(T_2,T_1/T_2) Two-Dimensional NMR Method for Gas Layers Typing

The gas saturation in flushed zone of gas layers is low and the observed gas signal is weak because the mud filtrate invasion reduces the native gas saturation.A(T2,T1/T2) two-dimensional nuclear magnetic resonance(NMR) method of typing gas layers was developed.The performance of(T2,T1/T2) method for typing gas at different kinds of reservoirs,signal-to-noise ratios and gas saturations was studied in details through numerical simulation.The results show that(T2,T1/T2) method is especially useful for identifying gas formations.It is suitable for typing lower gas saturation formation where drilling mud filtrate flushes strongly.

A Method of Choosing the Optimal Number of Singular Values in the Inverse Laplace Transform for the Two-Dimensional NMR Distribution Function

Two-dimensional(2D)nuclear magnetic resonance(NMR)distributions as functions of diffusion coefficient and relaxation time are powerful tools in the study of porous media.We propose a practical method to perform proper truncation of singular value decomposition(TSVD)in Laplace inversion for obtaining 2D-NMR distributions from measured NMR data.By analyzing basic algorithms for Laplace inversion,it is well known that proper TSVD does not affect the inversion result for an ill-posed problem with zero-order Tikhonov regularization,but can greatly increase the inversion speed.In this new method,the optimal number of singular values for data compression is applied to each dimension separately.The method also makes full use of the redundancy nature of the data with a finite signal-to-noise ratio and well balances the tradeoff between the speed and the bias.The method does not require the stochastic information of the estimated parameters when obtaining the optimal number of singular values.

Two-dimensional NMR inversion based on fast norm smoothing method

Two-dimensional(2D)nuclear magnetic resonance(NMR)inversion operates with massive echo train data and is an ill-posed problem.It is very important to select a suitable inversion method for the 2D NMR data processing.In this study,we propose a fast,robust,and effective method for 2D NMR inversion that improves the computational efficiency of the inversion process by avoiding estimation of some unneeded regularization parameters.Firstly,a method that combines window averaging(WA)and singular value decomposition(SVD)is used to compress the echo train data and obtain the singular values of the kernel matrix.Subsequently,an optimum regularization parameter in a fast manner using the signal-to-noise ratio(SNR)of the echo train data and the maximum singular value of the kernel matrix are determined.Finally,we use the Butler-Reeds-Dawson(BRD)method and the selected optimum regularization parameter to invert the compressed data to achieve a fast 2D NMR inversion.The numerical simulation results indicate that the proposed method not only achieves satisfactory 2D NMR spectra rapidly from the echo train data of different SNRs but also is insensitive to the number of the final compressed data points.

Progress on two-dimensional ferrovalley materials

The electron's charge and spin degrees of freedom are at the core of modern electronic devices. With the in-depth investigation of two-dimensional materials, another degree of freedom, valley, has also attracted tremendous research interest. The intrinsic spontaneous valley polarization in two-dimensional magnetic systems, ferrovalley material, provides convenience for detecting and modulating the valley. In this review, we first introduce the development of valleytronics.Then, the valley polarization forms by the p-, d-, and f-orbit that are discussed. Following, we discuss the investigation progress of modulating the valley polarization of two-dimensional ferrovalley materials by multiple physical fields, such as electric, stacking mode, strain, and interface. Finally, we look forward to the future developments of valleytronics.

Recent advances in two-dimensional photovoltaic devices

Two-dimensional(2D)materials have attracted tremendous interest in view of the outstanding optoelectronic properties,showing new possibilities for future photovoltaic devices toward high performance,high specific power and flexibility.In recent years,substantial works have focused on 2D photovoltaic devices,and great progress has been achieved.Here,we present the review of recent advances in 2D photovoltaic devices,focusing on 2D-material-based Schottky junctions,homojunctions,2D−2D heterojunctions,2D−3D heterojunctions,and bulk photovoltaic effect devices.Furthermore,advanced strategies for improving the photovoltaic performances are demonstrated in detail.Finally,conclusions and outlooks are delivered,providing a guideline for the further development of 2D photovoltaic devices.

Recent progress on valley polarization and valley-polarized topological states in two-dimensional materials

Valleytronics, using valley degree of freedom to encode, process, and store information, may find practical applications in low-power-consumption devices. Recent theoretical and experimental studies have demonstrated that twodimensional(2D) honeycomb lattice systems with inversion symmetry breaking, such as transition-metal dichalcogenides(TMDs), are ideal candidates for realizing valley polarization. In addition to the optical field, lifting the valley degeneracy of TMDs by introducing magnetism is an efficient way to manipulate the valley degree of freedom. In this paper, we first review the recent progress on valley polarization in various TMD-based systems, including magnetically doped TMDs,intrinsic TMDs with both inversion and time-reversal symmetry broken, and magnetic TMD heterostructures. When topologically nontrivial bands are empowered into valley-polarized systems, valley-polarized topological states, namely valleypolarized quantum anomalous Hall effect can be realized. Therefore, we have also reviewed the theoretical proposals for realizing valley-polarized topological states in 2D honeycomb lattices. Our paper can help readers quickly grasp the latest research developments in this field.

Anomalous valley Hall effect in two-dimensional valleytronic materials

The anomalous valley Hall effect(AVHE)can be used to explore and utilize valley degrees of freedom in materials,which has potential applications in fields such as information storage,quantum computing and optoelectronics.AVHE exists in two-dimensional(2D)materials possessing valley polarization(VP),and such 2D materials usually belong to the hexagonal honeycomb lattice.Therefore,it is necessary to achieve valleytronic materials with VP that are more readily to be synthesized and applicated experimentally.In this topical review,we introduce recent developments on realizing VP as well as AVHE through different methods,i.e.,doping transition metal atoms,building ferrovalley heterostructures and searching for ferrovalley materials.Moreover,2D ferrovalley systems under external modulation are also discussed.2D valleytronic materials with AVHE demonstrate excellent performance and potential applications,which offer the possibility of realizing novel low-energy-consuming devices,facilitating further development of device technology,realizing miniaturization and enhancing functionality of them.

Emerging two-dimensional Mo-based materials for rechargeable metal-ion batteries:Advances and perspectives

With the rapid development of rechargeable metal-ion batteries(MIBs)with safety,stability and high energy density,significant efforts have been devoted to exploring high-performance electrode materials.In recent years,two-dimensional(2D)molybdenum-based(Mo-based)materials have drawn considerable attention due to their exceptional characteristics,including low cost,unique crystal structure,high theoretical capacity and controllable chemical compositions.However,like other transition metal compounds,Mo-based materials are facing thorny challenges to overcome,such as slow electron/ion transfer kinetics and substantial volume changes during the charge and discharge processes.In this review,we summarize the recent progress in developing emerging 2D Mo-based electrode materials for MIBs,encompassing oxides,sulfides,selenides,carbides.After introducing the crystal structure and common synthesis methods,this review sheds light on the charge storage mechanism of several 2D Mo-based materials by various advanced characterization techniques.The latest achievements in utilizing 2D Mo-based materials as electrode materials for various MIBs(including lithium-ion batteries(LIBs),sodium-ion batteries(SIBs)and zinc-ion batteries(ZIBs))are discussed in detail.Afterwards,the modulation strategies for enhancing the electrochemical performance of 2D Mo-based materials are highlighted,focusing on heteroatom doping,vacancies creation,composite coupling engineering and nanostructure design.Finally,we present the existing challenges and future research directions for 2D Mo-based materials to realize high-performance energy storage systems.

Image segmentation of exfoliated two-dimensional materials by generative adversarial network-based data augmentation

Mechanically cleaved two-dimensional materials are random in size and thickness.Recognizing atomically thin flakes by human experts is inefficient and unsuitable for scalable production.Deep learning algorithms have been adopted as an alternative,nevertheless a major challenge is a lack of sufficient actual training images.Here we report the generation of synthetic two-dimensional materials images using StyleGAN3 to complement the dataset.DeepLabv3Plus network is trained with the synthetic images which reduces overfitting and improves recognition accuracy to over 90%.A semi-supervisory technique for labeling images is introduced to reduce manual efforts.The sharper edges recognized by this method facilitate material stacking with precise edge alignment,which benefits exploring novel properties of layered-material devices that crucially depend on the interlayer twist-angle.This feasible and efficient method allows for the rapid and high-quality manufacturing of atomically thin materials and devices.

Single-cell manipulation by two-dimensional micropatterning

Cells are highly sensitive to their geometrical and mechanical microenvironment that directly regulate cell shape,cytoskeleton and organelle,as well as the nucleus morphology and genetic expression.The emerging two-dimensional micropatterning techniques offer powerful tools to construct controllable and well-organized microenvironment for single-cell level investigations with qualitative analysis,cellular standardization,and in vivo environment mimicking.Here,we provide an overview of the basic principle and characteristics of the two most widely-used micropatterning techniques,including photolithographic micropatterning and soft lithography micropatterning.Moreover,we summarize the application of micropatterning technique in controlling cytoskeleton,cell migration,nucleus and gene expression,as well as intercellular communication.

Magnetic proximity effect in the two-dimensional ε-Fe_(2)O_(3)/NbSe_(2)heterojunction

Two-dimensional(2D)magnet/superconductor heterostructures can promote the design of artificial materials for exploring 2D physics and device applications by exotic proximity effects.However,plagued by the low Curie temperature and instability in air,it is hard to realize practical applications for the reported layered magnetic materials at present.In this paper,we developed a space-confined chemical vapor deposition method to synthesize ultrathin air-stable ε-Fe_(2)O_(3) nanosheets with Curie temperature above 350 K.The ε-Fe_(2)O_(3)/NbSe_(2) heterojunction was constructed to study the magnetic proximity effect on the superconductivity of the NbSe_(2) multilayer.The electrical transport results show that the subtle proximity effect can modulate the interfacial spin–orbit interaction while undegrading the superconducting critical parameters.Our work paves the way to construct 2D heterojunctions with ultrathin nonlayered materials and layered van der Waals(vdW)materials for exploring new physical phenomena.

Stacking-dependent exchange bias in two-dimensional ferromagnetic/antiferromagnetic bilayers

A clear microscopic understanding of exchange bias is crucial for its application in magnetic recording, and further progress in this area is desired. Based on the results of our first-principles calculations and Monte Carlo simulations,we present a theoretical proposal for a stacking-dependent exchange bias in two-dimensional compensated van der Waals ferromagnetic/antiferromagnetic bilayer heterostructures. The exchange bias effect emerges in stacking registries that accommodate inhomogeneous interlayer magnetic interactions between the ferromagnetic layer and different spin sublattices of the antiferromagnetic layer. Moreover, the on/off switching and polarity reversal of the exchange bias can be achieved by interlayer sliding, and the strength can be modulated using an external electric field. Our findings push the limits of exchange bias systems to extreme bilayer thickness in two-dimensional van der Waals heterostructures, potentially stimulating new experimental investigations and applications.

Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Research on aiming methods for small sample size shooting tests of two-dimensional trajectory correction fuse

The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.

High-performance flexible perovskite photodetectors based on single-crystal-like two-dimensional Ruddlesden-Popper thin films

Two-dimensional Ruddlesden-Popper(2DRP)perovskites have attracted intense research interest for optoelectronic applications,due to their tunable optoelectronic properties and better environmental stability than their threedimensional counterparts.Furthermore,high-performance photodetectors based on single-crystal and polycrystalline thin-films 2DRP perovskites have shown great potential for practical application.However,the complex growth process of single-crystal membranes and uncontrollable phase distribution of polycrystalline films hinder the further development of 2DRP perovskites photodetectors.Herein,we report a series of high-performance photodetectors based on single-crystal-like phase-pure 2DRP perovskite films by designing a novel spacer source.Experimental and theoretical evidence demonstrates that phase-pure films substantially suppress defect states and ion migration.These highly sensitive photodetectors show I_(light)/I_(dark) ratio exceeding 3×10^(4),responsivities exceeding 16 A/W,and detectivities exceeding 3×10^(13) Jones,which are higher at least by 1 order than those of traditional mixed-phase thinfilms 2DRP devices(close to the reported single-crystal devices).More importantly,this strategy can significantly enhance the operational stability of optoelectronic devices and pave the way to large-area flexible productions.

Two-dimensional silicon nanomaterials for optoelectronics

Silicon nanomaterials have been of immense interest in the last few decades due to their remarkable optoelectronic responses,elemental abundance,and higher biocompatibility.Two-dimensional silicon is one of the new allotropes of silicon and has many compelling properties such as quantum-confined photoluminescence,high charge carrier mobilities,anisotropic electronic and magnetic response,and non-linear optical properties.This review summarizes the recent advances in the synthesis of two-dimensional silicon nanomaterials with a range of structures(silicene,silicane,and multilayered silicon),surface ligand engineering,and corresponding optoelectronic applications.

Recent progress on two-dimensional ferroelectrics:Material systems and device applications

Ferroelectrics are a type of material with a polar structure and their polarization direction can be inverted reversibly by applying an electric field.They have attracted tremendous attention for their extensive applications in non-volatile memory,sensors and neuromorphic computing.However,conventional ferroelectric materials face insulating and interfacial issues in the commercialization process.In contrast,two-dimensional(2D)ferroelectric materials usually have excellent semiconductor performance,clean van der Waals interfaces and robust ferroelectric order in atom-thick layers,and hold greater promise for constructing multifunctional ferroelectric optoelectronic devices and nondestructive ultra-high-density memory.Recently,2D ferroelectrics have obtained impressive breakthroughs,showing overwhelming superiority.Herein,firstly,the progress of experimental research on 2D ferroelectric materials is reviewed.Then,the preparation of 2D ferroelectric devices and their applications are discussed.Finally,the future development trend of 2D ferroelectrics is looked at.

High-temperature ferromagnetism and strongπ-conjugation feature in two-dimensional manganese tetranitride

Two-dimensional(2D)magnetic materials have attracted tremendous research interest because of the promising application in the next-generation microelectronic devices.Here,by the first-principles calculations,we propose a twodimensional ferromagnetic material with high Curie temperature,manganese tetranitride MnN4monolayer,which is a square-planar lattice made up of only one layer of atoms.The structure is demonstrated to be stable by the phonon spectra and the molecular dynamic simulations,and the stability is ascribed to theπ–d conjugation betweenπorbital of N=N bond and d orbital of Mn.More interestingly,the MnN_(4)monolayer displays robust 2D ferromagnetism,which originates from the strong exchange couplings between Mn atoms due to theπ–d conjugation.The high critical temperature of 247 K is determined by solving the Heisenberg model using the Monte Carlo method.

Enhanced mechanical and thermal properties of two-dimensional SiC and GeC with temperature and size dependence

Two-dimensional materials with novel mechanical and thermal properties are available for sensors,photodetectors,thermoelectric,crystal diode and flexible nanodevices.In this investigation,the mechanical and thermal properties of pristine SiC and GeC are explored by molecular dynamics simulations.First,the fracture strength and fracture strain behaviors are addressed in the zigzag and armchair directions at 300 K.The excellent toughness of SiC and GeC is demonstrated by the maximal fracture strain of 0.43 and 0.47 in the zigzag direction,respectively.The temperature-tunable tensile strength of SiC and GeC is also investigated.Then,using non-equilibrium molecular dynamics(NEMD)calculations,the thermal performances of SiC and GeC are explored.In particular,the thermal conductivity of SiC and GeC shows a pronounced size dependence and reaches up to 85.67 W·m^(-1)-K^(-1)and 34.37 W·m^(-1)-K^(-1),respectively.The goal of our work is to provide a theoretical framework that can be used in the near future.This will enable us to design an efficient thermal management scheme for two-dimensional materials in electronics and optoelectronics.