A high Li-ion diffusion kinetics in multidimensional and compact-structured electrodes via vacuum filtration casting

Manufacturing process,diffusion co-efficient and areal capacity are the three main criteria for regulating thick electrodes for lithium-ion batteries(LIBs).However,simultaneously regulating these criteria for LIBs is desirable but remains a significant challenge.In this work,niobium pentoxide(Nb_(2)O_(5))anode and lithium iron phosphate(LiFePO_(4))cathode materials were chosen as the model materials and demonstrate that these three parameters can be simultaneously modulated by incorporation of micro-carbon fibers(MCF)and carbon nanotubes(CNT)with both Nb_(2)O_(5) and LFP via vacuum filtration approach.Both as-prepared MNC-20 anode and MLC-20 cathode achieves high reversible areal capacity of≈5.4 m A h cm^(-2)@0.1 C and outstanding Li-ion diffusion coefficients of≈10~(-8)cm~2 s~(-1)in the half-cell configuration.The assembled MNC-20‖MLC-20 full cell LIB delivers maximum energy and power densities of244.04 W h kg^(-1)and 108.86 W kg^(-1),respectively.The excellent electrochemical properties of the asprepared thick electrodes can be attributed to the highly conductive,mechanical compactness and multidimensional mutual effects of the MCF,CNT and active materials that facilitates rapid Li-ion diffusion kinetics.Furthermore,electrochemical impedance spectroscopy(EIS),symmetric cells analysis,and insitu Raman techniques clearly validates the enhanced Li-ion diffusion kinetics in the present architecture.

Special Section on High-Dimensional Signal Processing

Massive amounts of data are acquired in modern and future information technology industries such as communication,radar,and remote sensing.The presence of large dimensionality and size in these data offers new opportunities to enhance the performance of signal processing in such applications and even motivate new ones.However,the curse of dimensionality is always a challenge when processing such high-dimensional signals.In practical tasks,high-dimensional signals need to be acquired,processed,and analyzed with high accuracy,robustness,and computational efficiency.This special section aims to address these challenges,where articles attempt to develop new theories and methods that are best suited to the high dimensional nature of the signals involved,and explore modern and emerging applications in this area.

Higher-dimensional Chen-Lee-Liu equation and asymmetric peakon soliton

Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integrable systems in higher dimensions.Recent studies have shown that abundant higher-dimensional integrable systems can be constructed from(1+1)-dimensional integrable systems by using a deformation algorithm.Here we establish a new(2+1)-dimensional Chen-Lee-Liu(C-L-L)equation using the deformation algorithm from the(1+1)-dimensional C-L-L equation.The new system is integrable with its Lax pair obtained by applying the deformation algorithm to that of the(1+1)-dimension.It is challenging to obtain the exact solutions for the new integrable system because the new system combines both the original C-L-L equation and its reciprocal transformation.The traveling wave solutions are derived in implicit function expression,and some asymmetry peakon solutions are found.

Three‐dimensional(3D)‐printed MXene high‐voltage aqueous micro‐supercapacitors with ultrahigh areal energy density and low‐temperature tolerance

The rapid advancement in the miniaturization,integration,and intelligence of electronic devices has escalated the demand for customizable microsupercapacitors(MSCs)with high energy density.However,efficient microfabrication of safe and high‐energy MXene MSCs for integrating microelectronics remains a significant challenge due to the low voltage window in aqueous electrolytes(typically≤0.6 V)and limited areal mass loading of MXene microelectrodes.Here,we tackle these challenges by developing a highconcentration(18mol kg^(−1))“water‐in‐LiBr”(WiB)gel electrolyte for MXene symmetric MSCs(M‐SMSCs),demonstrating a record high voltage window of 1.8 V.Subsequently,additive‐free aqueous MXene ink with excellent rheological behavior is developed for three‐dimensional(3D)printing customizable all‐MXene microelectrodes on various substrates.Leveraging the synergy of a highvoltage WiB gel electrolyte and 3D‐printed microelectrodes,quasi‐solid‐state MSMSCs operating stably at 1.8 V are constructed,and achieve an ultrahigh areal energy density of 1772μWhcm^(−2) and excellent low‐temperature tolerance,with a long‐term operation at−40℃.Finally,by extending the 3D printing protocol,M‐SMSCs are integrated with humidity sensors on a single planar substrate,demonstrating their reliability in miniaturized integrated microsystems.

DOA estimation of high-dimensional signals based on Krylov subspace and weighted l_(1)-norm

With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.

Lax-Oleinik-Type Formulas and Efficient Algorithms for Certain High-Dimensional Optimal Control Problems

Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimensions.In this paper,we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control.We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians.Additionally,we present an efficient,grid-free numerical solver based on our representation formulas,which is shown to scale linearly with the state dimension,and thus,to overcome the curse of dimensionality.Using existing optimization methods and the min-plus technique,we extend our numerical solvers to address more general classes of convex and nonconvex initial costs.We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit(CPU)and a field-programmable gate array(FPGA).In several cases,our FPGA implementation obtains over a 10 times speedup compared to the CPU,which demonstrates the promising performance boosts FPGAs can achieve.Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.

Optimal Estimation of High-Dimensional Covariance Matrices with Missing and Noisy Data

The estimation of covariance matrices is very important in many fields, such as statistics. In real applications, data are frequently influenced by high dimensions and noise. However, most relevant studies are based on complete data. This paper studies the optimal estimation of high-dimensional covariance matrices based on missing and noisy sample under the norm. First, the model with sub-Gaussian additive noise is presented. The generalized sample covariance is then modified to define a hard thresholding estimator , and the minimax upper bound is derived. After that, the minimax lower bound is derived, and it is concluded that the estimator presented in this article is rate-optimal. Finally, numerical simulation analysis is performed. The result shows that for missing samples with sub-Gaussian noise, if the true covariance matrix is sparse, the hard thresholding estimator outperforms the traditional estimate method.

Six-Dimensional Guidance: The Strategies of Thinking Quality Cultivation in Senior High School English Discourse Learning

Taking the discourse learning of the new senior high school English textbook published by the People’s Education Press as an example,combined with the“six-dimensional guidance”deep reading strategy,and through the six-skill training strategies of“memory skill training,understanding skill training,application skill training,analytical skill training,evaluation skill training,creative skill training,”this paper aims to cultivate students’thinking profundity,logic,flexibility,sensitivity,criticality,and originality.It also promotes the real implementation of senior high school English deep reading that points to the cultivation of thinking quality in classroom teaching,and realizes the transformation from“conventional reading”to“deep reading”that reflects the core literacy of the discipline.

Preparation of three-dimensional interconnected mesoporous anatase TiO_2-SiO_2 nanocomposites with high photocatalytic activities

In this article, we report the preparation of a three-dimensional（3D） interconnected mesoporous anatase TiO2-SiO2 nanocomposite. The nanocomposite was obtained by using an ordered two-dimensional（2D） hexagonal mesoporous anatase 70 TiO2-30 SiO2-950 nanocomposite（crystallized at 950 °C for 2 h） as a precursor, NaO H as an etchant of SiO2 via a ＂creating mesopores in the pore walls＂ approach. Our strategy adopts mild conditions of creating pores such as diluted NaO H solution, appropriate temperature and solid/liquid ratio, etc. aiming at ensuring the integrities of mesopores architecture and anatase nanocrystals. XRD, TEM and N2 sorption techniques have been used to systematically investigate the physico-chemical properties of the nanocomposites. The results show that the intrawall mesopores are highly dense and uniform（average pore size 3.6 nm）, and highly link the initial mesochannels in a 3D manner while retaining mesostructural integrity. There is no significant change to either crystallinity or size of the anatase nanocrystals before and after creating the intrawall mesopores. The photocatalytic degradation rates of rhodamine B（RhB, 0.303 min^–1） and methylene blue（MB, 0.757 min^–1） dyes on the resultant nanocomposite are very high, which are 5.1 and 5.3 times that of the precursor; even up to 16.5 and 24.1 times that of Degussa P25 photocatalyst, respectively. These results clearly demonstrate that the 3D interconnected mesopores structure plays an overwhelming role to the increments of activities. The 3D mesoporous anatase TiO2-SiO2 nanocomposite exhibits unexpected-high degradation activities to RhB and MB in the mesoporous metal oxide-based materials reported so far. Additionally, the nanocomposite is considerably stable and reusable. We believe that this method would pave the way for the preparation of other 3D highly interconnected mesoporous metal oxide-based materials with ultra-high performance.

High-Order Soliton Solutions and Hybrid Behavior for the (2 + 1)-Dimensional Konopelchenko-Dubrovsky Equations

In this paper, the evolutionary behavior of N-solitons for a (2 + 1)-dimensional Konopelchenko-Dubrovsky equations is studied by using the Hirota bilinear method and the long wave limit method. Based on the N-soliton solution, we first study the evolution from N-soliton to T-order (T=1,2) breather wave solutions via the paired-complexification of parameters, and then we get the N-order rational solutions, M-order (M=1,2) lump solutions, and the hybrid behavior between a variety of different types of solitons combined with the parameter limit technique and the paired-complexification of parameters. Meanwhile, we also provide a large number of three-dimensional figures in order to better show the degeneration of the N-soliton and the interaction behavior between different N-solitons.

CABOSFV algorithm for high dimensional sparse data clustering

An algorithm, Clustering Algorithm Based On Sparse Feature Vector (CABOSFV),was proposed for the high dimensional clustering of binary sparse data. This algorithm compressesthe data effectively by using a tool 'Sparse Feature Vector', thus reduces the data scaleenormously, and can get the clustering result with only one data scan. Both theoretical analysis andempirical tests showed that CABOSFV is of low computational complexity. The algorithm findsclusters in high dimensional large datasets efficiently and handles noise effectively.

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity,leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals,and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this method,three data types are used,and seven common similarity measurement methods are compared.The experimental result indicates that the relative difference of the method is increasing with the dimensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition,the similarity range of this method in different dimensions is [0,1],which is fit for similarity analysis after dimensionality reduction.

Similarity measure design for high dimensional data

Information analysis of high dimensional data was carried out through similarity measure application. High dimensional data were considered as the a typical structure. Additionally, overlapped and non-overlapped data were introduced, and similarity measure analysis was also illustrated and compared with conventional similarity measure. As a result, overlapped data comparison was possible to present similarity with conventional similarity measure. Non-overlapped data similarity analysis provided the clue to solve the similarity of high dimensional data. Considering high dimensional data analysis was designed with consideration of neighborhoods information. Conservative and strict solutions were proposed. Proposed similarity measure was applied to express financial fraud among multi dimensional datasets. In illustrative example, financial fraud similarity with respect to age, gender, qualification and job was presented. And with the proposed similarity measure, high dimensional personal data were calculated to evaluate how similar to the financial fraud. Calculation results show that the actual fraud has rather high similarity measure compared to the average, from minimal 0.0609 to maximal 0.1667.

High-Dimensional Spatial Standardization Algorithm for Diffusion Tensor Image Registration

Three high dimensional spatial standardization algorithms are used for diffusion tensor image(DTI)registration,and seven kinds of methods are used to evaluate their performances.Firstly,the template used in this paper was obtained by spatial transformation of 16 subjects by means of tensor-based standardization.Then,high dimensional standardization algorithms for diffusion tensor images,including fractional anisotropy(FA)based diffeomorphic registration algorithm,FA based elastic registration algorithm and tensor-based registration algorithm,were performed.Finally,7 kinds of evaluation methods,including normalized standard deviation,dyadic coherence,diffusion cross-correlation,overlap of eigenvalue-eigenvector pairs,Euclidean distance of diffusion tensor,and Euclidean distance of the deviatoric tensor and deviatoric of tensors,were used to qualitatively compare and summarize the above standardization algorithms.Experimental results revealed that the high-dimensional tensor-based standardization algorithms perform well and can maintain the consistency of anatomical structures.

High temperature magnetic semiconductors: narrow band gaps and two-dimensional systems

Magnetic semiconductors have been demonstrated to work at low temperatures, but not yet at room temperature for spin electronic applications. In contrast to the p-type diluted magnetic semiconductors, n-type diluted magnetic semiconductors are few. Using a combined method of the density function theory and quantum Monte Carlo simulation, we briefly discuss the recent progress to obtain diluted magnetic semiconductors with both p- and n-type carriers by choosing host semiconductors with a narrow band gap. In addition, the recent progress on two-dimensional intrinsic magnetic semiconductors with possible room temperature ferromangetism and quantum anomalous Hall effect are also discussed.

Application of Three-Dimensional Laser Scanning and Surveying in Geological Investigation of High Rock Slope

The appearance of 3D laser scanning technology is one of the most important technology revolutions in surveying and mapping field. It can be widely used in many interrelated fields, such as engineering constructions and 3D measurements, owing to its prominent characteristics of the high efficiency and high precision. At present its application is still in the initial state, and it is quite rarely used in China, especially in geotechnical engineering and geological engineering fields. Starting with a general introduction of 3D laser scanning technology, this article studies how to apply the technology to high rock slope investigations. By way of a case study, principles and methods of quick slope documentation and occurrence measurement of discontinuities are discussed and analyzed. Analysis results show that the application of 3D laser scanning technology to geotechnical and geological engineering has a great prospect and value.

Two-dimensional electron gas characteristics of InP-based high electron mobility transistor terahertz detector

The samples of InxGa（1-x）As/In（0.52）Al（0.48）As two-dimensional electron gas（2DEG）are grown by molecular beam epitaxy（MBE）.In the sample preparation process,the In content and spacer layer thickness are changed and two kinds of methods,i.e.,contrast body doping andδ-doping are used.The samples are analyzed by the Hall measurements at 300 Kand 77 K.The InxGa1-xAs/In0.52Al0.48As 2DEG channel structures with mobilities as high as 10289 cm^2/V·s（300 K）and42040 cm^2/V·s（77 K）are obtained,and the values of carrier concentration（Nc）are 3.465×10^12/cm^2 and 2.502×10^12/cm^2,respectively.The THz response rates of In P-based high electron mobility transistor（HEMT）structures with different gate lengths at 300 K and 77 K temperatures are calculated based on the shallow water wave instability theory.The results provide a reference for the research and preparation of In P-based HEMT THz detectors.

A TWO-DIMENSIONAL LAGRANGIAN TECHNIQUE FOR FLOW FIELD MEASUREMENT UNDER HIGH DYNAMIC PRESSURE

In this paper,a two-dimensional(2-D)Lagrangian technique for flow field measurement under high dynamic pressure is presented,which includes a set of experimental device and 2-D Lagrange composite manganin-constantan ring gages.With this kind of gage,the histories of pressure and radial displacement can be measured simultaneously at different Lagrange positions in an axisymmetric shock loading flow field. The technique has some advantages over the 1-D one,such as,simplified loading device,continuously adjust- able output pressure,no restriction on sample length and the availability for the study of lateral rarefaction in shock propogation.As a preliminary application,the processes of 2-D shock initiation and attenuation in compacted TNT are measured.

The Structure of Reflective Function of Higher Dimensional Differential System

In this article, we discuss the structure of reflective function of the higher dimensional differential systems and apply the results to study the existence of periodic solutions of these systems.

Feature selection of ultrahigh-dimensional covariates with survival outcomes:a selective review

Many modern biomedical studies have yielded survival data with high-throughput predictors.The goals of scientific research often lie in identifying predictive biomarkers,understanding biological mechanisms and making accurate and precise predictions.Variable screening is a crucial first step in achieving these goals.This work conducts a selective review of feature screening procedures for survival data with ultrahigh dimensional covariates.We present the main methodologies,along with the key conditions that ensure sure screening properties.The practical utility of these methods is examined via extensive simulations.We conclude the review with some future opportunities in this field.