Equivalence of the equilibrium and the nonequilibrium molecular dynamics methods for thermal conductivity calculations: From bulk to nanowire silicon

Molecular dynamics simulations play an important role in studying heat transport in complex materials. The lattice thermal conductivity can be computed either using the Green-Kubo formula in equilibrium MD (EMD) simulations or using Fourier's law in nonequilibrium MD (NEMD) simulations. These two methods have not been systematically compared for materials with different dimensions and inconsistencies between them have been occasionally reported in the literature. Here we give an in-depth comparison of them in terms of heat transport in three allotropes of Si: three dimensional bulk silicon, two-dimensional silicene, and quasi-one-dimensional silicon nanowire. By multiplying the correlation time in the Green-Kubo formula with an appropriate effective group velocity, we can express the running thermal conductivity in the EMD method as a function of an effective length and directly compare it with the length-dependent thermal conductivity in the NEMD method. We find that the two methods quantitatively agree with each other for all the systems studied, firmly establishing their equivalence in computing thermal conductivity.Comment: 8 pages, 7 figure

Do the government subsidies inhibit the entity over-financialization? Fresh evidence from China

In order to verify effect of the industrial policies on solving the problem of market failure, we collect the data from China A-share listed companies among 2008-2019, and analyze the effect of government subsidies on the entity over-financialization. The results show that government subsidies significantly inhibit the entity over-financialization. Because the government subsidies could increase the performance of enterprise’s main business and level of the enterprise’s profitability. Subsequently, the enterprise’s arbitrage from cross-industries and the managers’ composition could be decreased. Consequently, government subsidies could reduce the entity over-financialization by the reduce of enterprise’s arbitrage from multi-industries and increase of the managers’ composition which is related to the enterprise’s performance. The results also indicate that the entity financialization is mainly motivated by enterprise arbitrage rather than ‘preventive reserve’ in China. Moreover, the inhibitory effect of government subsidies on the entity over-financialization is only significant in the enterprises with non-state-owned, high-tech, and higher level of demand of innovation. Thus, the government should accurately implement subsidy policies for the enterprises and increase the supports for enterprises with high-tech and higher level of demand of innovation, which could promote economy high-quality development

Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials

The standard equilibrium Green-Kubo and nonequilibrium molecular dynamics (MD) methods for computing thermal transport coefficients in solids typically require relatively long simulation times and large system sizes. To this end, we revisit here the homogeneous nonequilibrium MD method by Evans [Phys. Lett. A \textbf{91}, 457 (1982)] and generalize it to many-body potentials that are required for more realistic materials modeling. We also propose a method for obtaining spectral conductivity and phonon mean free path from the simulation data. This spectral decomposition method does not require lattice dynamics calculations and can find important applications in spatially complex structures. We benchmark the method by calculating thermal conductivities of three-dimensional silicon, two-dimensional graphene, and a quasi-one-dimensional carbon nanotube and show that the method is about one to two orders of magnitude more efficient than the Green-Kubo method. We apply the spectral decomposition method to examine the long-standing dispute over thermal conductivity convergence vs divergence in carbon nanotubes.Comment: 10 pages, 7 figure

Heat transport in pristine and polycrystalline single-layer hexagonal boron nitride

We use a phase field crystal model to generate large-scale bicrystalline and polycrystalline single-layer hexagonal boron nitride (h-BN) samples and employ molecular dynamics (MD) simulations with the Tersoff many-body potential to study their heat transport properties. The Kapitza thermal resistance across individual h-BN grain boundaries is calculated using the inhomogeneous nonequilibrium MD method. The resistance displays strong dependence on the tilt angle, the line tension and the defect density of the grain boundaries. We also calculate the thermal conductivity of pristine h-BN and polycrystalline h-BN with different grain sizes using an efficient homogeneous nonequilibrium MD method. The in-plane and the out-of-plane (flexural) phonons exhibit different grain size scalings of the thermal conductivity in polycrystalline h-BN and the extracted Kapitza conductance is close to that of large-tilt-angle grain boundaries in bicrystals.Comment: 12 pages, 9 figures, 2 tables, bicrystalline and polycrystalline samples availabl

Spherical Transformer: Adapting Spherical Signal to CNNs

Convolutional neural networks (CNNs) have been widely used in various vision tasks, e.g. image classification, semantic segmentation, etc. Unfortunately, standard 2D CNNs are not well suited for spherical signals such as panorama images or spherical projections, as the sphere is an unstructured grid. In this paper, we present Spherical Transformer which can transform spherical signals into vectors that can be directly processed by standard CNNs such that many well-designed CNNs architectures can be reused across tasks and datasets by pretraining. To this end, the proposed method first uses locally structured sampling methods such as HEALPix to construct a transformer grid by using the information of spherical points and its adjacent points, and then transforms the spherical signals to the vectors through the grid. By building the Spherical Transformer module, we can use multiple CNN architectures directly. We evaluate our approach on the tasks of spherical MNIST recognition, 3D object classification and omnidirectional image semantic segmentation. For 3D object classification, we further propose a rendering-based projection method to improve the performance and a rotational-equivariant model to improve the anti-rotation ability. Experimental results on three tasks show that our approach achieves superior performance over state-of-the-art methods

Patient-specific fetal radiation dosimetry for pregnant patients undergoing abdominal and pelvic CT imaging

Background: Accurate estimation of fetal radiation dose is crucial for risk-benefit analysis of radiological imaging, while the radiation dosimetry studies based on individual pregnant patient are highly desired. Purpose: To use Monte Carlo calculations for estimation of fetal radiation dose from abdominal and pelvic computed tomography (CT) examinations for a population of patients with a range of variations in patients’ anatomy, abdominal circumference, gestational age (GA), fetal depth (FD), and fetal development. Methods: Forty-four patient-specific pregnant female models were constructed based on CT imaging data of pregnant patients, with gestational ages ranging from 8 to 35 weeks. The simulation of abdominal and pelvic helical CT examinations was performed on three validated commercial scanner systems to calculate organ-level fetal radiation dose. Results: The absorbed radiation dose to the fetus ranged between 0.97 and 2.24 mGy, with an average of 1.63 ± 0.33 mGy. The CTDIvol-normalized fetal dose ranged between 0.56 and 1.30, with an average of 0.94 ± 0.25. The normalized fetal organ dose showed significant correlations with gestational age, maternal abdominal circumference (MAC), and fetal depth. The use of ATCM technique increased the fetal radiation dose in some patients. Conclusion: A technique enabling the calculation of organ-level radiation dose to the fetus was developed from models of actual anatomy representing a range of gestational age, maternal size, and fetal position. The developed maternal and fetal models provide a basis for reliable and accurate radiation dose estimation to fetal organs.</p