Loss-free tensile ductility of dual-structure titanium composites via an interdiffusion and self-organization strategy.

The deformation-coordination ability between ductile metal and brittle dispersive ceramic particles is poor, which means that an improvement in strength will inevitably sacrifice ductility in dispersion-strengthened metallic materials. Here, we present an inspired strategy for developing dual-structure-based titanium matrix composites (TMCs) that achieve 12.0% elongation comparable to the matrix Ti6Al4V alloys and enhanced strength compared to homostructure composites. The proposed dual-structure comprises a primary structure, namely, a TiB whisker-rich region engendered fine grain Ti6Al4V matrix with a three-dimensional micropellet architecture (3D-MPA), and an overall structure consisting of evenly distributed 3D-MPA "reinforcements" and a TiBw-lean titanium matrix. The dual structure presents a spatially heterogeneous grain distribution with 5.8 µm fine grains and 42.3 µm coarse grains, which exhibits excellent hetero-deformation-induced (HDI) hardening and achieves a 5.8% ductility. Interestingly, the 3D-MPA "reinforcements" show 11.1% isotropic deformability and 66% dislocation storage, which endows the TMCs with good strength and loss-free ductility. Our enlightening method uses an interdiffusion and self-organization strategy based on powder metallurgy to enable metal matrix composites with the heterostructure of the matrix and the configuration of reinforcement to address the strength-ductility trade-off dilemma.

Parallel Frequency Function-Deep Neural Network for Efficient Approximation of Complex Broadband Signals.

In recent years, with the growing popularity of complex signal approximation via deep neural networks, people have begun to pay close attention to the spectral bias of neural networks-a problem that occurs when a neural network is used to fit broadband signals. An important direction taken to overcome this problem is the use of frequency selection-based fitting techniques, of which the representative work is called the PhaseDNN method, whose core idea is the use of bandpass filters to extract frequency bands with high energy concentration and fit them by different neural networks. Despite the method's high accuracy, we found in a large number of experiments that the method is less efficient for fitting broadband signals with smooth spectrums. In order to substantially improve its efficiency, a novel candidate-the parallel frequency function-deep neural network (PFF-DNN)-is proposed by utilizing frequency domain analysis of broadband signals and the spectral bias nature of neural networks. A substantial improvement in efficiency was observed in the extensive numerical experiments. Thus, the PFF-DNN method is expected to become an alternative solution for broadband signal fitting.

[Study on the epidemic development of COVID-19 in Hubei province by a modified SEIR model].

OBJECTIVE: To establish a SEIR epidemic dynamics model that can be used to evaluate the COVID-19 epidemic, and to predict and evaluate the COVID-19 epidemic in Hubei province using the proposed model. METHODS: COVID-19 SEIR transmission dynamics model was established, which took transmission ability in latent period and tracking quarantine interventions into consideration. Based on the epidemic data of Hubei province from January 23, 2020 to February 24, 2020, the parameters of the newly established modified SEIR model were fitted. By using Euler integral algorithm to solve the modified SEIR dynamics model, the epidemic situation in Hubei province was analyzed, and the impact of prevention and control measures such as quarantine and centralized treatment on the epidemic development was discussed. RESULTS: The theoretical estimation of the epidemic situation by the modified SEIR epidemic dynamics model is in good agreement with the actual situation in Hubei province. Theoretical analysis showed that prevention and control quarantine and medical follow-up quarantine played an important inhibitory effect on the outbreak of the epidemic.The centralized treatment played a key role in the rapid decline in the number of infected people. In addition, it is suggested that individuals should improve their prevention awareness and take strict self-protection measures to curb the increase in infected people. CONCLUSIONS: The modified SEIR model is reliable in the evaluation of COVID-19 epidemic in Hubei province, which provides a theoretical reference for the decision-making of epidemic interventions.

Size-dependent melting modes and behaviors of Ag nanoparticles: a molecular dynamics study.

The size-dependent melting behaviors and mechanisms of Ag nanoparticles (NPs) with diameters of 3.5-16 nm were investigated by molecular dynamics (MD). Two distinct melting modes, non-premelting and premelting with transition ranges of about 7-8 nm, for Ag NPs were demonstrated via the evolution of distribution and transition of atomic physical states during annealing. The small Ag NPs (3.5-7 nm) melt abruptly without a stable liquid shell before the melting point, which is characterized as non-premelting. A solid-solid crystal transformation is conducted through the migration of adatoms on the surface of Ag NPs with diameters of 3.5-6 nm before the initial melting, which is mainly responsible for slightly increasing the melting point of Ag NPs. On the other hand, surface premelting of Ag NPs with diameters of 8-16 nm propagates from the outer shell to the inner core with initial anisotropy and late isotropy as the temperature increases, and the close-packed facets {111} melt by a side-consumed way which is responsible for facets {111} melting in advance relative to the crystallographic plane {111}. Once a stable liquid shell is formed, its size-independent minimum thickness is obtained, and a three-layer structure of atomic physical states is set up. Lastly, the theory of point defect-pair (vacancy-interstitial) severing as the mechanism of formation and movement of the solid-liquid interface was also confirmed. Our study provides a basic understanding and theoretical guidance for the research, production and application of Ag NPs.

Dual attention enhancement feature fusion network for segmentation and quantitative analysis of paediatric echocardiography.

Paediatric echocardiography is a standard method for screening congenital heart disease (CHD). The segmentation of paediatric echocardiography is essential for subsequent extraction of clinical parameters and interventional planning. However, it remains a challenging task due to (1) the considerable variation of key anatomic structures, (2) the poor lateral resolution affecting accurate boundary definition, (3) the existence of speckle noise and artefacts in echocardiographic images. In this paper, we propose a novel deep network to address these challenges comprehensively. We first present a dual-path feature extraction module (DP-FEM) to extract rich features via a channel attention mechanism. A high- and low-level feature fusion module (HL-FFM) is devised based on spatial attention, which selectively fuses rich semantic information from high-level features with spatial cues from low-level features. In addition, a hybrid loss is designed to deal with pixel-level misalignment and boundary ambiguities. Based on the segmentation results, we derive key clinical parameters for diagnosis and treatment planning. We extensively evaluate the proposed method on 4,485 two-dimensional (2D) paediatric echocardiograms from 127 echocardiographic videos. The proposed method consistently achieves better segmentation performance than other state-of-the-art methods, whichdemonstratesfeasibility for automatic segmentation and quantitative analysis of paediatric echocardiography. Our code is publicly available at https://github.com/end-of-the-century/Cardiac.

Scaling laws of electroconvective flow with finite vortex height near permselective membranes.

In a steady state, the linear scaling laws are confirmed between the intensity characteristics of electroconvective (EC) vortex (including the vortex height and electroosmotic slip velocity) and the applied voltage for the nonshear EC flow with finite vortex height near permselective membranes. This finding in the nonshear EC flow is different from the shear EC flow [Kwak et al., Phys. Rev. Lett. 110, 114501 (2013)10.1103/PhysRevLett.110.114501] and indicates that the local concentration gradient has a significant improvement in the analysis of slip velocity. Further, our study reveals that the EC vortex is mainly driven by the second peak effect of the Coulomb thrust in the extended space-charge layer, and the linear scaling law exhibited by the Coulomb thrust is an essential reason for the linear scaling laws of vortex intensity. The scaling laws proposed in this paper are supported by our direct numerical simulation data and previous experimental observations [Rubinstein et al., Phys. Rev. Lett. 101, 236101 (2008)10.1103/PhysRevLett.101.236101].

Shear electroconvective instability in electrodialysis channel under extreme depletion and its scaling laws.

The electroconvective instability (ECI) in an electrodialysis channel under a strong electric field is studied here. The phenomenon of ECI with extreme depletion (ECI-HD) is reported; that is, the overlapping vortices cause the extreme depletion zone to propagate in the horizontal direction. Using scaling theory and direct numerical simulation, we indicate a series of features under the ECI-HD. The decrease in ion transport rate with voltage in ECI-HD is different from the enhancement in the ECI with moderate depletion (ECI-MD), which results in a unique peak in the voltage-current curve. More importantly, we reveal that the ECI is regulated by a scaling factor consisting of the electric field, hydrodynamic coupling coefficient, and Péclet number. For the ECI-HD, the scaling factor has an opposite effect on the vortex size and overlimiting current as that on the ECI-MD. The extreme depletion zone of the ECI-HD also has an uncommon diffusion self-similar dynamics. These unique scaling laws allow one to establish the quantitative bridge between the ion concentration, electric field, and vortex size by the overlimiting current.

Stress Concentration and Damage Factor Due to Central Elliptical Hole in Functionally Graded Panels Subjected to Uniform Tensile Traction.

Functionally graded material (FGM) can optimize the mechanical properties of composites by designing the spatial variation of material properties. In this paper, the stress distribution of functionally graded panel with a central elliptical hole under uniaxial tensile load is analyzed. Based on the inhomogeneity variation and three different gradient directions, the effects of the inhomogeneity on the stress concentration factor and damage factor are discussed. The study results show that when Young's modulus increases with the distance from the hole, the stress concentration factor decreases compared with that of homogeneous material, and the optimal design of r-FGM is better than that of x-FGM and y-FGM when the tensile load. In addition, when the associated variation of ultimate stress is considered, the choice of scheme to reduce the failure index is related to the strength-modulus exponent ratio. When the strength-modulus exponent ratio is small, the failure index changes with the index of power-law, which means there is an optimal FGM design. But when the strength-modulus exponent ratio is large, the optimal design modulus design is to select a uniform material that maximizes the modulus at each point. These research results have a certain reference value for further in-depth understanding of the inhomogeneous design for FGM.

Length-dependent dual-mechanism-controlled failure modes in silver penta-twinned nanowires.

A series of molecular dynamics simulations on silver penta-twinned nanowires are performed to reveal the tensile failure mechanisms that are responsible for the different failure modes and morphologies of fracture surfaces observed in various experimental reports. The simulations show that a ductile-to-brittle transition in failure mode occurs with increasing length of the nanowires. Short nanowires have ductile-like plasticity with flat-like fracture surfaces, while long nanowires show brittle-like fractures with cone-like failure surfaces. These two seemingly counterintuitive scenarios can be attributed to two sets of mechanisms: (1) stable dislocation nucleation-controlled incipient plasticity followed by stable dislocation motion-mediated plasticity assisted by pores for short nanowires, (2) unstable dislocation nucleation-controlled incipient plasticity followed by rapid necking for long nanowires. These two sets of failure mechanisms are distinguished by fitted lines using phased strain data. We propose a general strategy to build a necking-based model for predicting the critical nanowire aspect ratio while distinguishing the fracture modes. A mechanism map of silver penta-twinned nanowire is constructed to delineate the predominant failure behaviours. Our findings reveal a correlation between the failure mode and the resulting morphology of the fracture surface and provide a paradigm for the design and engineering of mechanical properties of nanowires.