by systematic errors (e.g., temperature, reagent concentration, and well location) are always mixed up with the real biological signals, leading to misinterpretation of any conclusion drawn. Here, we reported a mean teacher-based deep learning model (DeepNoise) that can disentangle biological signals from the experimental noises. Specifically, we aimed to classify the phenotypic impact of 1108 different genetic perturbations screened from 125,510 fluorescent microscopy images, which were totally unrecognizable by the human eye. We validated our model by participating in the Recursion Cellular Image Classification Challenge, and DeepNoise achieved an extremely high classification score (accuracy: 99.596%), ranking the 2nd place among 866 participating groups. This promising result indicates the successful separation of biological and technical factors, which might help decrease the cost of treatment development and expedite the drug discovery process.
Atomically isolated Pd sites within Pd-S nanocrystals enable trifunctional catalysis for direct,electrocatalytic and photocatalytic syntheses of H_2O_2

Although high-efficiency production of hydrogen peroxide (H_2O_2) can be realized separately by means of direct,electrochemical,and photocatalytic synthesis,developing versatile catalysts is particularly challenging yet desirable.Herein,for the first time we reported that palladium-sulphur nanocrystals (Pd-S NCs) can be adopted as robust and universal catalysts,which can realize the efficient O_2 conversion by three methods.As a result,Pd-S NCs exhibit an excellent selectivity (89.5%) to H_2O_2 with high productivity (133.6 mol·kg_(cat)~(-1)·h~(-1)) in the direct synthesis,along with the significantly enhanced H_2O_2 production activity and stability via electrocatalytic and photocatalytic syntheses.It is demonstrated that the isolated Pd sites can enhance the adsorption of O_2 and inhibit its O-O bond dissociation,improving H_2O_2 selectivity and reducing H_2O_2 degradation.Further study confirms that the difference in surface atom composition and arrangement is the key factor for different ORR mechanisms on Pd NCs and Pd-S NCs.
Hybridized triboelectric-electromagnetic nanogenerators and solar cell for energy harvesting and wireless power transmission

Energy harvesting and power transmission is a significant challenge for the self-powered technologies towards mobile electronic devices.Here,we propose a hybridized energy harvester to complement each other's strengths for simultaneously scavenging multiple types of energy and then wirelessly transmit the power.The harvester consists of electromagnetic-triboelectric nanogenerator units for collecting rotational energy and a commercial water-proof flexible solar cell.At a rotation rate of 500 rpm,the output current of electromagnetic-triboelectric nanogenerator units can reach about 630 mA through energy management.Moreover,the power harvested by hybridized energy harvester can be wirelessly transmitted up to a distance of about 100 cm in real time to charge mobile phone,anemometer,and hygrometer based on self-resonant coils.The hybridized energy harvester with wireless power transmission has potential applications in large-scale energy collection,long-distance wireless power transmission and sustainably driving mobile electronic devices.
Carbothermal shock enabled facile and fast growth of carbon nanotubes in a second

Carbon nanotubes (CNTs) hold great promise in many fields because of their unique structures and properties.However,the preparation of CNTs generally involves cumbersome equipment and time-consuming processes.Here,we report an ultra-fast carbothermal shock (CTS) approach for synthesizing CNTs with a simple homemade setup by employing Joule heating of a carbon substrate.Carbonized silk fabric (CSF) loaded with transition metal salts in ethanol solution was used as the substrate,which was treated with a pulse voltage of 40 V for only 50 ms and then covered with uniform CNTs grown with bimetallic alloy catalyst nanoparticles (diameter:~ 9 nm).The temperature ramp rate is as high as 105 K/s.The as-obtained sample has a unique fluffy structure similar to the trichobothrium of spiders,endowing it versatile applications such as airflow sensors or air filters.The CTS technique presents an easy-accessible and highly efficient approach for synthesizing CNTs,which may be also applied in synthesizing other nanomaterials.
Exploring ternary organic photovoltaics for the reduced nonradiative recombination and improved efficiency over 17.23% with a simple large-bandgap small molecular third component

Ternary strategy is one of the most effective methods to further boost the power conversion efficiency (PCE) of organic photovoltaic cells (OPVs). In terms of high-efficiency PM6:Y6 binary systems, there is still room to further reduce energy loss (Eloss) through regulating molecular packing and aggregation by introducing a third component in the construction of ternary OPVs. Here we introduce a simple molecule BR1 based on an acceptor-donor-acceptor (A-D-A) structure with a wide bandgap and high crystallinity into PM6:Y6-based OPVs. It is proved that BR1 can be selectively dispersed into the donor phase in the PM6:Y6 and reduce disorder in the ternary blends, thus resulting in lower Eloss,non-rad and Eloss. Furthermore, the mechanism study reveals well-develop phase separation morphology and complemented absorption spectra in the ternary blends, leading to higher charge mobility, suppressed recombination, which concurrently contributes to the significantly improved PCE of 17.23% for the ternary system compared with the binary ones (16.21%). This work provides an effective approach to improve the performance of the PM6:Y6-based OPVs by adopting a ternary strategy with a simple molecule as the third component.
Underlying solvent-based factors that influence permanent porosity in porous liquids

Porous liquids (PLs) offer the potential to combine the ready handling and mature industry status of liquid absorbents, with the high permanent porosity of metal organic frameworks. To be functional, these nanocomposites need to satisfy a number of performance parameters, such as stability and viscosity of the porogen-solvent combination, avoiding solvent penetration into metal organic framework (MOF) pores, suitable capacities, and kinetics for gas sorption. In this work, we systematically investigate the component materials to elucidate the parametric space where stable photoluminescence (PL) can be generated. In this situation, deeper conclusions were able to be drawn with regard to the influence of hydrophobicity/philicity on the properties of the resulting nanocomposites. Zeolitic imidazolate frameworks (ZIFs) were combined with a range of solvents varying in steric bulk, to deliver CO_2 sorption capacities as high as 4.2 mmol·g~(-1) at 10 bar. These findings may have broader implications for future investigations of this tantalising field of nanocomposites.
Intrinsically scale-free ferroelectricity in two-dimensional M2X2Y6

Discovery of novel two-dimensional (2D) ferroelectric materials and understanding the mechanism are of vital importance for the design of nanoscale ferroelectric devices. Herein, we report the distinct geometric evolution mechanism of the newly reported M2Ge2Y6 monolayers and find out a large group of 2D ferroelectric candidates based on this mechanism. The origination of the ferroelectricity of M2Ge2Y6 is the vertical displacement of Ge-dimer in the same direction driven by a soft phonon mode of the centrosymmetric configuration. Interestingly, we find another centrosymmetric configuration which is dynamically stable but higher in energy comparing with the ferroelectric phase. The metastable centrosymmetric phase of M2Ge2Y6 monolayers allows a new two-step ferroelectric switching path and may induce novel domain behaviors. Moreover, the ferroelectric M2Ge2Y6 monolayers exhibit independently switchable dipoles and maintain their ferroelectricity after contacting with graphene electrodes, indicating their high application potentials in high-density storage. Furthermore, 16 ferroelectric (FE) M2Ge2Y6 and 65 potential FE M2Sn2Y6 monolayers are identified through high-throughput calculations. Our findings provide a new strategy for future discovery of novel 2D ferroelectric materials and also platforms for experimental design of related functional devices.
THz trapped ion model and THz spectroscopy detection of potassium channels

Advanced molecular dynamics (MD) simulation and infrared (IR) spectroscopy have been widely adopted to reveal the detailed dynamic process of high-speed selective permeability of potassium channels. Yet these MD simulations cannot avoid the choice of empirical molecular force fields and high transmembrane voltages (as driving electric fields for ions) far exceeding physiological levels. Moreover, the IR spectroscopy method usually requires isotope labels for carbonyl groups of the channels, which may change the original permeation process. Here, we build the terahertz (THz) trapped ion model for the selectivity filter (SF) of potassium channels KcsA based on the density functional theory (DFT) calculation of ion potentials. In this model, the zero-point energy of trapped ions and quantum tunneling effect provide the physical basis for near diffusion limited permeation rates of ions and explain the high driving electric field in MD simulations. Quantitative calculations of zero-point energy and tunneling probability show that the quantum effect assisted knock-on mechanism may help to realize the physiological functions of potassium channels. Furthermore, based on the trapped ion model, we calculated the ion decoherence timescale under the influence of protein environmental noise. We use the quantum optics method to describe the interaction between THz waves and the trapped ion. Then the novel THz spectroscopy approaches through the THz resonance fluorescence and the intense field non-resonant effect are presented theoretically. These are expected to be isotope label-free detective methods of the rapid ion permeation dynamics.
Defect-induced deposition of manganese oxides on hierarchical carbon nanocages for high-performance lithium-oxygen batteries

The cathode of lithium-oxygen(Li-O_2)batteries should have large space for high Li_2O_2 uptake and superior electrocatalytic activity to oxygen evolution/reduction for long lifespan. Herein, a high-performance MnO_x/hCNC cathode was constructed by the defect-induced deposition of manganese oxide(MnO_x)nanoparticles on hierarchical carbon nanocages(hCNC). The corresponding Li-O_2 battery(MnO_x/hCNC@Li-O_2)exhibited excellent electrocatalytic activity with the low overpotential of 0.73-0.99 V in the current density range of 0.1-1.0 A·g~(-1). The full discharge capacity and cycling life of MnO_x/hCNC@Li-O_2 were increased by ~86.7% and ~91%, respectively, compared with the hCNC@Li-O_2 counterpart. The superior performance of MnO_x/hCNC cathode was ascribed to(i)the highly dispersed MnO_x nanoparticles for boosting the reversibility of oxygen evolution/reduction reactions,(ii)the interconnecting pore structure for increasing Li_2O_2 accommodation and facilitating charge/mass transfer, and(iii)the concealed surface defects of hCNC for suppressing side reactions. This study demonstrated an effective strategy to improve the performance of Li-O_2 batteries by constructing cathodes with highly dispersed catalytic sites and hierarchical porous structure.
Ultrasensitive determination of intracellular hydrogen peroxide by equipping quantum dots with a sensing layer via self-passivation

Abnormal expression of hydrogen peroxide(H_2O_2)indicates the disorder of cell functions and is able to induce the occurrence and deterioration of numerous diseases. However, limited by its low concentration under pathophysiological conditions, intracellular H_2O_2 is still difficult to be determined to date. Herein, to achieve sensitive quantification of H_2O_2 in cells, CIS/ZnS/ZnS quantum dots(CIS/d-ZnS QDs)are retrofitted with ZnO shells via self-passivation. Different from the traditional self-passivation of QDs, self-passivation of CIS/d-ZnS QDs is realized facilely without the assistance of additional cation ions, which improves optical properties of QDs and equips the QDs with a sensing layer. As a result, the CIS/d-ZnS/ZnO QDs exhibit enhanced fluorescence emission and stability. Relying on the decomposition of ZnO and ZnS shells in the presence of H_2O_2, aggregated QDs reveal exciton energy transfer effect, resulting in fluorescence quenching. On a basis of this principle, a fluorescence H_2O_2 sensor is further established with the CIS/d-ZnS/ZnO QDs. To be noted, since the equipped ZnO shells are more susceptible to H_2O_2 than original ZnS shells, analytical performance of the fluorescence sensor is remarkably promoted by the self-passivation of QDs. Accordingly, H_2O_2 can be measured in 5 orders of magnitude with a limit of detection(LOD)of 0.46 nM. Furthermore, because the ZnO shells improve H_2O_2-responsive selectivity and sensitivity, variation of H_2O_2 in cells can also be quantified with the CIS/d-ZnS/ZnO QDs. In this work, sensitive detection of intracellular H_2O_2 is enabled by equipping QDs with a sensing layer, which provides an alternative perspective of functionalizing nanomaterials for analytical applications.
Ultradurable, freeze-resistant,and healable MXene-based ionic gels for multi-functional electronic skin

Hydrogel is a potential matrix material of electronic-skins(E-skins)because of its excellent ductility, tunability, and biocompatibility. However, hydrogel-based E-Skins will inevitably lose their sensing performance in practical applications for water loss, physical damage, and ambient interferences. It remains a challenge to manufacture highly durable gel-based E-skins. Herein, an E-Skin is fabricated by introducing ionic liquids(ILs)into MXene-composited binary polymer network. The obtained ionic gel shows excellent mechanical properties, strong adhesion, and superior tolerance to harsh environments. The E-skin exhibits high sensitivity to both strain and pressure in a wide range of deformations, which enables a monitoring function for various human motions and physiological activities. Importantly, the E-skin shows consistent electrical response after being stored in the open air for 30 days and can be quickly healed by irradiation with 808 nm near-infrared light, originating from the photo-thermal effect induced self-healing acceleration. It is noteworthy that the E-skin also reveals a highly sensitive perception of temperature and near-infrared light, displaying the promising potential applications in the multifunctional flexible sensor.
Ag_(24)Au cluster decorated mesoporous Co_3O_4 for highly selective and efficient photothermal CO_2 hydrogenation

Photothermal carbon dioxide hydrogenation represents a promising route to reduce the emission of greenhouse gas CO_2 and produce value-added chemicals, but the selectivity and stability of photothermal catalysts need to be improved. Herein, we report the rational fabrication of well-defined Ag_(24)Au cluster decorated highly ordered nanorod-like mesoporous Co_3O_4(Ag_(24)Au/meso-Co_3O_4)for highly efficient and selective CO_2 hydrogenation. The orderly assembled meso-Co_3O_4 nanorods were prepared via a nanocasting method, offering large surface area and abundant active sites for CO_2 adsorption and conversion. Moreover, the catalytic activity and selectivity were further improved by molecule-like Ag_(24)Au cluster decoration and reaction temperature optimization. The Ag_(24)Au/meso-Co_3O_4 composite catalyst exhibited an ultrahigh CH_4 yield rate of 204 mmol·g~(-1)·h~(-1) and a greatly improved CH_4 selectivity of 82% for CO_2 hydrogenation, significantly higher than those of pristine meso-Co_3O_4 catalyst. The mechanism of the photothermal catalytic performance improvement was verified by CO_2 temperature-programmed desorption and time-resolved transient photoluminescence, revealing that CO_2 molecules underwent a vigorous adsorption and rapid activation process over Ag_(24)Au/meso-Co_3O_4. The hot electrons created by the localized surface plasmon resonance effect of Ag_(24)Au clusters facilitated the charge transfer for subsequent multi-electron CO_2 hydrogeneration processes, resulting in a significant increase in the productivity and selectivity for CO_2-to-CH_4 conversion. This work suggests that the rational coupling of well-defined metal atom clusters and ordered transition metal compound nanostructures could open a new avenue towards photo-induced green chemistry processes for efficient CO_2 recycling and reutilization.