Results 71 to 80 of about 32,558 (228)
Nonequilibrium molecular dynamics
Condensed Matter Physics, 2005 Nonequilibrium Molecular Dynamics is a powerful simulation tool. Like its equilibrium cousin, nonequilibrium molecular dynamics is based on time-reversible equations of motion. But unlike conventional mechanics, nonequilibrium molecular dynamics provides
Wm.G.Hoover, C.G.Hoover
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Jarzynski equality for the transitions between nonequilibrium steady states
, 1999 Jarzynski equality [Phys. Rev. E {\bf 56}, 5018 (1997)] is found to be valid with slight modefication for the transitions between nonequilibrium stationary states, as well as the one between equilibrium states. Also numerical results confirm its validity.
C. Jarzynski +11 more
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A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics [PDF]
, 2015 A central problem in machine learning involves modeling complex data-sets using highly flexible families of probability distributions in which learning, sampling, inference, and evaluation are still analytically or computationally tractable.
Ganguli, Surya +3 more
core
, 2009 A complete mathematical theory of nonequilibrium thermodynamics of stochastic systems in terms of master equations is presented. As generalizations of isothermal entropy and free energy, two functions of states play central roles: the Gibbs entropy $S ...
A. I. Khinchin +12 more
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Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
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NONEQUILIBRIUM THERMODYNAMICS: A POWER FUL TOOL FOR SCIENTISTS AND ENGINEERS
Dyna, 2012 We present the two-generator framework of nonequilibrium thermodynamics with a strong emphasis on fundamental notions rather than mathematical details.
HANS CHRISTIAN ÖTTINGER
doaj
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
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Nonequilibrium Thermodynamics – A Tool for Applied Rheologists
Applied Rheology, 1999 GENERIC is reviewed not only as a new general framework for modeling nonequilibrium systems, but also as a new way of thinking about nonequilibrium dynamics.
Öttinger Hans Christian
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Advanced Intelligent Discovery, EarlyView.This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath +4 more
wiley +1 more source