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.

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 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 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.

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.

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.

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.

Preparation,Properties,and Applications of Low-Dimensional Molecular Organic Nanomaterials

In recent years, great progress has been made in research and development of small-molecule organic materials with various low-dimensional nanostructures. This paper presents a comprehensive review of recent research progress in this field, including preparation, electronic and optoelectronic properties and applications. First, an introduction gives to the reprecipitation, soft templates methods, and progress in synthesis and morphological control of low-dimensional small-molecule organic nanomaterials. Their unique optical and electronic properties and research progress in these aspects are reviewed and discussed in detail. Applications based on low-dimensional small-molecule organic nanomaterials are briefly described. Finally, some perspectives to the future development of this field are addressed.

Orientational Order of C_(60) Molecules in Low-dimensional Lattices

The orientational order is an important concept of the materials composed of large molecules or clusters. Using high-resolution scanning tunneling microscopy, we have studied the orientational order of two kinds of typical low-dimensional C60 lattices: two-dimensional molecules array and C60(111) multi-layer film surface. Due to the change of the crystal field, their orientational orders are distinctly different from those in bulk system, and some unique phenomena appear.

Ultrafast optical investigation of carrier and spin dynamics in low-dimensional perovskites

Low-dimensional perovskite(PVK)materials have attracted significant research interest,because of their quantum-confined effect,tunable band gap structures,and higher stability than that of three-dimensional(3D)PVKs.In semiconductor optoelectronic devices,high speed and small size are closely interlinked.The development of high-speed devices requires researchers to fully understand the properties of materials,especially the dynamic processes such as carrier recombination,separation,and transport,which often play a crucial role in the performance of devices.As an indispensable part of dynamic research,spin relaxation is also of great significance in studying the properties of materials and explore possible applications.Lead halide PVK materials have strong spin-orbit coupling(SOC),which provides a basis for information storage and processing by using spin degrees of freedom.Therefore,studying the carrier and spin dynamics of low-dimensional PVKs is an effective way to understand the internal properties of low-dimensional PVKs clearly.This paper summarizes the latest research progress on the ultrafast carrier and spin dynamics in low-dimensional PVKs,to comprehensively understand their carrier and spin behaviors and present an outlook for relevant studies in this area.

Optical and electrical anisotropy regulation engineering of low-dimensional materials toward polarized detection and imaging applications

Polarized-sensitive image sensors are a kind of photodetector with great development potential due to their enhanced ability to detect and identify the target objects from the aspect of spatial,spectral and polarized information.Recently,low-dimensional anisotropic materials with inherent anisotropic properties,ultrathin thickness,tunable bandgap and feasible integration with complementary metal oxide semiconductor(CMOS)fabrication processes have attracted great interest for their facilitation of polarized photodetector devices miniaturization.Maximizing the polarized detection performance of low-dimensional materials to satisfy realistic needs stimulates the exploration of modulation of anisotropic properties.In this review,we comprehensively introduce the latest research progress in modulating the optical and optoelectronic anisotropy characteristics of low-dimensional materials.The strategy of anisotropy regulation through crystal structure engineering and coupling system is discussed emphatically.Then,the latest progress in image recognition applications using anisotropic low-dimensional materials is reviewed in detail.Finally,we summarize the challenge and propose future opportunities in the practical application of polarized-sensitive imaging photodetectors based on low-dimensional anisotropic materials.

Mixed low-dimensional metal halide perovskite singlecrystal for low-detection-limit x-ray detection via orientedion migration

Low-dimensional metal halide perovskites exhibit exceptional photoelectronicproperties and intrinsic stability, positioning them as a promising class of semiconductormaterials for light-emitting devices and photodetectors. In thiswork, we present a millimeter-scale single crystal of mixed low-dimensional(one-dimensional–zero-dimensional [1D–0D]) organic lead iodide withwell-defined crystallinity. The fabricated single-crystal devices demonstratehigh-sensitivity photoresponse and x-ray detection performance. By spatiallyisolating organic molecules to form the mixed 1D–0D crystal structure, ionmigrations is effectively suppressed, resulting in a remarkable three orders ofmagnitude reduction in the dark current (56.4 pA @200 V) of the single-crystaldevices. Furthermore, by enhancing the background characteristics, weachieved an impressive low x-ray detection limit of 154.5 nGys^(-1) in the singlecrystaldevice. These findings highlight that the mixed 1D–0D organic leadiodide configuration efficiently controls ion migration within the crystal structure,offering a promising avenue for realizing high-performance perovskitebasedphotodetectors and x-ray detectors.

Dual function of formamidinium chloride additive improves the efficiency and stability of low-dimensional perovskite solar cells

Despite their excellent intrinsic stability,low-dimensional Ruddlesden-Popper(LDRP)perovskites face challenges with low power conversion efficiency(PCE),primarily due to the widen bandgap and limited charge transport caused by the bulky spacer cation.Herein,we introduce formamidinium chloride(FACl)as an additive into(4-FPEA)2MA4Pb5I16 perovskite.On the one hand,the addition of FACl narrows the bandgap through cation exchange between MA^(+)and FA^(+),thereby extending the light absorption range and enhancing photocurrent generation.On the other hand,this MA^(+)/FA^(+)cation exchange decelerates the sublimation of methylammonium chloride and prolongs the crystallization of LDRP perovskite,leading to higher crystallinity and better film quality with a decreased trap-state density.Consequently,this approach led to a remarkable PCE of 20.46%for<n>=5 LDRP perovskite solar cells(PSCs),ranking among the highest for MA/FA mixed low dimensional PSCs reported to date.Remarkably,our PSCs maintained 90%and 92%of the initial efficiency even after 1300 h at(60±5)℃and(60±5)%relative humidity,respectively.This work promotes the development of LDRP PSCs with excellent efficiency and environmental stability for potential commercial application.

Assembling of low-dimensional aggregates with interlaminar electromagnetic synergy network for high-efficient microwave absorption

Considering the risk of a sudden degeneration caused by the oxidation of MXenes in dielectric and microwave absorption properties,to enhance the oxidation resistance of multilayer MXenes can make them more applicable as microwave absorbers than those with few-layer.However,there remains disadvantage in optimizing the poor impedance matching and inherent aggregation of multilayer MXenes via rational assembling.In the present study,a facile self-assembly process is conducted to obtain 2D MXenes/1D MnO_(2)/0D NiCo_(2)S_(4) assembled lowdimensional aggregate with hierarchical structure and interlaminar electromagnetic synergy network.In addition to bridging adjacent MXenes lamellas for the enhancement of internal electron transport,high-density MnO2 can also combine with NiCo2S4 to form an electromagnetic synergy network between lamellas,thus improving microwave attenuation.Though the modulation of components and assembled structures,it is achievable to effectively adjust and optimize the performance in impedance matching and microwave absorption.Given the thickness of 2.17 mm,the optimal reflection loss of
59.23 dB,and the effective absorption bandwidth of 5.8 GHz are achieved.Moreover,the RCS simulations is performed to demonstrate its excellent performance.Thus,the present work contributes a facile method to the development of multi-layer MXenes based-MAs via interlaminar electromagnetic network design.