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The exceptional combination of strength and ductility in multi-component alloys is often attributed to the interaction of dislocations with the various solute atoms in the alloy. To study these effects on the mechanical properties of such…

Materials Science · Physics 2021-09-16 Markus Sudmanns , Jaafar A. El-Awady

Due to the vast compositional space of multi-principal element alloys (MPEAs), the rational design of MPEAs for optimized microstructures is difficult. Therefore, a high-throughput first-principles study of Mo-V-Nb-Ti-Zr, a refractory MPEA,…

Materials Science · Physics 2021-05-25 Zhidong Leong , Upadrasta Ramamurty , Teck Leong Tan

Diffusion models may be viewed as hierarchical variational autoencoders (VAEs) with two improvements: parameter sharing for the conditional distributions in the generative process and efficient computation of the loss as independent terms…

Machine Learning · Computer Science 2025-10-20 Beatrix M. G. Nielsen , Anders Christensen , Andrea Dittadi , Ole Winther

Understanding energy transport in semiconductors is critical for design of electronic and optoelectronic devices. Semiconductor material properties such as charge carrier mobility or diffusion length are commonly measured in bulk crystals…

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations…

We present an explicit method for simulating stochastic differential equations (SDEs) that have variable diffusion coefficients and satisfy the detailed balance condition with respect to a known equilibrium density. In Tupper and Yang…

Numerical Analysis · Mathematics 2014-06-27 Paul Tupper , Xin Yang

Diffusion in ternary, multiphase systems was studied theoretically and experimentally in Ni-Cr-Al system at 1200C. The samples were prepared by the multiple method. It has been shown that the method allows obtaining good quality, planar,…

Materials Science · Physics 2018-05-08 Marek Zajsuz

In alloys cluster expansions (CE) are increasingly used to combine first-principles electronic-structure and Monte Carlo methods to predict thermodynamic properties. As a basis-set expansion in terms of lattice geometrical clusters and…

Materials Science · Physics 2017-11-28 Nikolai A. Zarkevich , D. D. Johnson

We investigate a method for extracting nonlinear principal components (NPCs). These NPCs maximize variation subject to smoothness and orthogonality constraints; but we allow for a general class of constraints and multivariate probability…

Methodology · Statistics 2009-08-06 Xioahong Chen , Lars Peter Hansen , Jose Scheinkman

We expand on a recent study of a lattice model of interacting particles [Phys. Rev. Lett. 111, 110601 (2013)]. The adsorption isotherm and equilibrium fluctuations in particle number are discussed as a function of the interaction. Their…

Statistical Mechanics · Physics 2014-11-20 T. Becker , K. Nelissen , B. Cleuren , B. Partoens , C. Van den Broeck

A simple manner to describe the diffusive relaxation of a colloidal fluid adsorbed in a porous medium is to model the porous medium as a set of spherical particles fixed in space at random positions with prescribed statistical structural…

Conventional approaches for simulating steady-state distributions of particles under diffusive and advective transport at high P\'eclet numbers involve solving the diffusion and advection equations in at least two dimensions. Here, we…

The ability to predict the behavior of a wireless channel in terms of the frame delivery ratio is quite valuable, and permits, e.g., to optimize the operating parameters of a wireless network at runtime, or to proactively react to the…

Networking and Internet Architecture · Computer Science 2023-12-14 Gabriele Formis , Stefano Scanzio , Gianluca Cena , Adriano Valenzano

Cluster expansions are commonly employed as surrogate models to link the electronic structure of an alloy to its finite-temperature properties. Using cluster expansions to model materials with several alloying elements is challenging due to…

Materials Science · Physics 2025-01-31 Yann L. Müller , Anirudh Raju Natarajan

The accumulation and growth of vacancy clusters under irradiation is a pivotal degradation mode for structural materials in extreme environments. Even tungsten undergoes rapid defect coarsening compromising its integrity. Here we show a…

Refractory multi-principal element alloys (MPEAs) have exceptional mechanical properties, including high strength-to-weight ratio and fracture toughness, at high temperatures. Here, we elucidate the complex interplay between segregation,…

Materials Science · Physics 2020-05-18 Xiang-Guo Li , Chi Chen , Hui Zheng , Yunxing Zuo , Shyue Ping Ong

The mixture extension of exponential family principal component analysis (EPCA) was designed to encode much more structural information about data distribution than the traditional EPCA does. For example, due to the linearity of EPCA's…

Machine Learning · Computer Science 2020-04-08 Maoying Qiao , Tongliang Liu , Jun Yu , Wei Bian , Dacheng Tao

Recent efforts on Diffusion Mixture-of-Experts (MoE) models have primarily focused on developing more sophisticated routing mechanisms. However, we observe that the underlying architectural configuration space remains markedly…

Machine Learning · Computer Science 2025-12-02 Yahui Liu , Yang Yue , Jingyuan Zhang , Chenxi Sun , Yang Zhou , Wencong Zeng , Ruiming Tang , Guorui Zhou

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez

Disruption-generated runaway electrons (RE) present an outstanding issue for ITER. The predictive computational studies of RE generation rely on orbit-averaged computations and, as such, they lack the effects from the magnetic field…

Plasma Physics · Physics 2017-01-19 Konsta Särkimäki , Eero Hirvijoki , Joan Decker , Jari Varje , Taina Kurki-Suonio