Universal enhancement of vacancy diffusion by Mn inducing anomalous Friedel oscillation in concentrated solid-solution alloys

We present a proof-of-principle demonstration of a universal law for the element Mn, which greatly enhances vacancy diffusion through an anomalous Friedel Oscillation effect in a series of Ni-based concentrated solid-solution alloys, regardless of the type of atom involved. The antiferromagnetic element Mn possesses a unique half-filled 3d electron structure, creating split virtual bound states near the Fermi energy level and producing a large local magnetic moment after vacancy formation. The resultant electron spin oscillations reduce the number of electrons involved in charge density oscillations, destroying charge screening and lowering potential interaction at the saddle point between the vacancy and diffusing atom. This ultimately facilitates vacancy diffusion by reducing energy level variations of conduction band electrons during the diffusion process. These findings offer valuable insights into atom diffusion mechanisms and open up new avenues for manipulating defect properties through unique element design, thereby enabling the creation of high-performance alloys in a broad range of fields

Leveraging SOLOv2 model to detect heat stress of poultry in complex environments

Heat stress is one of the most important environmental stressors facing poultry production. The presence of heat stress will reduce the antioxidant capacity and immunity of poultry, thereby seriously affecting the health and performance of poultry. The paper proposes an improved FPN-DenseNet-SOLO model for poultry heat stress state detection. The model uses Efficient Channel Attention (ECA) and DropBlock regularization to optimize the DenseNet-169 network to enhance the extraction of poultry heat stress features and suppress the extraction of invalid background features. The model takes the SOLOv2 model as the main frame, and uses the optimized DenseNet-169 as the backbone network to integrate the Feature Pyramid Network to detect and segment instances on the semantic branch and mask branch. In the validation phase, the performance of FPN-DenseNet-SOLO was tested with a test set consisting of 12,740 images of poultry heat stress and normal state, and it was compared with commonly used object detection models (Mask R CNN, Faster RCNN and SOLOv2 model). The results showed that when the DenseNet-169 network lacked the ECA module and the DropBlock regularization module, the original model recognition accuracy was 0.884; when the ECA module was introduced, the model's recognition accuracy improved to 0.919. Not only that, the recall, AP0.5, AP0.75 and mean average precision of the FPN-DenseNet-SOLO model on the test set were all higher than other networks. The recall is 0.954, which is 15, 8.8, and 4.2% higher than the recall of Mask R CNN, Faster R CNN and SOLOv2, respectively. Therefore, the study can achieve accurate segmentation of poultry under normal and heat stress conditions, and provide technical support for the precise breeding of poultry

A Review of Solid-Solution Models of High-Entropy Alloys Based on Ab Initio Calculations

Similar to the importance of XRD in experiments, ab initio calculations, as a powerful tool, have been applied to predict the new potential materials and investigate the intrinsic properties of materials in theory. As a typical solid-solution material, the large degree of uncertainty of high-entropy alloys (HEAs) results in the difficulty of ab initio calculations application to HEAs. The present review focuses on the available ab initio based solid-solution models (virtual lattice approximation, coherent potential approximation, special quasirandom structure, similar local atomic environment, maximum-entropy method, and hybrid Monte Carlo/molecular dynamics) and their applications and limits in single phase HEAs

Ab initio atomistic simulation of metals and multicomponent alloys

Ab initio theory provides a powerful tool to understand and predict the behavior of materials. This thesis contains both of these aspects. First we use ab initio alloy theory to investigate a new kind of complex alloy (high-entropy alloy). Second we introduce a novel potential (interlayer potential), which can be extracted from ab inito total energy calculations using the Chen-Möbius inversion method. High-entropy alloys (HEAs) are composed of four or more metallic elements with nearly equimolar composition. In spite of the large number of components, most of the HEAs have a simple solid-solution phase rather than forming complex intermetallic structures. Extensive experiments have reported the unique microstructures and special properties of HEAs. Single-phase HEAs may be divided into three types, i.e. the 3d-HEAs adopting the face centered cubic (fcc) phase, the refractory-HEAs with a body centered cubic (bcc) phase, and the HEAs with the duplex fcc-bcc structure. We employ the exact muffin-tin orbitals (EMTO) method in combination with the coherent potential approximation (CPA) to investigate the electronic structure, the equilibrium volume and the elastic properties of these three-type HEAs. First we compare the CPA with the super cell technique (SC) to assess the performance of the EMTO-CPA method. As typical fcc 3d-HEAs, we consider the CuNiCoFeCrTix systems in the paramagnetic state. Starting from the calculated electronic structure, we give an explanation for the observed magnetic states. Furthermore, we provide a theoretical prediction for the elastic parameters and polycrystalline elastic moduli for CuNiCoFeCrTix (x= 0.0−0.5, 1.0) and NiCoTeCrTi. A detailed comparison between the theoretical results and the available experimental data demonstrates that ab initio theory can properly describe the fundamental properties of this important class of engineering alloys. Refractory-HEAs are composed of Ti, Zr, Hf, V, Nb, Ta, Mo, and W. These HEAs have a simple bcc structure. Taking the TiZrNbMoVx and TiZrVNb HEAs as examples, we provide a detailed investigation of the effect of alloying elements on the elastic parameters and the elastic isotropy. Our results indicate that vanadium enhances the anisotropy and ductility of TiZrNbMoVx. As an application of the present theoretical database, we verify the often quoted correlation between the valence charge concentration (VEC) and the micro-mechanical properties in the case of multi-component alloys. Furthermore, we predict that the present HEAs become elastically isotropic for VEC ≃ 4.72. With increase of the aluminum content, phase transformations (fcc→(fcc+bcc)→bcc) occur in NiCoFeCrAlx HEAs. Our ab initio results predict that at room temperature the paramagnetic NiCoFeCrAlx HEAs adopt the fcc structure for x ≤ 0.60 and the bcc structure for x ≥ 1.23, with an fcc-bcc duplex region in between the two pure phases. The calculated single- and polycrystal elastic parameters exhibit strong composition and crystal structure dependence. Based on the present theoretical findings, it is concluded that alloys around the equimolar NiCoFeCrAl composition have superior mechanical performance as compared to the single-phase regions. Many modern materials and material systems are layered. The properties related to layers are connected to interactions between atomic layers. We introduce the interlayer potential (ILP), a novel model potential which fully describes the interaction between layers. The ILPs are different from the usual interatomic potentials which present inter- action between atoms. We use the Chen-Möbius inversion method to extract the ILPs from ab initio total energy calculations. The so obtained ILPs can be employed to investigate several physical parameters connected with the particular set of atomic layers, e.g. surface energy, stacking fault energy, elastic parameters, etc. As an application, we adopt the supercell method and the axial interaction model in connection with the ILPs to calculate the stacking fault energy along the fcc ⟨111⟩ direction, including the intrinsic stacking fault energy, extrinsic stacking fault energy and twin stacking fault energy as well as the interactions between the intrinsic stacking faults. We find that the data derived from ILPs are consistent with those obtained in direct ab initio calculations. Along the fcc ⟨111⟩ direction, we study the surface energy and surface relaxation using the ILPs. The phonon dispersions are also described. Our conclusions are as follows the EMTO-CPAab initioalloy theory can be used to understand and predict the fundamental properties of multicomponent alloys. the interlayer potentials based on the Chen-Möbius inversion method may provide a new way to investigate the properties related to layers in layered materials, the EMTO-CPA alloy theory combined with the Chen-Möbius inversion method offers a powerful technique to study the properties of complex alloys.QC 20131108</p

Ab initio Interlayer Potentials For Metals and Alloys

Many modern materials and material systems are layered. The properties related to layers are connected to interactions between atomic layers. In the present thesis, we introduce the interlayer potential (ILP), a novel model potential which fully describes the interaction between layers. The ILPs are different from the usual interatomic potentials which present interaction between atoms. We use the Chen-Möbius inversion method to extract the ILPs from ab initio total energy calculations. The so obtained ILPs can be employed to investigate several physical parameters connected with the particular set of atomic layers, e.g. surface energy, stacking fault energy, elastic parameters, etc. The interactions between the face centered cubic (fcc) (111) planes are described by two different ILPs. Using two close-packed model structures, namely the ABC stacking along the fcc ⟨111⟩ direction and AB stacking along the hcp ⟨0001⟩ direction, we demonstrate how these two ILPs are obtained via the Chen-Möbius method. Density function theory (DFT) is employed to generate the ILPs and also to compute the equilibrium structural properties of elemental metals Al, Ni, Cu, Ag, Au and Pd as well as of Pd-Ag random solid solutions. With the so established ILPs, we adopt the supercell method and the axial interaction model to calculate the stacking fault energy along the fcc ⟨111⟩ direction, including the intrinsic stacking fault energy, extrinsic stacking fault energy and twin stacking fault energy as well as the interactions between the intrinsic stacking faults. We find that the data derived from ILPs are consistent with those obtained in direct ab initio calculations. Along the fcc ⟨111⟩ direction, we study the surface energy and surface relaxation using the ILPs. The phonon dispersions are also described. We conclude that the interlayer potentials based on the Chen-M¨obius inversion technique may provide a new way to investigate the properties related to layers in layered materials.QC 20121101</p

Research on Navigation Path Extraction and Obstacle Avoidance Strategy for Pusher Robot in Dairy Farm

Existing push robots mainly use magnetic induction technology. These devices are susceptible to external electromagnetic interference and have a low degree of intelligence. To make up for the insufficiency of the existing material pushing robots, and at the same time solve the problems of labor-intensive, labor-intensive, and inability to push material in time at night, etc., in this study, an autonomous navigation pusher robot based on 3D lidar is designed, and an obstacle avoidance strategy based on the improved artificial potential field method is proposed. Firstly, the 3D point cloud data of the barn is collected by the self-designed pushing robot, the point cloud data of the area of interest is extracted using a direct-pass filtering algorithm, and the 3D point cloud of the barn is segmented using a height threshold. Secondly, the Least-Squares Method (LSM) and Random Sample Consensus (RANSAC) were used to extract fence lines, and then the boundary contour features were extracted by projection onto the ground. Finally, a target influence factor is added to the repulsive potential field function to determine the principle of optimal selection of the parameters of the improved artificial potential field method and the repulsive direction, and to clarify the optimal obstacle avoidance strategy for the pusher robot. It can verify the obstacle avoidance effect of the improved algorithm. The experimental results showed that under three different environments: no noise, Gaussian noise, and artificial noise, the fence lines were extracted using RANSAC. Taking the change in the slope as an indicator, the obtained results were about &minus;0.058, 0.058, and &minus;0.061, respectively. The slope obtained by the RANSAC method has less variation compared to the no-noise group. Compared with LSM, the extraction results did not change significantly, indicating that RANSAC has a certain resistance to various noises, but RANSAC performs better in extraction effect and real-time performance. The simulation and actual test results show that the improved artificial potential field method can select reasonable parameters and repulsive force directions. The optimized path increases the shortest distance of the obstacle point cloud from the navigation path from 0.18 to 0.41 m, where the average time is 0.059 s, and the standard deviation is 0.007 s. This shows that the optimization method can optimize the path in real time to avoid obstacles, basically meet the requirements of security and real-time performance, and effectively avoid the local minimum problem. This research will provide corresponding technical references for pusher robots to overcome the problems existing in the process of autonomous navigation and pushing operation in complex open scenarios

Ab Initio Predicted Alloying Effects on the Elastic Properties of AlxHf1−xNbTaTiZr High Entropy Alloys

Using ab initio alloy theory, we investigate the equilibrium bulk properties and elastic mechanics of the single bcc solid-solution AlxHf1−xNbTaTiZr (x = 0–0.7, 1.0) high entropy alloys. Ab initio predicted equilibrium volume is consistent with the available experiment. We make a detailed investigation of the alloying effect of Al and Hf on the equilibrium volume, elastic constants and polycrystalline elastic moduli. Results imply that the partial replacement Hf with Al increases the stability of the bcc phase and decreases the ductility of the AlxHf1−xNbTaTiZr HEAs. The inner ductility of Al0.4Hf0.6NbTaTiZr is predicted by the calculations of ideal tensile strength

Local Lattice Distortion in High-Entropy Carbide Ceramics

Using the ab initio calculations, we study the lattice distortion of HfNbTaTiVC5, HfNbTaTiZrC5 and MoNbTaTiVC5 high-entropy carbide (HEC) ceramics. Results indicate that the Bader atomic radius and charge transfer in HECs is very close to those from binary carbide. The degree of lattice distortion strongly depends on the alloying element. The Bader atomic radius can excellently describe the lattice distortion in HEC. Further, the corresponding atomic radius and formation enthalpy of binary carbides may be indicators to predict the single-phase HECs

Ab initio-predicted micro-mechanical performance of refractory high-entropy alloys

Recently developed high-entropy alloys (HEAs) consisting of multiple principal elements represent a new field of metallurgy and have demonstrated appealing properties for a wide range of applications. Using ab initio alloy theory, we reveal the alloying effect on the elastic properties and the ideal tensile strength (ITS) in the [001] direction of four body-centered cubic (bcc) refractory HEAs based on Zr, V, Ti, Nb, and Hf. We find that these HEAs show high elastic anisotropy and large positive Cauchy pressure, suggesting good extrinsic ductility. Starting from ZrNbHf, it is found that the ITS decreases with equimolar Ti addition. On the other hand, if both Ti and V are added to ZrNbHf, the ITS is enhanced by about 42%. An even more captivating effect is the ITS increase by about 170%, if Ti and V are substituted for Hf. The alloying effect on the ITS is explained by the d-band filling. An intrinsic brittle-to-ductile transition is found in terms of the failure mode under uniaxial tension. These investigations suggest that intrinsically ductile HEAs with high ideal strength can be achieved by controlling the proportion of group four elements to group five elements.Funding: Hungarian Scientific Research Fund OTKA 84078 109570, National Natural Science Foundation of China (NSFC) 51401014, fundamental research funds for the Central Universities FRF-TP-14-029A1, National 973 Project of China 2011CB606401 </p

Tests on the Accuracy and Scalability of the Full-Potential DFT Method Based on Multiple Scattering Theory

We investigate a reduced scaling full-potential DFT method based on the multiple scattering theory (MST) code MuST, which is released online (https://github.com/mstsuite/MuST) very recently. First, we test the accuracy by calculating structural properties of typical body-centered cubic (BCC) metals (V, Nb, and Mo). It is shown that the calculated lattice parameters, bulk moduli, and elastic constants agree with those obtained from the VASP, WIEN2k, EMTO, and Elk codes. Second, we test the locally self-consistent multiple scattering (LSMS) mode, which achieves reduced scaling by neglecting the multiple scattering processes beyond a cut-off radius. In the case of Nb, the accuracy of 0.5 mRy/atom can be achieved with a cut-off radius of 20 Bohr, even when small deformations are imposed on the lattice. Despite that the calculation of valence states based on MST exhibits linear scaling, the whole computational procedure has an overall scaling of about O(N-1.6), due to the fact that the updating of Coulomb potential scales almost as O(N-2). Nevertheless, it can be still expected that MuST would provide a reliable and accessible way to large-scale first-principles simulations of metals and alloys