Entropy: From Atoms to Complex Systems
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Statistical Physics".
Deadline for manuscript submissions: 15 September 2025 | Viewed by 1293
Special Issue Editor
Special Issue Information
Dear Colleagues,
Entropy has proven to be central to understanding the multiple and fascinating behaviors exhibited by systems at equilibrium and out of equilibrium. Several definitions of entropy have been developed, using thermodynamics, statistical physics, and information theory to quantify the degree of order/disorder or randomness of the systems. Moreover, with frameworks such as the fluctuation theorems, we can detect and quantify how far a system is from equilibrium. Entropy production offers a measure of irreversibility but also quantifies dissipation and, thus, efficiency. These developments are particularly important in emergent fields such as self-organization, with the formation of structured forms (crystals, colloidal assemblies, and topological active matter), but also to better understand molecular machines (from proteins to artificial molecular factories). Practically, in the past two decades or so, we have seen a huge increase in computational methods that aim to estimate entropy and entropy production based on Monte Carlo and/or molecular dynamics simulations. Additionally, the use of AI and machine learning techniques has not only sped up calculation but has also helped to design new entropy-based measures, allowing for a deeper characterization of physical systems while also shedding light on the fundamental role of entropy.
Dr. Caroline Desgranges
Guest Editor
Manuscript Submission Information
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Keywords
- entropy
- entropy production
- machine learning
- Monte Carlo
- molecular dynamics
- fluctuation theorems
- thermodynamics
- statistical physics
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