Phthalocyanine-derived catalysts decorated by metallic nanoclusters for enhanced CO_(2)electroreduction

Electrochemical CO_(2)reduction(CO_(2)RR)over molecular catalysts is a paramount approach for CO_(2)conversion to CO.Herein,we report a novel phthalocyanine-derived catalyst synthesized by a two-step method with a much improved electroconductivity.Furthermore,the catalyst contains both Ni-N4sites and highly dispersed metallic Ni nanoclusters,leading to an increased CO_(2)RR currents by two folds.Isotope labelling study and in situ spectroscopic analysis demonstrate that the existence of metallic Ni nanoclusters is the key factor for the activity enhancement and can shift the CO_(2)RR mechanism from being electron transfer(ET)-limited(forming*COO^(-))to concerted proton-electron transfer(CPET)-limited(forming CO).

Pyridine terminated polyurethane dendrimer/chlorinated butyl rubber nanocomposites with excellent mechanical and damping properties

Due to the special viscoelastic property, traditional rubber with high performance has been widely used in human life and production. However, it is challenging to improve the damping property without sacrificing the extensibility. In this work, a novel type of second-generation polyurethane dendrimer terminated with pyridine(G2-Py) was synthesized by using thiolactone chemistry and subsequently complexed with Zn ions. The structure and morphology of G2-Py were characterized. G2-Py-Zn2+was then mixed with chlorinated butyl rubber(CIIR) by a two-roll mill. A series of CIIR/G2-Py-Zn2+elastomers were obtained through vulcanization. CIIR/G2-Py-Zn2+elastomers could achieve high stretchability(a strain of ~1035%), high mechanical strength(a tensile stress of 7.64 MPa). This was benefitted from the friction between G2-Py and CIIR as well as variety of non-covalent bonds provided by G2-Py-Zn2+,which can dissipate energy to further improve the strength and extensibility. The coordination of Zn2+-pyridine was confirmed by Fourier transform infrared spectroscopy, stress relaxation and cycle tensile test. To further investigate the morphology and damping properties of the elastomers, scanning electron microscopy and dynamic mechanical analysis were performed. CIIR-5 showed the best damping performance with higher tan δ_(max) and wider effective damping temperatures. Therefore, this dendrimer modification technology provides wider applications for CIIR elastomers in daily life.

Improvement of Attributed Scattering Center Extraction by Using SAR Super-Resolution Preprocessing

Synthetic aperture radar(SAR)is able to acquire high-resolution method using the active microwave imaging method.SAR images are widely used in target recognition,classification,and surface analysis,with extracted features.Attribute scattering center(ASC)is able to describe the image features for these tasks.However,sidelobe effects reduce the accuracy and reliability of the estimated ASC model parameters.This paper incorporates the SAR super-resolution into the ASC extraction to improve its performance.Both filter bank and subspace methods are demonstrated for preprocessing to supress the sidelobe.Based on the preprocessed data,a reinforcement based ASC method is used to get the parameters.The experimental results show that the super-resolution method can reduce noise and suppress sidelobe effect,which improve accuracy of the estimated ASC model parameters.

Enhanced inhibitory control during re-engagement processing in badminton athletes:An event-related potential study

Purpose:The purpose of present study was to investigate the impact of sport experience on response inhibition and response re-engagement in expert badminton athletes during the stop-signal task and change-signal task.Methods:A total of 19 badminton athletes and 20 nonathletes performed both the stop-signal task and change-signal task.Reaction times(RTs)and event-related potentials were recorded and analyzed.Results:Behavioral results indicated that badminton athletes responded faster than nonathletes to go stimuli and to change signals,with faster change RTs and change-signal RTs,which take into consideration the variable stimulus onset time mean.During successful change trials in the change-signal task,the amplitudes of the event-related potential components N2 and P3 were smaller for badminton athletes than for nonathletes.Moreover,change-signal RTs and N2 amplitudes as well as change RTs and P3 amplitudes were significantly correlated in badminton athletes.A significant correlation was also found between the amplitude of the event-related potential component N1 and response accuracy to change signals in badminton athletes.Conclusion:Moderation of brain cortical activity in badminton athletes was more associated with their ability to rapidly inhibit a planned movement and re-engage with a new movement compared with nonathletes.The superior inhibitory control and more efficient neural mechanisms in badminton athletes compared with nonathletes might be a result of badminton athletes’ professional training experience.

Stable hydrogen isoscape in precipitation generated using data fusion for East China

The stable hydrogen isotope in precipitation is an effective environmental tracer for climatic and hydrologic studies.However,accurate and high-precision precipitation hydrogen isoscapes are currently unavailable in China.In this study,a data fusion method based on Convolutional Neural Networks(CNN)is used to fuse the hydrogen isotopic composition(δ^(2)H_(p))of observations and isotope-equipped general circulation model(iGCM)simulations.A precipitation hydrogen isoscape with a temporal resolution of monthly and a spatial resolution of 50-60 km is established for East China for the 1969-2017 period.Prior to building the isoscape,the performance of three data fusion methods(DFMs)and two bias correction methods(BCMs)is compared.The results indicate that the CNN fusion method performs the best with a correlation coefficient larger than 0.90 and root mean square error smaller than 10.5‰ when using observation as a benchmark.The fusion methods based on back propagation and long short-term memory neural network perform similarly,while slightly outperforming the bias correction methods.Thus,the CNN method is used to generate the hydrogen isoscape,and the temporal and spatial distribution characteristics of the hydrogen isotope in precipitation are analyzed based on this dataset.The generated isoscape shows similar spatial and temporal distribution characteristics to observations.In general,the distribution pattern of δ^(2)H_(p) is consistent with the temperature effect in northern China,and consistent with the precipitation amount effect in southern China.The trend of the δ^(2)H_(p) time series is consistent with that of observed precipitation and temperature.Overall,the generated isoscape effectively reproduces the observations,and has the characteristics of time continuity and relative spatial regularity,which can provide valuable data support for tracking atmospheric and hydrological processes.

Cybertwin Based Cloud Native Networks

With the emerging applications of the Internet of things,artificial intelligence,and satellite communications,the future network will be featured as the Internet of everything around the globe.The network heterogeneity,applications cloudification,and personalized user services demand a revolutionary change in the network architecture.With the rapid development of cloud native technology,the new network should support heterogeneous networks and personalized quality of services for users.In this paper,we propose a Cybertwinbased cloud native network(CCNN)that merges the radio access network(RAN),the IP bearer network,and the data center network and is based on the cloud native data center network using Kubernetes as a network operating system for unified virtualization of computing,storage,and network resources,unified scheduling and allocation,and unified operation and management.Then,we propose a fully decoupled RAN architecture that can flexibly and efficiently utilize the resource for personlized user services.We also propose a Cybertwin-based management framework built on Kubernetes for integrated networking,computing and storage resource scheduling.Finally,we design an immunology-inspired intrinsic security architecture with zero trust security system and adaptive defense system.The proposed CCNN is a new network architecture expected to address future generation communications and networks challenges.

A Fully-Decoupled RAN Architecture for 6G Inspired by Neurotransmission

While the commercial deployment and promotion of 5G is ongoing,mobile communication networks are still facing three fundamental challenges,i.e.,spectrum resource scarcity,especially for low-frequency spectrum,exacerbated by fragmented spectrum allocation,user-centric network service provision when facing billions of personalized user demands in the era of Internet of everything(IoE),and proliferating operation costs mainly due to huge energy consumption of network infrastructure.To address these issues,it is imperative to consider and develop disruptive technologies in the next generation mobile communication networks,namely 6G.In this paper,by studying brain neurons and the neurotransmission,we propose the fully-decoupled radio access network(FD-RAN).In the FD-RAN,base stations(BSs)are physically decoupled into control BSs and data BSs,and the data BSs are further physically split into uplink BSs and downlink BSs.We first review the fundamentals of neurotransmission and then propose the 6G design principles inspired by the neurotransmission.Based on the principles,we propose the FD-RAN architecture,elastic resource cooperation in FD-RAN,and improved transport service layer design.The proposed fully decoupled and flexible architecture can profoundly facilitate resource cooperation to enhance the spectrum utilization,reduce the network energy consumption and improve the quality of user experience.Future research topics in this direction are envisioned and discussed.