Simulation of Rotating Asymmetric Sideways Forces during Vertical Displacement Events in CFETR

Tokamak plasmas with elongated cross sections are susceptible to vertical displacement events(VDEs),which can damage the first wall via heat flux or electromagnetic(EM)forces.We present a 3D nonlinear reduced magnetohydrodynamic(MHD)simulation of CFETR plasma during a cold VDE following the thermal quench,focusing on the relationship among the EM force,plasma displacement,and the n=1 mode.The dominant mode,identified as m/n=2/1,becomes destabilized when most of the current is contracted within the q=2 surface.The displacement of the plasma current centroid is less than that of the magnetic axis due to the presence of SOL current in the open field line region.Hence,the symmetric component of the induced vacuum vessel current is significantly mitigated.The direction of the sideways force keeps a constant phase approximately compared to the asymmetric component of the vacuum vessel current and the SOL current,which in turn keep in-phase with the dominant 2/1 mode.Their amplitudes are also closely associated with the growth of the dominant mode.These findings provide insights into potential methods for controlling the phase and amplitude of sideways forces during VDEs in the future.

Boosting Lean Electrolyte Lithium-Sulfur Battery Performance with Transition Metals: A Comprehensive Review

Lithium–sulfur(Li–S) batteries have received widespread attention, and lean electrolyte Li–S batteries have attracted additional interest because of their higher energy densities. This review systematically analyzes the effect of the electrolyte-to-sulfur(E/S) ratios on battery energy density and the challenges for sulfur reduction reactions(SRR) under lean electrolyte conditions. Accordingly, we review the use of various polar transition metal sulfur hosts as corresponding solutions to facilitate SRR kinetics at low E/S ratios(< 10 μL mg~(-1)), and the strengths and limitations of different transition metal compounds are presented and discussed from a fundamental perspective. Subsequently, three promising strategies for sulfur hosts that act as anchors and catalysts are proposed to boost lean electrolyte Li–S battery performance. Finally, an outlook is provided to guide future research on high energy density Li–S batteries.

Deep Reinforcement Learning-Based URLLC-Aware Task Offloading in Collaborative Vehicular Networks

Collaborative vehicular networks is a key enabler to meet the stringent ultra-reliable and lowlatency communications(URLLC)requirements.A user vehicle(UV)dynamically optimizes task offloading by exploiting its collaborations with edge servers and vehicular fog servers(VFSs).However,the optimization of task offloading in highly dynamic collaborative vehicular networks faces several challenges such as URLLC guaranteeing,incomplete information,and dimensionality curse.In this paper,we first characterize URLLC in terms of queuing delay bound violation and high-order statistics of excess backlogs.Then,a Deep Reinforcement lEarning-based URLLCAware task offloading algorithM named DREAM is proposed to maximize the throughput of the UVs while satisfying the URLLC constraints in a besteffort way.Compared with existing task offloading algorithms,DREAM achieves superior performance in throughput,queuing delay,and URLLC.

Endogenous Security-Aware Resource Management for Digital Twin and 6G Edge Intelligence Integrated Smart Park

The integration of digital twin(DT)and 6G edge intelligence provides accurate forecasting for distributed resources control in smart park.However,the adverse impact of model poisoning attacks on DT model training cannot be ignored.To address this issue,we firstly construct the models of DT model training and model poisoning attacks.An optimization problem is formulated to minimize the weighted sum of the DT loss function and DT model training delay.Then,the problem is transformed and solved by the proposed Multi-timescAle endogenouS securiTy-aware DQN-based rEsouRce management algorithm(MASTER)based on DT-assisted state information evaluation and attack detection.MASTER adopts multi-timescale deep Q-learning(DQN)networks to jointly schedule local training epochs and devices.It actively adjusts resource management strategies based on estimated attack probability to achieve endogenous security awareness.Simulation results demonstrate that MASTER has excellent performances in DT model training accuracy and delay.

Adaptive Learning-Based Delay-Sensitive and Secure Edge-End Collaboration for Multi-Mode Low-Carbon Power IoT

Multi-mode power internet of things(PIoT)combines various communication media to provide spatio-temporal coverage for low-carbon operation in smart park.Edge-end collaboration is feasible to achieve the full utilization of heterogeneous resources and anti-eavesdropping.However,edge-end collaboration-based multi-mode PIoT faces challenges of mutual contradiction in communication and security quality of service(QoS)guarantee,inadaptability of resource management,and multi-mode access conflict.We propose an Adaptive learning based delAysensitive and seCure Edge-End Collaboration algorithm(ACE_(2))to optimize multi-mode channel selection and split device power into artificial noise(AN)transmission and data transmission for secure data delivery.ACE_(2) can achieve multi-attribute QoS guarantee,adaptive resource management and security enhancement,and access conflict elimination with the combined power of deep actor-critic(DAC),“win or learn fast(WoLF)”mechanism,and edge-end collaboration.Simulations demonstrate its superior performance in queuing delay,energy consumption,secrecy capacity,and adaptability to differentiated low-carbon services.

All Binder-Free Electrodes for High-Performance Wearable Aqueous Rechargeable Sodium-Ion Batteries

Extensive efforts have recently been devoted to the construction of aqueous rechargeable sodium-ion batteries(ARSIBs)for large-scale energy-storage applications due to their desired properties of abundant sodium resources and inherently safer aqueous electrolytes.However,it is still a significant challenge to develop highly flexible ARSIBs ascribing to the lack of flexible electrode materials.In this work,nanocube-like KNiFe(CN)6(KNHCF)and rugby balllike NaTi2(PO4)3(NTP)are grown on carbon nanotube fibers via simple and mild methods as the flexible binder-free cathode(KNHCF@CNTF)and anode(NTP@CNTF),respectively.Taking advantage of their high conductivity,fast charge transport paths,and large accessible surface area,the as-fabricated binder-free electrodes display admirable electrochemical performance.Inspired by the remarkable flexibility of the binder-free electrodes and the synergy of KNHCF@CNTF and NTP@CNTF,a high-performance quasi-solid-state fiber-shaped ARSIB(FARSIB)is successfully assembled for the first time.Significantly,the as-assembled FARSIB possesses a high capacity of 34.21 mAh cm?3 and impressive energy density of 39.32 mWh cm?3.More encouragingly,our FARSIB delivers superior mechanical flexibility with only 5.7%of initial capacity loss after bending at 90°for over 3000 cycles.Thus,this work opens up an avenue to design ultraflexible ARSIBs based on all binder-free electrodes for powering wearable and portable electronics.

Atomic Modulation of 3D Conductive Frameworks Boost Performance of MnO2 for Coaxial Fiber‑Shaped Supercapacitors

Coaxial fiber-shaped supercapacitors are a promising class of energy storage devices requiring high performance for flexible and miniature electronic devices.Yet,they are still struggling from inferior energy density,which comes from the limited choices in materials and structure used.Here,Zn-doped CuO nanowires were designed as 3D framework for aligned distributing high mass loading of MnO2 nanosheets.Zn could be introduced into the CuO crystal lattice to tune the covalency character and thus improve charge transport.The Zn–CuO@MnO2 as positive electrode obtained superior performance without sacrificing its areal and gravimetric capacitances with the increasing of mass loading of MnO2 due to 3D Zn–CuO framework enabling efficient electron transport.A novel category of free-standing asymmetric coaxial fiber-shaped supercapacitor based on Zn0.11CuO@MnO2 core electrode possesses superior specific capacitance and enhanced cell potential window.This asymmetric coaxial structure provides superior performance including higher capacity and better stability under deformation because of sufficient contact between the electrodes and electrolyte.Based on these advantages,the as-prepared asymmetric coaxial fiber-shaped supercapacitor exhibits a high specific capacitance of 296.6 mF cm^−2 and energy density of 133.47μWh cm^−2.In addition,its capacitance retention reaches 76.57%after bending 10,000 times,which demonstrates as-prepared device’s excellent flexibility and long-term cycling stability.

Investigation of Two-Dimensional Ultrasonic Surface Burnishing Process on 7075-T6 Aluminum

A novel two-dimensional ultrasonic surface burnishing process(2D-USBP)is proposed.7075-T6 aluminum samples are processed by a custom-designed 2D-USBP setup.Parameter optimization of 2D-USBP is conducted to determine the best processing strategy of 7075-T6 aluminum.A uniform design method is utilized to optimize the 2D-USBP process.U〔3(133)and 4(72)tables are established to conduct parameter optimization.Burnishing depth,spindle speed,and feed rate are taken as the control parameters.The surface roughness and Vickers hardness are taken as the evaluation indicators.It establishes the active control models for surface quality.Dry wear tests are conducted to compare the wear-resistance of the 2D-USBP treated sample and the original sample.Results show that the machining quality of 2D-USBP is best under 0.24 mm burnishing depth,5000 r/min spindle speed,and 25 mm/min feed rate.The surface roughness of the sample is reduced from 2517.758 to 50.878 nm,and the hardness of the sample surface is improved from 167 to 252 HV.Under the lower load,the wear mechanism of the 2D-USBP treated sample is mainly abrasive wear accompanied by delamination wear,while the wear mechanism of the original sample is mainly delamination wear.Under the higher load,the accumulation of frictional heat on the sample surface transforms the wear mechanisms of the original and the 2D-USBP treated samples into thermal wear.

Evaluation of Surface Roughness of Aluminum Alloy in Burnishing Process Based on Chaos Theory

Burnishing experiments with different burnishing parameters were performed on a computer numerical control milling machine to characterize the surface roughness of an aluminum alloy during burnishing.The chaos theory was employed to investigate the nonlinear features of the burnishing system.The experimental results show that the power spectrum is broadband and continuous,and the Lyapunov exponentλis positive,proving that burnishing has chaotic characteristics.The chaotic characteristic parameter,the correlation dimension D,is sensitive to the time behavior of the system and is used to establish the corresponding relationship with the surface roughness.The correlation dimension was the largest,when the surface roughness was the smallest.Furthermore,when the correlation dimension curve decreases,the roughness curve increases.The correlation dimension and surface roughness exhibit opposite variation trends.The higher the correlation dimension,the lower the surface roughness.The surface roughness of the aluminum alloy can be characterized online by calculating the correlation dimension during burnishing.

One-step ethylene separation from ternary C_(2) hydrocarbon mixture with a robust zirconium metal-organic framework

One-step separation of high-purity ethylene(C_(2)H_(4))from C_(2) hydrocarbon mixture is critical but challenging because of the very similar molecular sizes and physical properties of C_(2)H_(4),ethane(C_(2)H_(6)),and acetylene(C_(2)H_(2)).Herein,we report a robust zirconium metal-organic framework(MOF)Zr-TCA(H3TCA=4,4',4"-tricarboxytriphenylamine)with suitable pore size(0.6 nm×0.7 nm)and pore environment for direct C_(2)H_(4) purification from C_(2)H_(4)/C_(2)H_(2)/C_(2)H_(6) gas-mixture.Computational studies indicate that the abundant oxygen atoms and non-polar phenyl rings created favorable pore environments for the preferential binding of C_(2)H_(2) and C_(2)H_(6) over C_(2)H_(4).As a result,Zr-TCA exhibits not only high C_(2)H_(6)(2.28 mmol·g^(-1))and C_(2)H_(2)(2.78 mmol·g^(-1))adsorption capacity but also excellent C_(2)H_(6)/C_(2)H_(4)(2.72)and C_(2)H_(2)/C_(2)H_(4)(5.64)selectivity,surpassing most of one-step C_(2)H_(4) purification MOF materials.Dynamic breakthrough experiments confirm that Zr-TCA can produce high-purity C_(2)H_(4)(>99.9%)from a ternary gas mixture(1/9/90 C_(2)H_(2)/C_(2)H_(6)/C_(2)H_(4))in a single step with a high C_(2)H_(4) productivity of 5.61 L·kg^(-1).

A Special Issue:“Optimization and Key Equipments of Integrated Energy System”for Global Energy Interconnection

Energy is a critical basis for the survival and progress of humanity.Traditional energy systems,which are planned,designed,and operated in isolation,have artificially disrupted the interconnections among various energy forms.This limitation has reduced the reliability and flexibility of system operations,rendering them unsuitable for societal advancement.Integrated energy systems(IESs)dismantle the technical,market,and managerial barriers inherent in traditional systems.

Dynamical evolution of cross phase of edge fluctuations and transport bifurcation

The dynamical evolution of edge turbulence during a transport bifurcation is explored using a flux-driven nonlinear fluid model with a geometry relevant to the plasma edge region.The simulations show that the self-generated mean shear flows can dramatically modify the phase angle between turbulent fluctuations.The changes in phase differences and amplitudes of edge fluctuations give rise to the modifications of turbulent edge transport.The statistical properties of flux and fluctuations are also investigated before and after edge shear flow generation.

Recent advances in self-healing hydrogel composites for flexible wearable electronic devices

Flexible electronic devices with mechanical properties like the soft tissues of human organs have great potential for the next generation of wearable and implantable electronic devices.Self-healing hydrogel composites typically have high tensile strength,high electrical conductivity and damage repair properties and have wide applications in flexible electronics,such as human-computer interaction,health detection and soft robots.Various self-healing hydrogel composites have been developed to produce new stretchable conductive materials with satisfactory mechanical and selfhealing properties.This paper presents the fabrication of self-healing hydrogel composites and their application in flexible electronic devices.Firstly,the repair mechanism of physically cross-linked and chemically cross-linked self-healing hydrogel composites is presented.Secondly,self-healing double network hydrogels,self-healing nanocomposite hydrogels and double crosslinked self-healing hydrogel composites and their applications in flexible sensors,energy harvesting devices,energy storage devices and optical devices are presented and discussed.Finally,the challenges and prospects of self-healing hydrogel composites in flexible electronic devices in the future are presented.

公立医院成本管控的案例与启示——以国药医疗为例

伴随着我国医保支付制度改革的不断深入,药耗零加成、疾病诊断相关分组(DRG)支付方式改革等政策相继实施,公立医院承受越来越大的运营压力,如何开展成本精益化管控、实现管理转型是公立医院亟待解决的问题。本文从国药医疗所属公立医院中选取本量利模型、提质增效项目制和DRG综合分析模型三个成本管控典型案例,总结其成本管控经验,进而为公立医院成本管控提供实践参考。

New radiocarbon and archaeobotanical evidence reveal the timing and route of southward dispersal of rice farming in south China

The origins and spreads of rice agriculture have been enduring topics, yet the timing and southward dispersal from the Yangtze River Basin have been difficult to trace, due to the scarcity of archaeobotanical data, especially systematic macro-plant remains examination, combined with the poor preservation in the humid climate and acidic soils of China's southern provinces.Here, we report new radiocarbon dating and preserved rice phytolith evidence, derived from three Late Neolithic archaeological sites in south China, dated about 5,000–4,100 cal a BP.Our results demonstrate that rice farming had spread southward through the mountainous regions of Wuyi and Nanling, then entered the areas of Western Fujian and North Guangdong by 5,000 cal a BP, followed by continued expansion into coastal areas of East China Sea and South China Sea, also crossing the Taiwan Strait, around 4,500–4,000 cal a BP.The North River,East River, Min River, and possibly other river systems likely were influential as pathways or conduits.

Hf_(0.5)Zr_(0.5)O_(2)-based ferroelectric memristor with multilevel storage potential and artificial synaptic plasticity

Memristors are designed to mimic the brain’s integrated functions of storage and computing,thus breaking through the von Neumann framework.However,the formation and breaking of the conductive filament inside a conventional memristor is unstable,which makes it difficult to realistically mimic the function of a biological synapse.This problem has become a main factor that hinders memristor applications.The ferroelectric memristor overcomes the shortcomings of the traditional memristor because its resistance variation depends on the polarization direction of the ferroelectric thin film.In this work,an Au/Hf0.5Zr0.5O2/p+-Si ferroelectric memristor is proposed,which is capable of achieving resistive switching characteristics.In particular,the proposed device realizes the stable characteristics of multilevel storage,which possesses the potential to be applied to multi-level storage.Through polarization,the resistance of the proposed memristor can be gradually modulated by flipping the ferroelectric domains.Additionally,a plurality of resistance states can be obtained in bidirectional continuous reversibility,which is similar to the changes in synaptic weights.Furthermore,the proposed memristor is able to successfully mimic biological synaptic functions such as long-term depression,long-term potentiation,paired-pulse facilitation,and spike-timing-dependent plasticity.Consequently,it constitutes a promising candidate for a breakthrough in the von Neumann framework.

Flexible memristors as electronic synapses for neuro- inspired computation based on scotch tape-exfoliated mica substrates

Flexible memristor devices based on plastic substrates have attracted considerable attention due to their applications in wearable computers and integrated circuits. However, most plastic-substrate memristors cannot function or be grown in high-temperature environments. In this study, scotch-tape-exfoliated mica was used as the flexible memristor substrate in order to resolve these high-temperature issues. Our TiN/ZHO/IGZO memristor, which was constructed using a thin （10 μm） mica substrate, has superior flexibility and thermostability. After bending it 103 times, the device continues to exhibit exceptional electrical characteristics. It can also be implemented for transitions between high and low resistance states, even in temperatures of up to 300 ℃. More importantly, the biological synaptic characteristics of paired-pulse facilitation/depression （PPF/PPD） and spike- timing-dependent plasticity （STDP） were observed through applying different pulse measurement modes. This work demonstrates that flexible memristor devices on mica substrates may potentially allow for the realization of high-temperature memristor applications for biologically-inspired computing systems.

Memristor based onα-In_(2)Se_(3)for emulating biological synaptic plasticity and learning behavior

Nowadays,memristors are extremely similar to biological synapses and can achieve many basic functions of biological synapses,making them become a new generation of research hotspots for brain-like neurocomputing.In this work,we prepare a memristor based on two-dimensionalα-In_(2)Se_(3)nanosheets,which exhibits excellent electrical properties,faster switching speeds,and continuous tunability of device conduction.Meanwhile,most basic bio-synapse functions can be implemented faithfully,such as short-term memory(STM),long-term memory(LTM),four different types of spike-timing-dependent plasticity(STDP),and paired-pulse facilitation(PPF).More importantly,we systematically study three effective methods to achieve LTM,in which the reinforcement learning can be faithfully simulated according to the Ebbinghaus forgetting curve.Therefore,we believe this work will promote the development of learning functions for brain-like computing and artificial intelligence.

Superstructured α-Fe2O3 nanorods as novel binder-free anodes for high-performing fiber-shaped Ni/Fe battery

Fiber-shaped energy storage devices are indispensable parts of wearable and portable electronics.Aqueous rechargeable Ni/Fe battery is a very appropriate energy storage device due to their good safety without organic electrolytes, high ionic conductivity, and low cost. Unfortunately, the low energy density,poor power density and cycling performance hinder its further practical applications. In this study, in order to obtain high performance negative iron-based material, we first synthesized a-iron oxide(α-Fe2O3) nanorods(NRs) with superstructures on the surface of highly conductive carbon nanotube fibers(CNTFs), then electrically conductive polypyrrole(PPy) was coated to enhance the electron, ion diffusion and cycle stability. The as-prepared α-Fe2O3@PPy NRs/CNTF electrode shows a high specific capacity of 0.62 Ah cm-3 at the current density of 1 A cm-3. Furthermore, the Ni/Fe battery that was assembled by the above negative electrode shows a maximum volumetric energy density of 15.47 mWh cm-3 with228.2 mW cm-3 at a current density of 1 A cm-3. The cycling durability and mechanical flexibility of the Ni/Fe battery were tested, which show good prospect for practical application. In summary, these merits make it possible for our Ni/Fe battery to have practical applications in next generation flexible energy storage devices.

A review of Mott insulator in memristors:The materials,characteristics,applications for future computing systems and neuromorphic computing

Mott insulator material,as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity,shows excellent application prospects in neuromorphological calculations and has attracted significant attention in the scientific community.Especially,computing systems based on Mott insulators can overcome the bottleneck of separated data storage and calculation in traditional artificial intelligence systems based on the von Neumann architecture,with the potential to save energy,increase operation speed,improve integration,scalability,and three-dimensionally stacked,and more suitable to neuromorphic computing than a complementary metal-oxide-semiconductor.In this review,we have reviewed Mott insulator materials,methods for driving Mott insulator transformation(pressure-,voltage-,and temperature-driven approaches),and recent relevant applications in neuromorphic calculations.The results in this review provide a path for further study of the applications in neuromorphic calculations based on Mott insulator materials and the related devices.