Results 71 to 80 of about 3,464,601 (248)

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
wiley   +1 more source

Eigenstate Thermalization Hypothesis with projective representation

Journal of High Energy Physics
The Eigenstate Thermalization Hypothesis (ETH) provides a sufficient condition for thermalization of isolated quantum systems. While the standard ETH is formulated in the absence of degeneracy, physical systems often possess symmetries that induce ...
Soma Onoda, Osamu Fukushima, Ryusuke Hamazaki, Okuto Morikawa   +3 more
doaj   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

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, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Nonequilibrium Statistical Mechanics (Stationary): Overview

, 2006
Review on nonequilibrium statistical ...
GALLAVOTTI, Giovanni, G. Gallavotti
core   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

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, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

Entropy, Closures and Subgrid Modeling

Entropy, 2008
Maximum entropy states or statistical mechanical equilibrium solutions have played an important role in the development of a fundamental understanding of turbulence and its role in geophysical flows. In modern general circulation models of the earth’
Terence J. O’Kane, Jorgen S. Frederiksen   +1 more
doaj   +1 more source

Derivation In A Nonequilibrium Ensemble Formalism Of A Far-reaching Generalization Of A Quantum Boltzmann Theory

, 2015
Within the framework of the nonequilibrium statistical ensemble formalism provided by the nonequilibrium statistical operator method, we derive a quantum Boltzmann-style transport theory of a broad scope.
Vasconcellos A.R., Luzzi R., Galvao Ramos J.   +2 more
core   +1 more source

Probing Machine Learning Interatomic Potentials on Ion Transport Properties

Advanced Intelligent Discovery, EarlyView.
We perform a systematic benchmark of six state‐of‐the‐art universal machine learning interatomic potentials on their ability to predict ion transport properties in lithium‐ and sodium‐based superionic conductors relevant to all‐solid‐state batteries.
Ogheneyoma Aghoghovbia, Ming Hu, Adji Bousso Dieng   +2 more
wiley   +1 more source

N.N. Bogoliubov's contribution to nonequilibrium statistical mechanics (1937-1945)

, 2020
It is shown that many important and still relevant results in the field of nonequilibrium statistical mechanics were derived by Bogoliubov (jointly with N. M. Krylov) early in the prewar years and were completely published in a still insufficiently known
Rudoy Y.G.
core   +2 more sources

Classical and Quantum Models in Non-Equilibrium Statistical Mechanics: Moment Methods and Long-Time Approximations

Entropy, 2012
We consider non-equilibrium open statistical systems, subject to potentials and to external “heat baths” (hb) at thermal equilibrium at temperature T (either with ab initio dissipation or without it).
Ramon F. Alvarez-Estrada
doaj   +1 more source