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This work is concerned with numerically recovering multiple parameters simultaneously in the subdiffusion model from one single lateral measurement on a part of the boundary, while in an incompletely known medium. We prove that the boundary…

Numerical Analysis · Mathematics 2023-07-10 Siyu Cen , Bangti Jin , Yikan Liu , Zhi Zhou

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

The diffusion of elements is a key process in understanding the unusual surface composition of white dwarfs stars and their spectral evolution. The diffusion coefficients of Paquette et al. (1986) have been widely used to model diffusion in…

Solar and Stellar Astrophysics · Physics 2020-06-17 R. A. Heinonen , D. Saumon , J. Daligault , C. E. Starrett , S. D. Baalrud , G. Fontaine

Compositionally complex alloys or concentrated solid solutions are the latest frontier in catalyst design, but mixing different elements in one catalyst may result in surface segregation. Atomistic simulations can predict segregation…

Materials Science · Physics 2022-12-12 Alberto Ferrari , Vadim Sotskov , Alexander V. Shapeev , Fritz Körmann

Model analogies and exchange of ideas between physics or chemistry with biology or epidemiology have often involved inter-sectoral mapping of techniques. Material mechanics has benefitted hugely from such interpolations from mathematical…

Biological Physics · Physics 2022-06-06 Amit K Chattopadhyay , Bidisha Kundu , Sujit Kumar Nath , Elias C Aifantis

A non-equilibrium thermodynamics model able to analyze the combined effect of diffusion and adsorption in porous materials is proposed. The model considers the coupled dynamics of the diffusive phase, described by a diffusion type equation,…

Materials Science · Physics 2015-06-04 I. Santamaria-Holek , Z. J. Grzywna , J. M. Rubi

Diffusion models are learning pattern-learning systems to model and sample from data distributions with three functional components namely the forward process, the reverse process, and the sampling process. The components of diffusion…

Machine Learning · Computer Science 2025-06-02 Ziyi Chang , George Alex Koulieris , Hyung Jin Chang , Hubert P. H. Shum

We present the detailed analysis of the diffusive transport of spatially inhomogeneous fluid mixtures and the interplay between structural and dynamical properties varying on the atomic scale. The present treatment is based on different…

Mesoscale and Nanoscale Physics · Physics 2011-05-19 Umberto Marini Bettolo Marconi , Simone Melchionna

Particle diffusion in rotating drums is studied via computer simulations using a full 3-D model which does not involve any arbitrary input parameters. The diffusion coefficient for single-component systems agree qualitatively with previous…

Condensed Matter · Physics 2009-10-28 G. A. Kohring

Understanding the role of solute diffusivities in equilibrium tie-line selection during growth of a second phase in ternary and higher multicomponent two phase alloys is an important problem due to the strong dependence of mechanical…

Materials Science · Physics 2016-03-31 Arka Lahiri , T. A. Abinandanan , Abhik Choudhury , M. S. Bhaskar

Microalloying elements tend to segregate to the matrix-precipitate phase boundaries to reduce the interfacial energy. The segregation mechanism is emerging as a novel design strategy for developing precipitation-hardened alloys with…

Materials Science · Physics 2022-01-11 Sourabh Bhagwan Kadambi , Srikanth Patala

The microscopic model of atomic diffusion is considered to describe the short-range order relaxation kinetics within the f.c.c.-Ni-Fe Permalloys. The model takes into account both the discrete and anisotropic characters of atomic jumps…

Materials Science · Physics 2023-06-09 T. M. Radchenko , V. A. Tatarenko , S. M. Bokoch

The Invar effect in ferromagnetic Fe-Ni, Fe-Pt, and Fe-Pd alloys is investigated theoretically by means of a computationally efficient scheme. The procedure can be divided into two stages: study of magnetism and calculations of structural…

Materials Science · Physics 2012-08-15 F. Liot , C. A. Hooley

Diffusion of atoms in solids is one of the most fundamental kinetic processes that ultimately governs many materials properties. Here, we report on a combined first-principles and kinetic Monte Carlo study of macroscopic diffusion…

Materials Science · Physics 2021-05-25 Tanmoy Chakraborty , Jutta Rogal

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…

Accurately estimating friction coefficients between arbitrary material pairs is critical for robotics, digital fabrication, and physics-based simulation, but exhaustive pairwise testing scales quadratically with the number of materials. We…

Robotics · Computer Science 2026-04-28 Zhendong Wang , Huamin Wang

Diffusion models have demonstrated powerful performance in generating high-quality images. A typical example is text-to-image generator like Stable Diffusion. However, their widespread use also poses potential privacy risks. A key concern…

Computer Vision and Pattern Recognition · Computer Science 2026-04-20 Guo Li , Weihong Chen , Yongfu Fan

The kinetics of coherent Cu rich precipitation in Fe-Cu and Fe-Cu-Ni alloys during thermal ageing have been modeled by Atomic Kinetic Monte Carlo method (AKMC). The AKMC is parameterized by existing ab-inito data to treat vacancy mediated…

Materials Science · Physics 2013-01-16 Yi Wang , Huai Yu Hou , Xiang Bing Liu , Rong Shan Wang , Jing Tao Wang

We study the diffusion process in binary mixtures using transition probabilities that depend on a mean-field potential. This approach reproduces the Darken equation, a relationship between the intrinsic and the tracer diffusion…

Statistical Mechanics · Physics 2019-08-21 Marisel Di Pietro Martínez , Miguel Hoyuelos

Diffusion models have gained attention for their ability to represent complex distributions and incorporate uncertainty, making them ideal for robust predictions in the presence of noisy or incomplete data. In this study, we develop and…

Machine Learning · Computer Science 2024-11-05 Yilin Zhuang , Sibo Cheng , Karthik Duraisamy