Self-patterning Gd nano-fibers in Mg-Gd alloys

Manipulating the shape and distribution of strengthening units, e.g. particles, fibers, and precipitates, in a bulk metal, has been a widely applied strategy of tailoring their mechanical properties. Here, we report self-assembled patterns of Gd nano-fibers in Mg-Gd alloys for the purpose of improving their strength and deformability. 1-nm Gd nano-fibers, with a 〈c〉-rod shape, are formed and hexagonally patterned in association with Gd segregations along dislocations that nucleated during hot extrusion. Such Gd-fiber patterns are able to regulate the relative activities of slips and twinning, as a result, overcome the inherent limitations in strength and ductility of Mg alloys. This nano-fiber patterning approach could be an effective method to engineer hexagonal metals

A Slice Escape Detection Model Based on Full Flow Adaptive Detection

The 5G power trading private network increases network flexibility and lowers building costs with the aid of 5G and Access Point Name (APN) technology. However, the private network is facing a series of security problems, such as the lack of effective isolation between slices and malicious terminal damage in slices, which result in a large consumption of slice resource failures and even slice escape attacks. To solve this problem, we propose a slice escape detection model based on full flow adaptive detection. Firstly, we improve the "six-tuple" flow table features detection technology, and creatively proposed a set of "eleven-tuple" features scheme, so as to realize the adaptive detection of intra-slice and inter-slice escape attacks. Secondly, we construct a two-level detection model based on long short-term memory network and self-attention mechanism to improve detection efficiency and reduce false alarm rate. Thirdly, we design an exception handling module to handle the abnormally detected traffic. Our model has a high detection accuracy and a low false alarm rate for the slice escape assault, according to a large number of experiments on the CIC-DDoS2019 dataset, and the detection delay complies with the requirements for online detection

Atomically informed nonlocal semidiscrete variational Peierls-Nabarro model for planar core dislocations

Prediction of Peierls stress associated with dislocation glide is of fundamental concern in understanding and designing the plasticity and mechanical properties of crystalline materials. Here, we develop a nonlocal semi-discrete variational Peierls-Nabarro (SVPN) model by incorporating the nonlocal atomic interactions into the semi-discrete variational Peierls framework. The nonlocal kernel is simplified by limiting the nonlocal atomic interaction in the nearest neighbor region, and the nonlocal coefficient is directly computed from the dislocation core structure. Our model is capable of accurately predicting the displacement profile, and the Peierls stress, of planar-extended core dislocations in face-centered cubic structures. Our model could be extended to study more complicated planar-extended core dislocations, such as \u3c110\u3e {111} dislocations in Al-based and Ti-based intermetallic compounds

Mesoscale Mechanisms in Viscoplastic Deformation of Metals and Their Applications to Constitutive Models

Deformation of metals has attracted great interest for a long time. However, the constitutive models for viscoplastic deformation at high strain rates are still under intensive development, and more physical mechanisms are expected to be involved. In this work, we employ the newly-proposed methodology of mesoscience to identify the mechanisms governing the mesoscale complexity of collective dislocations, and then apply them to improving constitutive models. Through analyzing the competing effects of various processes on the mesoscale behavior, we have recognized two competing mechanisms governing the mesoscale complex behavior of dislocations, i.e., maximization of the rate of plastic work, and minimization of the elastic energy. Relevant understandings have also been discussed. Extremal expressions have been proposed for these two mesoscale mechanisms, respectively, and a stability condition for mesoscale structures has been established through a recently-proposed mathematical technique, considering the compromise between the two competing mechanisms. Such a stability condition, as an additional constraint, has been employed subsequently to close a two-phase model mimicking the practical dislocation cells, and thus to take into account the heterogeneous distributions of dislocations. This scheme has been exemplified in three increasingly complicated constitutive models, and improves the agreements of their results with experimental ones

Mechanism of Modified Ether Amine Agents in Petalite and Quartz Flotation Systems under Weak Alkaline Conditions

To investigate the flotation separation behavior of petalite and quartz, various methods were employed in this study. These included micro-flotation experiments, a contact angle analysis, zeta potential analysis, Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS) to explore the separation mechanism of a modified ether amine reagent (L0-503) for petalite and quartz under weakly alkaline conditions. The micro-flotation test results indicated that the modified ether amine collector had a higher collecting ability for quartz than for petalite, with a maximum recovery rate of 93.2% for quartz and a recovery rate consistently below 14% for petalite in the presence of L0-503. This indicates that the modified ether amine reagent can be used as a reverse flotation agent for separating petalite and quartz. The separation mechanism results showed that the modified ether amine reagent had a significantly higher adsorption capacity for quartz than for petalite due to a strong reaction between the quartz and the secondary amine (-NH=) on the modified ether amine collector. Additionally, the electrostatic force and hydrogen bonding between the reagent and quartz further enhanced the adsorption, while no reaction occurred between the reagent and petalite

Multiscale investigation of shear relaxation in shock loading: A top-down perspective

Shear relaxation commonly occurs in shock compressed metals at the plastic wave front, but no consensus has ever been reached on its origin due to the multiscale nature of high rate plasticity. To this end, this work takes a top-down approach by conducting a theoretical and numerical investigation on the macroscale, and then simulations on the mesoscale with crystal plasticity, followed by a brief discussion on the microscale mechanisms based on dislocation theory. On the macroscale, theoretical derivation through isotropic elasticity and von-Mises plasticity, as well as continuum simulations of shocked aluminum employing Johnson-Cook plasticity and equations of state for nonlinear elasticity at high pressures, uncovers that strain rate hardening decisively leads to shear relaxation when the equivalent plastic strain rate is greater than two-thirds of the total strain rate (ε̇p>2/3∙ε̇1). Other factors play subsidiary roles, including limited or conditioned promotive effect of thermal softening and suppressive effect of strain hardening. On the mesoscale, simulations with crystal plasticity and hyperelasticity perfectly verify the macroscopic discoveries, and additionally revealed the subordinate stimulative effect of deformation heterogeneity of polycrystals. On the microscale, dislocation nucleation and multiplication are identified as the dominant factors by evaluating contributions of micro-mechanisms to strain rate hardening

SLC31A1 Identifying a Novel Biomarker with Potential Prognostic and Immunotherapeutic Potential in Pan-Cancer

Solute carrier family 31 member 1 (SLC31A1) encodes a protein that functions as a homotrimer for the uptake of dietary copper. As a vital member of the cuproptosis gene family, it plays an essential role in both normal tissues and tumors. In this study, we analyzed SLC31A1 across human cancer types to gain a better understanding of SLC31A1’s role in cancer development. We searched for information using online databases to analyze, systematically and comprehensively, the role of SLC31A1 in tumors. Amongst nine cancer types, the expression of SLC31A1 was significantly different between tumors and normal tissues. According to further analysis, pancreatic cancer had the highest mutation rate of the SLC31A1 gene, and the methylation levels of the gene were significantly reduced in seven tumors. The expression of SLC31A1 is also linked to the infiltration of tumors by immune cells, the expression of immune checkpoint genes, and immunotherapy markers (TMB and MSI), suggesting that SLC31A1 may be of particular relevance in immunotherapy. This thorough analysis of SLC31A1 across different types of cancer gives us a clear and comprehensive insight into its role in causing cancer on a systemic level

On Optimal Imaging Angles in Multi-Angle Ocean Sun Glitter Remote-Sensing Platforms to Observe Sea Surface Roughness

Sea surface roughness (SSR) is a key physical parameter in studies of air–sea interactions and the ocean dynamics process. The SSR quantitative inversion model based on multi-angle sun glitter (SG) images has been proposed recently, which will significantly promote SSR observations through multi-angle remote-sensing platforms. However, due to the sensitivity of the sensor view angle (SVA) to SG, it is necessary to determine the optimal imaging angle and their combinations. In this study, considering the design optimization of imaging geometry for multi-angle remote-sensing platforms, we have developed an error transfer simulation model based on the multi-angle SG remote-sensing radiation transmission and SSR estimation models. We simulate SSR estimation errors at different imaging geometry combinations to evaluate the optimal observation geometry combination. The results show that increased SSR inversion accuracy can be obtained with SVA combinations of 0° and 20° for nadir- and backward-looking SVA compared with current combinations of 0° and 27.6°. We found that SSR inversion prediction error using the proposed model and actual SSR inversion error from field buoy data are correlated. These results can provide support for the design optimization of imaging geometry for multi-angle ocean remote-sensing platforms