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Copper precipitation is a technique extensively deployed in steel strengthening. Being as tiny as a few nanometers in diameter, the Cu precipitates present a real challenge to experimental techniques in determination of their composition. The late Professor Morris Fine called it a mystery when addressing the discrepancy between the fact of low solubility of Fe in bulk Cu and the remarkable content of Fe in Cu precipitates according to atom probe tomography measurement. With a thorough search using rigorous first-principles density functional theory calculations, we are surprised to find that the interface between Cu precipitate and Fe matrix is neither immiscibly sharp, nor commonly miscible over a range of atomic layers, but rather manifests itself as a single-layer mixed Fe-Cu interphase. Our detailed analysis reveals that spin polarization is a key factor in defining such an interphase. The magnetic Friedel oscillations through spin polarization is the driving force to stabilize it. When the single-layer Fe-Cu interphase is counted in, the content of Fe in Cu precipitates would be significant due to their small size. Our finding is a strong demonstration that quantum mechanical effects such as Friedel oscillations can have explicit consequence also in structural materials. The accurate knowledge of the Fe-Cu interface is crucial for the design of advanced high-strength steels., Comment: 17 pages, 11 figures

A stronger interlayer magnetic coupling (ILMC) can open up new opportunities in spintronics devices for Fe$_5$GeTe$_2$ (F5GT), a demonstrated two-dimensional (2D) van der Waals (vdW) material with high Currie temperature. Here we observe an extraordinary ILMC spike in F5GT, jumping from 1.15 to 12.79 meV/f.u, by applying a 3% in-plane strain. This spike is mainly ascribed to a significant increase in the magnetic moment of the Fe5 ion. Moreover, the applied in-plane strain can also significantly enhance the magnetic anisotropy energy (MAE) of the system, triggering the transition between the in/off-plane configurations in multi-layer F5GT., Comment: 25 pages, 9 figures

To overcome current serious energy and environmental issues, photocatalytic water splitting holds great promise because it requires only solar energy as an energy input to produce hydrogen. Two-dimensional (2D) semiconductors and heterostructures possess several inherent advantages which are more suitable for boosting solar energy than their bulk counterparts. In this work, by performing high-throughput first-principles calculations combined with a semiempirical van der Waals dispersion correction, we first provided the periodic table of band alignment type for van der Waals heterostructures when packing any two of the 260 semiconductor monolayers obtained from our 2D semiconductor database (2DSdb) (https://materialsdb.cn/2dsdb/index.html). Based on the rules of thumb for photocatalytic water splitting, we have further screened dozens of potential semiconductors and thousands of heterostructures which are promising for photocatalytic water splitting. The resulting database would provide a useful guidance for experimentalists to design suitable 2D vdWHs and photocatalysts according to desired applications., Comment: 7 pages, 4 figures

In this paper, we create a single-use and full syntax zero-knowledge proof system, a.k.a zk-Fabric. Comparing with zk-SNARKS and another variant zero-knowledge proofing system, zkBOO and it's variant zkBOO++. We present multiple new approaches on how to use partitioned garbled circuits to achieve a joint zero-knowledge proof system, with the benefits of less overhead and full syntax verification. zk-Fabric based on partitioned garbled circuits has the advantage of being versatile and single-use, meaning it can be applied to arbitrary circuits with more comprehensive statements, and it can achieve the non-interactivity among all participants. One of the protocols proposed within is used for creating a new kind of partitioned garbled circuits to match the comprehensive Boolean logical expression with multiple variables, we use the term "polythitic syntax" to refer to the context-based multiple variables in a comprehensive statement. We also designed a joint zero knowledge proof protocol that uses partitioned garbled circuits, Comment: 6 pages, 5 figures

We present the VASPKIT, a command-line program that aims at providing a powerful and user-friendly interface to perform high-throughput analysis of a variety of material properties from the raw data produced by the VASP code. It consists of mainly the pre- and post-processing modules. The former module is designed to prepare and manipulate input files such as the necessary input files generation, symmetry analysis, supercell transformation, k-path generation for a given crystal structure. The latter module is designed to extract and analyze the raw data about elastic mechanics, electronic structure, charge density, electrostatic potential, linear optical coefficients, wave function plots in real space, and etc. This program can run conveniently in either interactive user interface or command line mode. The command-line options allow the user to perform high-throughput calculations together with bash scripts. This article gives an overview of the program structure and presents illustrative examples for some of its usages. The program can run on Linux, MacOS, and Windows platforms. The executable versions of VASPKIT and the related examples, together with the tutorials, are available in its official website vaspkit.com., Comment: 33 pages, 19 figures

By performing high-throughput first-principles calculations combined with a semiempirical van der Waals dispersion correction, we have screened 74 direct- and 185 indirect-gap two dimensional (2D) nonmagnetic semiconductors from near 1000 monolayers according to the criteria for energetic, thermodynamic, mechanical, dynamic and thermal stabilities, and conductivity type. We present the calculated lattice constants, simulated scanning tunnel microscopy, formation energy, Young's modulus, Poisson's ratio, shear modulus, anisotropic effective mass, band structure, band gap, ionization energy, and electron affinity for each candidate meeting our criteria. The resulting 2D semiconductor database (2DSdb) can be accessed via the website https://materialsdb.cn/2dsdb/index.html. The 2DSdb provides an ideal platform for computational modeling and design of new 2D semiconductors and heterostructures in photocatalysis, nanoscale devices, and other applications. Further, a linear fitting model was proposed to evaluate band gap, ionization energy and electron affinity of semiconductor from the density functional theory (DFT) calculated data as initial input. This model can be as precise as hybrid DFT but with much lower computational cost., Comment: 16 pages, 18 figures

The massive scale of future wireless networks will create computational bottlenecks in performance optimization. In this paper, we study the problem of connecting mobile traffic to Cloud RAN (C-RAN) stations. To balance station load, we steer the traffic by designing device association rules. The baseline association rule connects each device to the station with the strongest signal, which does not account for interference or traffic hot spots, and leads to load imbalances and performance deterioration. Instead, we can formulate an optimization problem to decide centrally the best association rule at each time instance. However, in practice this optimization has such high dimensions, that even linear programming solvers fail to solve. To address the challenge of massive connectivity, we propose an approach based on the theory of optimal transport, which studies the economical transfer of probability between two distributions. Our proposed methodology can further inspire scalable algorithms for massive optimization problems in wireless networks., Comment: 6 pages, 5 figures

In this work we detail a novel open source library, called MMLSpark, that combines the flexible deep learning library Cognitive Toolkit, with the distributed computing framework Apache Spark. To achieve this, we have contributed Java Language bindings to the Cognitive Toolkit, and added several new components to the Spark ecosystem. In addition, we also integrate the popular image processing library OpenCV with Spark, and present a tool for the automated generation of PySpark wrappers from any SparkML estimator and use this tool to expose all work to the PySpark ecosystem. Finally, we provide a large library of tools for working and developing within the Spark ecosystem. We apply this work to the automated classification of Snow Leopards from camera trap images, and provide an end to end solution for the non-profit conservation organization, the Snow Leopard Trust.

Hydrogen atoms absorbed by metals in the hydrogen-containing environments can lead to the premature fracture of the metal components used in load-bearing conditions. Since metals used in practice are mostly polycrystalline, grain boundaries (GBs) can play an important role in hydrogen embrittlement of metals. Here we show that the reaction of GB with lattice dislocations is a key component in hydrogen embrittlement mechanism for polycrystalline metals. We use atomistic modeling methods to investigate the mechanical response of GBs in alpha-iron with various hydrogen concentrations. Analysis indicates that dislocations impingement and emission on the GB cause the GB to locally transform into an activated state with a more disordered atomistic structure, and introduce a local stress concentration. The activation of the GB segregated with hydrogen atoms can greatly facilitate decohesion of the GB. We show that the hydrogen embrittlement model proposed here can give better explanation of many experimental observations.