Low dimensional perovskites have recently attracted much attention due to their vertical growth of crys- talline orientation, excellent film morphology, and long-term humidity, light, and heat stability, How- ever, lo...Low dimensional perovskites have recently attracted much attention due to their vertical growth of crys- talline orientation, excellent film morphology, and long-term humidity, light, and heat stability, How- ever, low dimensional perovskites suffer fl'om low power conversion efficiency (PCE) with respect to their three dimensional analogues. Therefore, it is imperative to find excellent low-dimensional perovskite materials for improving the PCE. Previous work has demonstrated that bulkier organic molecules, e,g., C6Hs(CH2)2NH3+ (PEA+), CH3(CH2)3NH3+(n-BAT, iso-BA+), C2H4NH3 +, and polyethylenimine cations (PEI+), play an important role in the formation of low-dimensional perovskites. In this review, we review the recent development of low dimensional perovskites for solar cells application in terms of film preparation, photophysics, and stability of perovskites, as well as the related device structure and physics. We have also discussed the future development of low-dimensional perovskites from materials design, fabri- cation processes, and device structure.展开更多
Seismic data reconstruction is an essential and yet fundamental step in seismic data processing workflow,which is of profound significance to improve migration imaging quality,multiple suppression effect,and seismic i...Seismic data reconstruction is an essential and yet fundamental step in seismic data processing workflow,which is of profound significance to improve migration imaging quality,multiple suppression effect,and seismic inversion accuracy.Regularization methods play a central role in solving the underdetermined inverse problem of seismic data reconstruction.In this paper,a novel regularization approach is proposed,the low dimensional manifold model(LDMM),for reconstructing the missing seismic data.Our work relies on the fact that seismic patches always occupy a low dimensional manifold.Specifically,we exploit the dimension of the seismic patches manifold as a regularization term in the reconstruction problem,and reconstruct the missing seismic data by enforcing low dimensionality on this manifold.The crucial procedure of the proposed method is to solve the dimension of the patches manifold.Toward this,we adopt an efficient dimensionality calculation method based on low-rank approximation,which provides a reliable safeguard to enforce the constraints in the reconstruction process.Numerical experiments performed on synthetic and field seismic data demonstrate that,compared with the curvelet-based sparsity-promoting L1-norm minimization method and the multichannel singular spectrum analysis method,the proposed method obtains state-of-the-art reconstruction results.展开更多
The characterization of microstructure for three kinds of typical low dimensional materials,such as ultrafine particle(zero- dimension),whisker(one- dimension)and thin film(two-dimensions),has been carried out.The met...The characterization of microstructure for three kinds of typical low dimensional materials,such as ultrafine particle(zero- dimension),whisker(one- dimension)and thin film(two-dimensions),has been carried out.The methods and criteria for the characterization are investigated and introduced.Some interesting results of the characterization are reported.展开更多
Recently,the development of materials with circularly polarized luminescence(CPL)has attracted numerous attentions owing to their potential applications in various fields.Among diverse mechanisms for the origin of chi...Recently,the development of materials with circularly polarized luminescence(CPL)has attracted numerous attentions owing to their potential applications in various fields.Among diverse mechanisms for the origin of chiroptical properties in low dimensional semiconductors(LDS),the self-assembly approach provides a powerful technique for acquisition of strong chiroptical activity.Benefiting from this approach,LDS could be endowed with CPL in which the dissymmetry factor,a vital parameter for evaluating the performance of CPL,could be greatly improved.In this review,state-of-the-art of selfassembled LDS will be summarized.The current challenges and perspectives in this emerging field are also presented.This review could not only provide insights of the fundamentals of self-assembled chirality,but also shine light for designing CPL-active functional nanomaterials toward their applications based on novel optoelectronic devices.展开更多
Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the ...Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.展开更多
Neuronal ensemble activity codes working memory.In this work,we developed a neuronal ensemble sparse coding method,which can effectively reduce the dimension of the neuronal activity and express neural coding.Multicha...Neuronal ensemble activity codes working memory.In this work,we developed a neuronal ensemble sparse coding method,which can effectively reduce the dimension of the neuronal activity and express neural coding.Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze.As discretesignals,spikes were transferred into cont inuous signals by estinating entropy.Then the normalized continuous signals were decomposed via non-negative sparse met hod.The non-negative components were extracted to reconstruct a low-dimensional ensemble,while none of the feature components were missed.The results showed that,for well-trained rats,neuronal ensemble activities in the prefrontal cortex changed dynamically during the.working memory task.And the neuronal ensemble is more explicit via using non-negative sparse coding.Our results indicate that the neuronal ensemblesparse coding method can effectively reduce the dimnension of neuronal activity and it is a useful tool to express neural coding.展开更多
In this paper we analyze a long standing problem of the appearance of spurious,non-physical solutions arising in the application of the effective mass theory to low dimensional nanostructures.The theory results in a s...In this paper we analyze a long standing problem of the appearance of spurious,non-physical solutions arising in the application of the effective mass theory to low dimensional nanostructures.The theory results in a system of coupled eigenvalue PDEs that is usually supplemented by interface boundary conditions that can be derived from a variational formulation of the problem.We analyze such a system for the envelope functions and show that a failure to restrict their Fourier expansion coeffi-cients to small k components would lead to the appearance of non-physical solutions.We survey the existing methodologies to eliminate this difficulty and propose a simple and effective solution.This solution is demonstrated on an example of a two-band model for both bulk materials and low-dimensional nanostructures.Finally,based on the above requirement of small k,we derive a model for nanostructures with cylindrical symmetry and apply the developed model to the analysis of quantum dots using an eight-band model.展开更多
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 certi...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.展开更多
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...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.展开更多
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 ...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.展开更多
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 t...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.展开更多
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 ...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.展开更多
We have studied the optical spectra of low-dimensional semiconductor systems by calculating all possible optical transitions between electronic states. Optical absorption and emission have been obtained under differen...We have studied the optical spectra of low-dimensional semiconductor systems by calculating all possible optical transitions between electronic states. Optical absorption and emission have been obtained under different carrier population conditions and in different photon wavelengths. The line-shapes of the peaks in the optical spectrum are determined by the density of electronic states of the system, and the symmetries and intensities of these peaks can be improved by reducing the dimensionality of the system. Optical gain requires in general a population inversion, whereas for a quantum-dot system, there exists a threshold value of the population inversion.展开更多
To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.Fir...To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.展开更多
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( PO...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.展开更多
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 ...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.展开更多
大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油...大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油含水率软件检测大豆含油率;核磁共振成像(magnetic resonance imaging,MRI)结合深度学习,建立大豆含油率高低判别模型。引入低场二维核磁共振(low field two-dimensional nuclear magnetic resonance,LF-2D-NMR)技术,定性分析一维波谱中信号重叠无法区分组分的问题。试验结果表明,LF-NMR含油含水率软件能快速准确检测大豆含油率,T1-T2二维核磁图谱成功解决了自由水和油信号重叠问题。利用U-net++深度学习模型对MRI成像的矢状面、冠状面、横截面以及三面混合数据集进行训练,其中横截面评价指标与其他数据集相比更优,语义分割部分中平均交并比(mean intersection over union,mIoU)约0.9058,全局准确率0.9980,训练后的模型能够将MRI图像识别并分割,快速判别大豆含油率高低。试验证明,LF-NMR及MRI能够快速无损掌握大豆含油率信息,为大豆的高油育种提供了新思路和技术支持。展开更多
基金financially supported by the National Basic Research Program of China,Fundamental Studies of Perovskite Solar Cells(Grant 2015CB932200)the Natural Science Foundation of China(Grant 51035063)+2 种基金Natural Science Foundation of Jiangsu Province,China(Grants 55135039 and 55135040)Jiangsu Specially-Appointed Professor program(Grant 54907024)Startup from Nanjing Tech University(Grants 3983500160,3983500151,and 44235022)
文摘Low dimensional perovskites have recently attracted much attention due to their vertical growth of crys- talline orientation, excellent film morphology, and long-term humidity, light, and heat stability, How- ever, low dimensional perovskites suffer fl'om low power conversion efficiency (PCE) with respect to their three dimensional analogues. Therefore, it is imperative to find excellent low-dimensional perovskite materials for improving the PCE. Previous work has demonstrated that bulkier organic molecules, e,g., C6Hs(CH2)2NH3+ (PEA+), CH3(CH2)3NH3+(n-BAT, iso-BA+), C2H4NH3 +, and polyethylenimine cations (PEI+), play an important role in the formation of low-dimensional perovskites. In this review, we review the recent development of low dimensional perovskites for solar cells application in terms of film preparation, photophysics, and stability of perovskites, as well as the related device structure and physics. We have also discussed the future development of low-dimensional perovskites from materials design, fabri- cation processes, and device structure.
基金supported by National Natural Science Foundation of China(Grant No.41874146 and No.42030103)Postgraduate Innovation Project of China University of Petroleum(East China)(No.YCX2021012)
文摘Seismic data reconstruction is an essential and yet fundamental step in seismic data processing workflow,which is of profound significance to improve migration imaging quality,multiple suppression effect,and seismic inversion accuracy.Regularization methods play a central role in solving the underdetermined inverse problem of seismic data reconstruction.In this paper,a novel regularization approach is proposed,the low dimensional manifold model(LDMM),for reconstructing the missing seismic data.Our work relies on the fact that seismic patches always occupy a low dimensional manifold.Specifically,we exploit the dimension of the seismic patches manifold as a regularization term in the reconstruction problem,and reconstruct the missing seismic data by enforcing low dimensionality on this manifold.The crucial procedure of the proposed method is to solve the dimension of the patches manifold.Toward this,we adopt an efficient dimensionality calculation method based on low-rank approximation,which provides a reliable safeguard to enforce the constraints in the reconstruction process.Numerical experiments performed on synthetic and field seismic data demonstrate that,compared with the curvelet-based sparsity-promoting L1-norm minimization method and the multichannel singular spectrum analysis method,the proposed method obtains state-of-the-art reconstruction results.
文摘The characterization of microstructure for three kinds of typical low dimensional materials,such as ultrafine particle(zero- dimension),whisker(one- dimension)and thin film(two-dimensions),has been carried out.The methods and criteria for the characterization are investigated and introduced.Some interesting results of the characterization are reported.
基金the National Natural Science Foundation of China(62174079)Science,Technology and Innovation Commission of Shenzhen Municipality(Projects Nos.JCYJ20220530113015035,JCYJ20210324120204011 and KQTD2015071710313656).
文摘Recently,the development of materials with circularly polarized luminescence(CPL)has attracted numerous attentions owing to their potential applications in various fields.Among diverse mechanisms for the origin of chiroptical properties in low dimensional semiconductors(LDS),the self-assembly approach provides a powerful technique for acquisition of strong chiroptical activity.Benefiting from this approach,LDS could be endowed with CPL in which the dissymmetry factor,a vital parameter for evaluating the performance of CPL,could be greatly improved.In this review,state-of-the-art of selfassembled LDS will be summarized.The current challenges and perspectives in this emerging field are also presented.This review could not only provide insights of the fundamentals of self-assembled chirality,but also shine light for designing CPL-active functional nanomaterials toward their applications based on novel optoelectronic devices.
文摘Signal processing in phase space based on nonlinear dynamics theory is a new method for underwater acoustic signal processing. One key problem when analyzing actual acoustic signal in phase space is how to reduce the noise and lower the embedding dimen- sion. In this paper, local-geometric-projection method is applied to obtain fow dimensional element from various target radiating noise and the derived phase portraits show obviously low dimensional attractors. Furthermore, attractor dimension and cross prediction error are used for classification. It concludes that combining these features representing the geometric and dynamical properties respectively shows effects in target classification.
基金supported by the National Natural Science Foundation of China(No.61074131,91132722)the Doctoral Fund of the Ministry of Education of China(20101202110007).
文摘Neuronal ensemble activity codes working memory.In this work,we developed a neuronal ensemble sparse coding method,which can effectively reduce the dimension of the neuronal activity and express neural coding.Multichannel spike trains were recorded in rat prefrontal cortex during a work memory task in Y-maze.As discretesignals,spikes were transferred into cont inuous signals by estinating entropy.Then the normalized continuous signals were decomposed via non-negative sparse met hod.The non-negative components were extracted to reconstruct a low-dimensional ensemble,while none of the feature components were missed.The results showed that,for well-trained rats,neuronal ensemble activities in the prefrontal cortex changed dynamically during the.working memory task.And the neuronal ensemble is more explicit via using non-negative sparse coding.Our results indicate that the neuronal ensemblesparse coding method can effectively reduce the dimnension of neuronal activity and it is a useful tool to express neural coding.
文摘In this paper we analyze a long standing problem of the appearance of spurious,non-physical solutions arising in the application of the effective mass theory to low dimensional nanostructures.The theory results in a system of coupled eigenvalue PDEs that is usually supplemented by interface boundary conditions that can be derived from a variational formulation of the problem.We analyze such a system for the envelope functions and show that a failure to restrict their Fourier expansion coeffi-cients to small k components would lead to the appearance of non-physical solutions.We survey the existing methodologies to eliminate this difficulty and propose a simple and effective solution.This solution is demonstrated on an example of a two-band model for both bulk materials and low-dimensional nanostructures.Finally,based on the above requirement of small k,we derive a model for nanostructures with cylindrical symmetry and apply the developed model to the analysis of quantum dots using an eight-band model.
基金supported by the Doctoral Program of Higher Education(20130142120075)the Fundamental Research Funds for the Central Universities(HUST:2016YXMS032)National Key Research and Development Program of China(Grant No.2016YFB0700702)
文摘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.
基金Project supported by the National Natural Science Foundation of China (Grant No 10547006).
文摘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.
基金support from the Robert A.Welch Foundation(E-1728)National Science Foundation(EEC-1530753)supported by the State of Texas through the Texas Center for superconductivity at the University of Houston
文摘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.
基金supported by the National Natural Science Foundation of China(11222217)the State Key Laboratory of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics(MCMS-0414G01)
文摘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.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11374082 and 51671048)the Ten Thousand Talents Plan of Zhejiang Province of China(Grant No.2018R52003)。
文摘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.
文摘We have studied the optical spectra of low-dimensional semiconductor systems by calculating all possible optical transitions between electronic states. Optical absorption and emission have been obtained under different carrier population conditions and in different photon wavelengths. The line-shapes of the peaks in the optical spectrum are determined by the density of electronic states of the system, and the symmetries and intensities of these peaks can be improved by reducing the dimensionality of the system. Optical gain requires in general a population inversion, whereas for a quantum-dot system, there exists a threshold value of the population inversion.
基金Project(60925011) supported by the National Natural Science Foundation for Distinguished Young Scholars of ChinaProject(9140A06040510BQXXXX) supported by Advanced Research Foundation of General Armament Department,China
文摘To address the issue of premature convergence and slow convergence rate in three-dimensional (3D) route planning of unmanned aerial vehicle (UAV) low-altitude penetration,a novel route planning method was proposed.First and foremost,a coevolutionary multi-agent genetic algorithm (CE-MAGA) was formed by introducing coevolutionary mechanism to multi-agent genetic algorithm (MAGA),an efficient global optimization algorithm.A dynamic route representation form was also adopted to improve the flight route accuracy.Moreover,an efficient constraint handling method was used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation.Simulation and corresponding analysis show that the planning results of CE-MAGA have better performance on terrain following,terrain avoidance,threat avoidance (TF/TA2) and lower route costs than other existing algorithms.In addition,feasible flight routes can be acquired within 2 s,and the convergence rate of the whole evolutionary process is very fast.
基金Sponsored by the National Natural Science Foundation of China(Grant o.51576051)
文摘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.
基金supported by the National Natural Science Foundation of China (NSFC) under Grant No.60736005 and 60425101-1the Foundation for Innovative Research Groups of the NSFC under Grant No.60721001+3 种基金Provincial Project under grant No.9140A02060609DZ0208 and No.20090185110020Program for New Century Excellent Talents in University under Grant No.NCET-06-0812 and No. 08-0088SRF for ROCS,SEM under Grant No.GGRYJJ08-05Young Excellent Project of Sichuan Province under Grant No.09ZQ026-074
文摘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.
文摘大豆含油率的高低直接影响榨油与育种结果。为探究大豆含油率的最佳检测方法与构建含油率高低判别模型,该研究基于不同维度低场核磁共振(low field nuclear magnetic resonance,LF-NMR)技术,以国标法为对照,利用LF-NMR波谱和LF-NMR含油含水率软件检测大豆含油率;核磁共振成像(magnetic resonance imaging,MRI)结合深度学习,建立大豆含油率高低判别模型。引入低场二维核磁共振(low field two-dimensional nuclear magnetic resonance,LF-2D-NMR)技术,定性分析一维波谱中信号重叠无法区分组分的问题。试验结果表明,LF-NMR含油含水率软件能快速准确检测大豆含油率,T1-T2二维核磁图谱成功解决了自由水和油信号重叠问题。利用U-net++深度学习模型对MRI成像的矢状面、冠状面、横截面以及三面混合数据集进行训练,其中横截面评价指标与其他数据集相比更优,语义分割部分中平均交并比(mean intersection over union,mIoU)约0.9058,全局准确率0.9980,训练后的模型能够将MRI图像识别并分割,快速判别大豆含油率高低。试验证明,LF-NMR及MRI能够快速无损掌握大豆含油率信息,为大豆的高油育种提供了新思路和技术支持。