Biomass-derived porous carbon with single-atomic cobalt toward high-performance aqueous zinc-sulfur batteries at room temperature

Aqueous zinc-sulfur batteries at room temperature hold great potential for next-generation energy storage technology due to their low cost,safety and high energy density.However,slow reaction kinetics and high activation energy at the sulfur cathode pose great challenges for the practical applications.Herein,biomass-derived carbon with single-atomic cobalt sites(MMPC-Co)is synthesized as the cathode in Zn-S batteries.The catalysis of single-atom Co sites greatly promotes the transform of cathode electrolyte interface(CEI)on the cathode surface,while offering accelerated charge transfer rate for high conversion reversibility and large electrochemical surface area(ECSA)for high electrocatalytic current.Furthermore,the rich pore structure not only physically limits sulfur loss,but also accelerates the transport of zinc ions.In addition,the large pore volume of MMPC-Co is able to relieve the stress effect caused by the volume expansion of Zn S during charge/discharge cycles,thereby maintaining the stability of electrode structure.Consequently,the sulfur cathode maintains a high specific capacity of 729.96 m A h g^(-1)after 500 cycles at4 A g^(-1),which is much better than most cathode materials reported in the literature.This work provides new insights into the design and development of room-temperature aqueous Zn-S batteries.

Neural Dynamics for Cooperative Motion Control of Omnidirectional Mobile Manipulators in the Presence of Noises: A Distributed Approach

This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.

An artificial systems,computational experiments and parallel execution-based surface electromyogram-driven anti-disturbance zeroing neurodynamic strategy for upper limb human-robot interaction control

In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.

Design and analysis of recurrent neural network models with non-linear activation functions for solving time-varying quadratic programming problems

A special recurrent neural network(RNN),that is the zeroing neural network(ZNN),is adopted to find solutions to time-varying quadratic programming(TVQP)problems with equality and inequality constraints.Howevet,there are some weaknesses in activation functions of traditional ZNN models,including convex restriction and redundant formulation.With the aid of different activation functions,modified ZNN models are obtained to overcome the drawbacks for solving TVQP problems.Theoretical and experimental research indicate that the proposed models are better and more effective at solving such TVQP problems.

The dynamic relaxation form finding method aided with advanced recurrent neural network

How to establish a self‐equilibrium configuration is vital for further kinematics and dynamics analyses of tensegrity mechanism.In this study,for investigating tensegrity form‐finding problems,a concise and efficient dynamic relaxation‐noise tolerant zeroing neural network(DR‐NTZNN)form‐finding algorithm is established through analysing the physical properties of tensegrity structures.In addition,the non‐linear constrained opti-misation problem which transformed from the form‐finding problem is solved by a sequential quadratic programming algorithm.Moreover,the noise may produce in the form‐finding process that includes the round‐off errors which are brought by the approximate matrix and restart point calculating course,disturbance caused by external force and manufacturing error when constructing a tensegrity structure.Hence,for the purpose of suppressing the noise,a noise tolerant zeroing neural network is presented to solve the search direction,which can endow the anti‐noise capability to the form‐finding model and enhance the calculation capability.Besides,the dynamic relaxation method is contributed to seek the nodal coordinates rapidly when the search direction is acquired.The numerical results show the form‐finding model has a huge capability for high‐dimensional free form cable‐strut mechanisms with complicated topology.Eventually,comparing with other existing form‐finding methods,the contrast simulations reveal the excellent anti‐noise performance and calculation capacity of DR‐NTZNN form‐finding algorithm.

Numerical‐discrete‐scheme‐incorporated recurrent neural network for tasks in natural language processing

A variety of neural networks have been presented to deal with issues in deep learning in the last decades.Despite the prominent success achieved by the neural network,it still lacks theoretical guidance to design an efficient neural network model,and verifying the performance of a model needs excessive resources.Previous research studies have demonstrated that many existing models can be regarded as different numerical discretizations of differential equations.This connection sheds light on designing an effective recurrent neural network(RNN)by resorting to numerical analysis.Simple RNN is regarded as a discretisation of the forward Euler scheme.Considering the limited solution accuracy of the forward Euler methods,a Taylor‐type discrete scheme is presented with lower truncation error and a Taylor‐type RNN(T‐RNN)is designed with its guidance.Extensive experiments are conducted to evaluate its performance on statistical language models and emotion analysis tasks.The noticeable gains obtained by T‐RNN present its superiority and the feasibility of designing the neural network model using numerical methods.

Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered to be a powerful QPs solver due to its parallel processing capability and feasibility of hardware implementation[2].

Non-electrocardiography-gated dual-energy cardiac CT angiography for assessment of left atrial appendage thrombus

Objective:To explore the diagnosis value of a low dose,dual-energy cardiac computed tomography angiography(CTA)with non-electrocardiography-gated(non-ECG-gated)in detecting left atrial appendage(IAA)thrombus.Methods:Consecutive patients with atrial fibrillation who underwent cardiac CTA protocol(dual-energy scan for arterial phase and conventional scan for delayed phase)were prospectively enrolled.LAA lesions were proved by clinical comprehensive diagnosis,the final study included 18 cases with LAA thrombus and 48 cases with circulatory stasis.Quantitative parameters derived from dual-energy images were measured for the LAA lesions,including the conventional CT attenuation value(CT value),iodine concentration(IC),normalized iodine concentration(NIC),effective atomic number values(Zeff)and energy spectrum curve slope(Slope).The differences between LAA thrombus group and circulatory stasis group were compared by independent sample t-test or Wilcoxon rank sum test regarding to the normality test.The diagnosis performance of the dual-energy parameters was assessed using receiver operating characteristic(ROC)curve analysis and area under curve(AUC).Results:All the dual-energy parameters were demonstrated significantly difference between LAA thrombus and circulatory stasis group(P<0.05),and showed better diagnostic performance than the conventional CT value.ROC analysis revealed IC was the most predictive parameter with AUC equal to 0.836.The radiation dose in the arterial phase was(2.640.66)mSv.Conclusion:Dual-energy CTA scanning shows convincing diagnostic performance in detecting left atrial appendage thrombus with lower radiation dose,and may help reduce the need for delayed phase scan.

A PUF-Based and Cloud-Assisted Lightweight Authentication for Multi-Hop Body Area Network

Wireless sensor technology plays an important role in the military,medical,and commercial fields nowadays.Wireless Body Area Network(WBAN)is a special application of the wireless sensor network in human health monitoring,through which patients can know their physical condition in real time and respond to emergencies on time.Data reliability,guaranteed by the trust of nodes in WBAN,is a prerequisite for the effective treatment of patients.Therefore,authenticating the sensor nodes and the sink nodes in WBAN is necessary.This paper proposes a lightweight Physical Unclonable Function(PUF)-based and cloud-assisted authentication mechanism for multi-hop body area networks,which compared with the star single-hop network,can enhance the adaptability to human motion and the integrity of data transmission.Such authentication mechanism can significantly reduce the storage overhead and resource loss in the data transmission process.

Tuning structure and magnetic properties of table-like magnetocaloric effect in Er_(6)MnSb_(2) by zirconium substitution

In this study,zirconium(Zr) successfully substituted for erbium(Er) in Er_(6-x)Zr_(x)MnSb_(2)(x=0,0.5,1,1.5) of the Fe_(2)P type,with comprehensive characterizations on crystal structure,electronic structure and magnetic properties.According to synchrotron powder X-ray diffraction data analysis and density functional theory calculation,Zr does not randomly but preferentially occupy during the doping process and results in weaker magnetic exchange interactions and depressed ordering temperatures.The electronic structure data show that the doping of Zr can weaken interaction between Er and Mn atoms.Owing to multiple transitions,the Er_(6-x)Zr_(x)MnSb_(2)(x=0,0.5,1,1.5) exhibit table-like magnetocaloric effect.Er_(6)MnSb_(2) displays wide δT_(FWHM)(full width at half maximum of the magnetic entropy change curve) of 116 K and high relative cooling power of 388.62 J/kg for 3 T.The maximum magnetic entropy change of Er_(6-x)Zr_(x)MnSb_(2) is increased from 3.81 to 7.69 J/(kg·K) with the Zr content up from x=0 to x=1.5.

Guiding topological semimetals towards water oxidation in a Kagomé crystal lattice

Photocatalytic splitting of relatively plentiful water into O2 and H2 supplies a possible solution for storing solar energy to meet energy demands and environmental requirements[1].The water oxidation half reaction to form dioxygen known as the oxygen evolution reaction(OER,2H2O→O2+4H++4e-)is attracting more attention because there are already known materials for efficient mediation of the reduction step(4H++4e-→2H2)[2].Current research focuses on understanding the mechanisms of OER and development of new OER catalysts.The widely studied OER systems include platinum surface[1],transition metal oxides[2],transition metal complexes[3],3d transition metal spinels and perovskites[4],and metal-organic framework(MOF)materials based on3d transition metals[5].In these materials,transition metals in the surface generally serve as active centers for the OER,while the surrounding atomic environments determine their performance and stability[6].However,preparation of the surface has a large effect on reactivity(defects,kinks,low coordinate sites)therefore it is difficult to predict an OER material’s properties by its bulk structure.