Dynamics of supercooled liquids from static averaged quantities using machine learning
We introduce a machine-learning approach to predict the complex non-Markovian dynamics of supercooled liquids from static averaged quantities. Compared to techniques based on particle propensity, our method is built upon a theoretical framework that uses as input and output system-averaged quantitie...
Main Authors: | Simone Ciarella, Massimiliano Chiappini, Emanuele Boattini, Marjolein Dijkstra, Liesbeth M C Janssen |
---|---|
Format: | Article |
Language: | English |
Published: |
IOP Publishing
2023-01-01
|
Series: | Machine Learning: Science and Technology |
Subjects: | |
Online Access: | https://doi.org/10.1088/2632-2153/acc7e1 |
Similar Items
-
Role of attractive forces in the relaxation dynamics of supercooled liquids
by: Chattoraj, Joyjit, et al.
Published: (2020) -
An Ising Model for Supercooled Liquids and the Glass Transition
by: Ralph V. Chamberlin
Published: (2022-10-01) -
Structural glasses and supercooled liquids : theory, experiment, and applications /
by: Wolynes, P. G. (Peter G.) 548586, et al.
Published: ([201) -
Long-Range Static and Dynamic Previtreous Effects in Supercooled Squalene—Impact of Strong Electric Field
by: Szymon Starzonek, et al.
Published: (2021-09-01) -
The dynamic properties of supercooled liquids/
by: 278084 Harrison, Gilroy
Published: (1976)