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In this paper we introduce and discuss kinetic equations for the evolution of the probability distribution of the number of particles in a population subject to binary interactions. The microscopic binary law of interaction is assumed to be…

Probability · Mathematics 2015-01-13 Federico Bassetti , Giuseppe Toscani

Aqueous foams are subject to coarsening, whereby gas from the bubbles diffuses through the liquid phase. Gas is preferentially transported from small to large bubbles, resulting in a gradual decrease of the number of bubbles and an increase…

Soft Condensed Matter · Physics 2026-02-19 Jacob Morgan , Simon Cox

When particles/molecules diffuse in systems that contain obstacles, the steady-state regime (during which the mean-square displacement scales linearly with time, $\left< r^2 \right> \sim t$) is preceded by a transient regime. It is common…

Biological Physics · Physics 2021-08-12 Nicholas Ilow , Gary W. Slater

Stagnation of grain growth is often attributed to impurity segregation. Yttria-stabilized cubic zirconia does not evidence any segregation-induced slowdown, as its grain growth obeys the parabolic law when the grain size increases by more…

Materials Science · Physics 2020-05-18 Yanhao Dong , I-Wei Chen

Grain growth in nanocrystalline Al was studied by means of molecular dynamics simulations. The novelty of this study results from the utilization of an algorithm to resolve per-grain kinetics and orientation change from molecular dynamics…

Materials Science · Physics 2016-12-30 Paul W. Hoffrogge , Luis A. Barrales-Mora

The established microalgae growth models are semi-empirical or considerable fitting coefficients exist currently. Therefore, the ability of the model prediction is reduced by the numerous fitting coefficients. Furthermore, the predicted…

Biological Physics · Physics 2022-05-12 C. Y. Ma

We present a general approach to study a class of random growth models in $n$-dimensional Euclidean space. These models are designed to capture basic growth features which are expected to manifest at the mesoscopic level for several…

Probability · Mathematics 2020-08-20 Amir Dembo , Pablo Groisman , Ruojun Huang , Vladas Sidoravicius

A continuum grain boundary model is developed that uses experimentally measured grain boundary energy data as a function of misorientation to simulate idealized grain boundary evolution in a 1-D grain array. The model uses a continuum…

Materials Science · Physics 2024-01-29 Syed Ansari , Amit Acharya , Alankar Alankar

Many-body stochastic processes with weighted multiplicative interactions are investigated analytically and numerically. An interaction rate between particles with quantities $x, y$ is controlled by a homogeneous symmetric kernel $K(x, y)…

Statistical Mechanics · Physics 2007-05-23 Akihiro Fujihara , Satoshi Tanimoto , Toshiya Ohtsuki , Hiroshi Yamamoto

Abnormal grain growth in the presence of second phase particles is investigated with the help of a two-dimensional Monte Carlo simulation. An aggregate of equiaxed grains is considered with constant grain boundary energy and mobility. The…

Materials Science · Physics 2007-05-23 Rene Messina , Michele Soucail , Ladislas Kubin

Discrete and continuous models belonging to a universality class share the same linearities and (or) nonlinearities. In this work, we propose a new approach to calculate coarse grained coefficients of the continuous differential equation…

Statistical Mechanics · Physics 2012-11-22 R. C. Buceta , D. Hansmann

We developed a grain growth model that is based on the energy minimisation of surfaces with respect to the volume energy and the grain's environment. We used the well-known FePt L1$_\text{0}$ system to discover the physical factors that…

Materials Science · Physics 2022-09-14 Connor Skelland , Gino Hrkac

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. C. C. Coolen , A. De Martino , A. Annibale

In order to study analytically the nature of the size segregation in granular mixtures, we introduce a mean field theory in the framework of a statistical mechanics approach, based on Edwards' original ideas. For simplicity we apply the…

Statistical Mechanics · Physics 2009-11-11 M. Tarzia , A. Fierro , M. Nicodemi , M. Pica Ciamarra , A. Coniglio

We explore a systematic approach to studying the dynamics of evolving networks at a coarse-grained, system level. We emphasize the importance of finding good observables (network properties) in terms of which coarse grained models can be…

The topological transitions that occur to the grain boundary network during grain growth in a material with uniform grain boundary energies are believed to be known. The same is not true for more realistic materials, since more general…

Materials Science · Physics 2021-10-29 Erdem Eren , Jeremy K. Mason

The phenomenon of stochastic growth of a surface on a two-dimensional substrate occurs in Nature in a variety of circumstances and its statistical characterization requires the study of higher order cumulants. Here, we consider the…

Statistical Mechanics · Physics 2016-11-23 Tapas Singha , Malay K. Nandy

We consider generalizations of the Kardar--Parisi--Zhang equation that accomodate spatial anisotropies and the coupled evolution of several fields, and focus on their symmetries and non-perturbative properties. In particular, we derive…

Statistical Mechanics · Physics 2009-11-10 Rava A. da Silveira , Mehran Kardar

We show that the growth rate of dust grains in cold molecular clouds is enhanced by the high degree of compressibility of a turbulent, dilute gas. By means of high resolution (10243) numerical simulations, we confirm the theory that the…

Astrophysics of Galaxies · Physics 2020-11-18 Xiang-Yu Li , Lars Mattsson

In machine learning, the scaling law describes how the model performance improves with the model and data size scaling up. From a learning theory perspective, this class of results establishes upper and lower generalization bounds for a…

Machine Learning · Computer Science 2025-02-14 Shihong Ding , Haihan Zhang , Hanzhen Zhao , Cong Fang