Synthesis and Modulation of Low-Dimensional Transition Metal Chalcogenide Materials via Atomic Substitution

In recent years,low-dimensional transition metal chalcogenide(TMC)materials have garnered growing research attention due to their superior electronic,optical,and catalytic properties compared to their bulk counterparts.The controllable synthesis and manipulation of these materials are crucial for tailoring their properties and unlocking their full potential in various applications.In this context,the atomic substitution method has emerged as a favorable approach.It involves the replacement of specific atoms within TMC structures with other elements and possesses the capability to regulate the compositions finely,crystal structures,and inherent properties of the resulting materials.In this review,we present a comprehensive overview on various strategies of atomic substitution employed in the synthesis of zero-dimensional,one-dimensional and two-dimensional TMC materials.The effects of substituting elements,substitution ratios,and substitution positions on the structures and morphologies of resulting material are discussed.The enhanced electrocatalytic performance and photovoltaic properties of the obtained materials are also provided,emphasizing the role of atomic substitution in achieving these advancements.Finally,challenges and future prospects in the field of atomic substitution for fabricating low-dimensional TMC materials are summarized.

Constructing low-dimensional perovskite network to assist efficient and stable perovskite solar cells

The use of low-dimensional(LD)perovskite materials is crucial for achieving high-performance perovskite solar cells(PSCs).However,LD perovskite films fabricated by conventional approaches give rise to full coverage of the underlying 3D perovskite films,which inevitably hinders the transport of charge carriers at the interface of PSCs.Here,we designed and fabricated LD perovskite structure that forms net-like morphology on top of the underlying three-dimensional(3D)perovskite bulk film.The net-like LD perovskite not only reduced the surface defects of 3D perovskite film,but also provided channels for the vertical transport of charge carriers,effectively enhancing the interfacial charge transfer at the LD/3D hetero-interface.The net-like morphological design comprising LD perovskite effectively resolves the contradiction between interfacial defect passivation and carrier extraction across the hetero-interfaces.Furthermore,the net-like LD perovskite morphology can enhance the stability of the underlying 3D perovskite film,which is attributed to the hydrophobic nature of LD perovskite.As a result,the net-like LD perovskite film morphology assists PSCs in achieving an excellent power conversion efficiency of up to 24.6%with over 1000 h long-term operational stability.

Machine Learning-Assisted Low-Dimensional Electrocatalysts Design for Hydrogen Evolution Reaction

Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.Nevertheless,the conventional"trial and error"method for producing advanced electrocatalysts is not only cost-ineffective but also time-consuming and labor-intensive.Fortunately,the advancement of machine learning brings new opportunities for electrocatalysts discovery and design.By analyzing experimental and theoretical data,machine learning can effectively predict their hydrogen evolution reaction(HER)performance.This review summarizes recent developments in machine learning for low-dimensional electrocatalysts,including zero-dimension nanoparticles and nanoclusters,one-dimensional nanotubes and nanowires,two-dimensional nanosheets,as well as other electrocatalysts.In particular,the effects of descriptors and algorithms on screening low-dimensional electrocatalysts and investigating their HER performance are highlighted.Finally,the future directions and perspectives for machine learning in electrocatalysis are discussed,emphasizing the potential for machine learning to accelerate electrocatalyst discovery,optimize their performance,and provide new insights into electrocatalytic mechanisms.Overall,this work offers an in-depth understanding of the current state of machine learning in electrocatalysis and its potential for future research.

Low-dimensional perovskite modified 3D structures for higher-performance solar cells

For solution prepared perovskite solar cells,metal halide perovskite materials with low-dimensional(LD)are flexibly employed in 3D perovskite solar cells to promote efficiency and long-term stability.In this review,the various structures,properties,and applications of LD perovskites are firstly summarized and discussed.To take advantage of LD materials,LD perovskites are introduced in the 3D bulk and/or the interface between the perovskite thin film and the carrier transporting layer to passivate the gain boundary defects while providing the stability advantage of LD materials.Therefore,the preparation methods and crystallization control of the LD perovskite layers are discussed in depth.Then,the combined devices using both LD and 3D components are reviewed on the basis of device design,cell structure,interface charge transfer,energy lever alignment,and synergistic improvement of both efficiency and stability.Finally,the challenges and expectations are speculated for further development of perovskite solar cells.

Numerical manifold method for thermo-mechanical coupling simulation of fractured rock mass

As a calculation method based on the Galerkin variation,the numerical manifold method(NMM)adopts a double covering system,which can easily deal with discontinuous deformation problems and has a high calculation accuracy.Aiming at the thermo-mechanical(TM)coupling problem of fractured rock masses,this study uses the NMM to simulate the processes of crack initiation and propagation in a rock mass under the influence of temperature field,deduces related system equations,and proposes a penalty function method to deal with boundary conditions.Numerical examples are employed to confirm the effectiveness and high accuracy of this method.By the thermal stress analysis of a thick-walled cylinder(TWC),the simulation of cracking in the TWC under heating and cooling conditions,and the simulation of thermal cracking of the SwedishÄspöPillar Stability Experiment(APSE)rock column,the thermal stress,and TM coupling are obtained.The numerical simulation results are in good agreement with the test data and other numerical results,thus verifying the effectiveness of the NMM in dealing with thermal stress and crack propagation problems of fractured rock masses.

Delineating homogeneous domains of fractured rocks using topological manifolds and deep learning

Determining homogeneous domains statistically is helpful for engineering geological modeling and rock mass stability evaluation.In this text,a technique that can integrate lithology,geotechnical and structural information is proposed to delineate homogeneous domains.This technique is then applied to a high and steep slope along a road.First,geological and geotechnical domains were described based on lithology,faults,and shear zones.Next,topological manifolds were used to eliminate the incompatibility between orientations and other parameters(i.e.trace length and roughness)so that the data concerning various properties of each discontinuity can be matched and characterized in the same Euclidean space.Thus,the influence of implicit combined effect in between parameter sequences on the homogeneous domains could be considered.Deep learning technique was employed to quantify abstract features of the characterization images of discontinuity properties,and to assess the similarity of rock mass structures.The results show that the technique can effectively distinguish structural variations and outperform conventional methods.It can handle multisource engineering geological information and multiple discontinuity parameters.This technique can also minimize the interference of human factors and delineate homogeneous domains based on orientations or multi-parameter with arbitrary distributions to satisfy different engineering requirements.

A STABILITY RESULT FOR TRANSLATINGSPACELIKE GRAPHS IN LORENTZ MANIFOLDS

In this paper,we investigate spacelike graphs defined over a domain Ω⊂M^(n) in the Lorentz manifold M^(n)×ℝ with the metric−ds^(2)+σ,where M^(n) is a complete Riemannian n-manifold with the metricσ,Ωhas piecewise smooth boundary,and ℝ denotes the Euclidean 1-space.We prove an interesting stability result for translating spacelike graphs in M^(n)×ℝ under a conformal transformation.

Galerkin-based quasi-smooth manifold element(QSME)method for anisotropic heat conduction problems in composites with complex geometry

The accurate and efficient analysis of anisotropic heat conduction problems in complex composites is crucial for structural design and performance evaluation. Traditional numerical methods, such as the finite element method(FEM), often face a trade-off between calculation accuracy and efficiency. In this paper, we propose a quasi-smooth manifold element(QSME) method to address this challenge, and provide the accurate and efficient analysis of two-dimensional(2D) anisotropic heat conduction problems in composites with complex geometry. The QSME approach achieves high calculation precision by a high-order local approximation that ensures the first-order derivative continuity.The results demonstrate that the QSME method is robust and stable, offering both high accuracy and efficiency in the heat conduction analysis. With the same degrees of freedom(DOFs), the QSME method can achieve at least an order of magnitude higher calculation accuracy than the traditional FEM. Additionally, under the same level of calculation error, the QSME method requires 10 times fewer DOFs than the traditional FEM. The versatility of the proposed QSME method extends beyond anisotropic heat conduction problems in complex composites. The proposed QSME method can also be applied to other problems, including fluid flows, mechanical analyses, and other multi-field coupled problems, providing accurate and efficient numerical simulations.

Isometric Immersions of Lightlike Warped Product Manifolds

In this paper, we deal with isommetric immersions of globally null warped product manifolds into Lorentzian manifolds with constant curvature c in codimension k≥3. Under the assumptions that the globally null warped product manifold has no points with the same constant sectional curvature c as the Lorentzian ambient, we show that such isometric immersion splits into warped product of isometric immersions.

Low-dimensional multi-spectral space for color reproduction based on nonnegative constrained principal component analysis

In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.

Low-dimensional structures formed by irradiation of laser

Some kinds of low-dimensional nanostructures can be formed by irradiation of laser on the pure silicon sample and the SiGe alloy sample. This paper has studied the photoluminescence （PL） of the hole-net structure of silicon and the porous structure of SiGe where the PL intensity at 706nm and 725nm wavelength increases obviously. The effect of intensity-enhancing in the PL peaks cannot be explained within the quantum confinement alone. A mechanism for increasing PL emission in the above structures is proposed, in which the trap states of the interface between SiO2 and nanocrystal play an important role.

Low-Dimensional Halide Perovskites and Their Advanced Optoelectronic Applications

Metal halide perovskites are crystalline materials originally developed out of scientific curiosity. They have shown great potential as active materials in optoelectronic applications. In the last 6 years, their certified photovoltaic efficiencies have reached 22.1%. Compared to bulk halide perovskites, low-dimensional ones exhibited novel physical properties. The photoluminescence quantum yields of perovskite quantum dots are close to 100%. The external quantum efficiencies and current efficiencies of perovskite quantum dot light-emitting diodes have reached 8% and 43 cd A^(-1),respectively, and their nanowire lasers show ultralow-threshold room-temperature lasing with emission tunability and ease of synthesis. Perovskite nanowire photodetectors reached a responsivity of 10 A W^(-1)and a specific normalized detectivity of the order of 10^(12 )Jones. Different from most reported reviews focusing on photovoltaic applications, we summarize the rapid progress in the study of low-dimensional perovskite materials, as well as their promising applications in optoelectronic devices. In particular, we review the wide tunability of fabrication methods and the state-of-the-art research outputs of low-dimensional perovskite optoelectronic devices. Finally, the anticipated challenges and potential for this exciting research are proposed.

Low-dimensional materials for photovoltaic application

The photovoltaic(PV)market is currently dominated by silicon based solar cells.However technological diversification is essential to promote competition,which is the driving force for technological growth.Historically,the choice of PV materials has been limited to the three-dimensional(3D)compounds with a high crystal symmetry and direct band gap.However,to meet the strict demands for sustainable PV applications,material space has been expanded beyond 3D compounds.In this perspective we discuss the potential of low-dimensional materials(2D,1D)for application in PVs.We present unique features of low-dimensional materials in context of their suitability in the solar cells.The band gap,absorption,carrier dynamics,mobility,defects,surface states and growth kinetics are discussed and compared to 3D counterparts,providing a comprehensive view of prospects of low-dimensional materials.Structural dimensionality leads to a highly anisotropic carrier transport,complex defect chemistry and peculiar growth dynamics.By providing fundamental insights into these challenges we aim to deepen the understanding of low-dimensional materials and expand the scope of their application.Finally,we discuss the current research status and development trend of solar cell devices made of low-dimensional materials.

Origin of Luminescent Centers and Edge States in Low-Dimensional Lead Halide Perovskites:Controversies,Challenges and Instructive Approaches

With only a few deep-level defect states having a high formation energy and dominance of shallow carrier non-trapping defects,the defect-tolerant electronic and optical properties of lead halide perovskites have made them appealing materials for high-efficiency,low-cost,solar cells and light-emitting devices.As such,recent observations of apparently deep-level and highly luminescent states in low-dimensional perovskites have attracted enormous attention as well as intensive debates.The observed green emission in 2D CsPb2Br5 and 0 D Cs4PbBr6 poses an enigma over whether it is originated from intrinsic point defects or simply from highly luminescent CsPbBr3 nanocrystals embedded in the otherwise transparent wide band gap semiconductors.The nature of deep-level edge emission in 2D Ruddlesden–Popper perovskites is also not well understood.In this mini review,the experimental evidences that support the opposing interpretations are analyzed,and challenges and root causes forthe controversy are discussed.Shortcomings in the current density functional theory approaches to modeling of properties and intrinsic point defects in lead halide perovskites are also noted.Selected experimental approaches are suggested to better correlate property with structure of a material and help resolve the controversies.Understanding and identification of the origin of luminescent centers will help design and engineer perovskites for wide device applications.

Negative photoconductivity in low-dimensional materials

In recent years,low-dimensional materials have received extensive attention in the field of electronics and optoelectronics.Among them,photoelectric devices based on photoconductive effect in low-dimensional materials have a broad development space.In contrast to positive photoconductivity,negative photoconductivity(NPC)refers to a phenomenon that the conductivity decreases under illumination.It has novel application prospects in the field of optoelectronics,memory,and gas detection,etc.In this paper,we review reports about the NPC effect in low-dimensional materials and systematically summarize the mechanisms to form the NPC effect in existing low-dimensional materials.

Heat transport in low-dimensional materials: A review and perspective

Heat transport is a key energetic process in materials and devices. The reduced sample size, low dimension of the problem and the rich spectrum of material imperfections introduce fruitful phenomena at nanoscale. In this review, we summarize recent progresses in the understanding of heat transport process in low-dimensional materials, with focus on the roles of defects, disorder, interfaces, and the quantum- mechanical effect. New physics uncovered from computational simulations, experimental studies, and predictable models will be reviewed, followed by a perspective on open challenges.

A low-dimensional crystal growth model on an isotropic and quasi-free sustained substrate

A new crystal growth theoretical model is established for the low-dimensional nanocrystals on an isotropic and quasifree sustained substrate. The driven mechanism of the model is based on the competitive growth among the preferential growth directions of the crystals possessing anisotropic crystal structures, such as the hexagonal close-packed and wurtzite structures. The calculation results are in good agreement with the experimental findings in the growth process of the lowdimensional Zn nanocrystals on silicone oil surfaces. Our model shows a growth mechanism of various low-dimensional crystals on/in the isotropic substrates.

POD Analysis and Low-Dimensional Model Based on POD-Galerkin for Two-Dimensional Rayleigh-Bénard Convection

Direct numerical simulation based on OpenFOAM is carried out for two-dimensional RayleighBénard( RB) convection in a square domain at high Rayleigh number of 107 and Pr = 0.71. Proper orthogonal decomposition( POD) is used to analyze the flow and temperature characteristics from POD energy spectrum and eigenmodes. The results show that the energy spectrum converges fast and the scale of vortex structures captured by eigenmodes becomes smaller as the eigenmode order increases. Meanwhile,a low-dimensional model( LDM) for RB convection is derived based on POD eigenmodes used as a basis of Galerkin project of Navier-Stokes-Boussinesq equations. LDM is built based on different number of eigenmodes and through the analysis of phase portraits,streamline and isothermal predicted by LDM,it is suggested that the error between LDM and DNS is still large.

Secret Sharing Scheme Based on the Differential Manifold

In this paper, the concepts of topological space and differential manifold are introduced, and it is proved that the surface determined by function F (x2, x2, …, xt) of class Cr in Euelidean Rt is a differential manifold. Using the intersection of the tangent plane and the hypernormal of the differential manifold to construct the shared master key of participants, an intuitive, secure and complete (t,n)-threshold secret sharing scheme is designed. The paper is proved to be safe, and the probability of successful attack of attackers is only 1/pt-1. When the prime number p is sufficiently large, the probability is almost 0. The results show that this scheme has the characteristics of single-parameter representation of the master key in the geometric method, and is more practical and easy to implement than the Blakley threshold secret sharing scheme.

SOME CONVERGENCE PROBLEMS REGARDING THE FRACTIONAL SCHRODINGER PROPAGATOR ON NONCOMPACT MANIFOLDS

Let L be the Laplace-Beltrami operator.On an n-dimensional(n≥2),complete,noncompact Riemannian manifold M,we prove that if 0<α<1,s>α/2 and f∈Hs(M),then the fractional Schr?dinger propagator e(it|L|α/2)(f)(x)→f(x)a.e.as t→0.In addition,for when M is a Lie group,the rate of the convergence is also studied.These results are a non-trivial extension of results on Euclidean spaces and compact manifolds.