109 Result(s)
within
**ang-**g Wang
Materials Science
Computational Intelligence
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Article
Open AccessUnraveling dislocation-based strengthening in refractory multi-principal element alloys
Refractory multi-principal element alloys (RMPEAs) draw great interest with their superior mechanical properties and extremely high melting points, yet the strengthening mechanism remains unclear. Here, we cal...
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Open AccessAutomated design of hybrid halide perovskite monolayers for band gap engineering
The recent experimental confirmation of perovskite monolayers has sparked ongoing efforts in their prediction and synthesis, showcasing their flexible tunable band gap and potential in advanced functional devi...
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Open AccessRealization of 2D multiferroic with strong magnetoelectric coupling by intercalation: a first-principles high-throughput prediction
The discovery of novel two-dimensional (2D) multiferroic materials is attractive due to their potential for the realization of information storage and logic devices. Although many approaches have been explored...
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Open AccessProbabilistic physics-integrated neural differentiable modeling for isothermal chemical vapor infiltration process
Chemical vapor infiltration (CVI) is a widely adopted manufacturing technique used in producing carbon-carbon and carbon-silicon carbide composites. These materials are especially valued in the aerospace and a...
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Open AccessThe cage effect of electron beam irradiation damage in cryo-electron microscopy
Electron beam irradiation can cause damage to biological and organic samples, as determined via transmission electron microscopy (TEM). Cryo-electron microscopy (cryo-EM) significantly reduces such damage by q...
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Open AccessData-driven optimization and machine learning analysis of compatible molecules for halide perovskite material
Optoelectronic stability of halide perovskite material in hostile conditions such as water is rather limited, preventing them from further industrial deployment. Here, we optimize and perform machine learning ...
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Open AccessPretraining of attention-based deep learning potential model for molecular simulation
Machine learning-assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a mo...
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Open AccessOptical second harmonic generation in anisotropic multilayers with complete multireflection of linear and nonlinear waves using ♯SHAARP.ml package
Optical second harmonic generation (SHG) is a nonlinear optical effect widely used for nonlinear optical microscopy and laser frequency conversion. Closed-form analytical solution of the nonlinear optical resp...
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Open AccessMLMD: a programming-free AI platform to predict and design materials
Accelerating the discovery of advanced materials is crucial for modern industries, aerospace, biomedicine, and energy. Nevertheless, only a small fraction of materials are currently under experimental investig...
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Open AccessStoner instability-mediated large magnetoelectric effects in 2D stacking electrides
Strong magnetoelectric effects in single-phase two-dimensional (2D) materials are extremely rare in nature. Here by first-principles calculations, we find a strong magnetoelectric coupling in polar stacking bi...
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Open AccessExploitable magnetic anisotropy and half-metallicity controls in multiferroic van der Waals heterostructure
Two-dimensional (2D) XY ferromagnets have drawn pronounced interest in recent years, but the characteristic of easy-plane magnetization restricts their application in spintronics to some extent. Here, we propo...
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Open AccessCoherent and semicoherent α/β interfaces in titanium: structure, thermodynamics, migration
The α/β interface is central to the microstructure and mechanical properties of titanium alloys. We investigate the structure, thermodynamics and migration of the coherent and semicoherent Ti α/β interfaces as a ...
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Open AccessFull-scale ab initio simulations of laser-driven atomistic dynamics
The coupling of excited states and ionic dynamics is the basic and challenging point for the materials response at extreme conditions. In the laboratory, the intense laser produces transient nature and complex...
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Open AccessSymmetry-driven half-integer conductance quantization in Cobalt–fulvalene sandwich nanowire
Precise manipulation and monitoring spin transport in one-dimensional (1D) systems is a long-sought goal in the field of nano-spintronics. Based on first-principles calculations, we report the observation of h...
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Open AccessMachine learning assisted derivation of minimal low-energy models for metallic magnets
We consider the problem of extracting a low-energy spin Hamiltonian from a triangular Kondo Lattice Model (KLM). The non-analytic dependence of the effective spin-spin interactions on the Kondo exchange exclud...
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Open AccessHigh-throughput deformation potential and electrical transport calculations
The deformation potential plays an important role in electrical transport properties, but in the context of high-throughput searches requires a consistent and readily computable reference level. Here, we desig...
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Open AccessAlloy synthesis and processing by semi-supervised text mining
Alloy synthesis and processing determine the design of alloys with desired microstructure and properties. However, using data science to identify optimal synthesis-design routes from a specified set of startin...
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Open AccessLocal symmetry distortion induced anomalous thermal conduction in thermoelectric layered oxyselenides
Polyhedral distortion, associated closely with the atomic arrangement and interatomic interactions, drives many unique behaviors in solids, such as phase transition and negative thermal expansion. In thermoele...
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Open AccessPredicting the synthesizability of crystalline inorganic materials from the data of known material compositions
Reliably identifying synthesizable inorganic crystalline materials is an unsolved challenge required for realizing autonomous materials discovery. In this work, we develop a deep learning synthesizability model (
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Open AccessMultiscale simulations of growth-dominated Sb2Te phase-change material for non-volatile photonic applications
Chalcogenide phase-change materials (PCMs) are widely applied in electronic and photonic applications, such as non-volatile memory and neuro-inspired computing. Doped Sb2Te alloys are now gaining increasing atten...
