Entropy in Particle Systems

Dear Colleagues,

Many natural materials and industrial products are made of individual particles that traverse a wide range of length scales, from nanometers to centimeters or larger. The bulk behaviour (i.e., the state) of any complex particle system is a collective representation of the motion of individual particles and their interactions, which is determined by the mechanical and surface properties of individual particles (such as shape, size, elasticity, plasticity, friction and surface energy). Information theory and the concept of entropy were first introduced to describe the state of particle system in 1990s. With the advances in measurement and numerical techniques, such as the discrete element method (DEM), significant progress has been made in understanding the complex behaviour of particle systems at various length scales. These advancements not only enable scientists to explore the link between microscopic and macroscopic behaviours but also provide vast information on particle systems for detailed examination of the transient complex nature of particle systems in many natural and industrial processes. Building upon these advancements, information theory and statistical mechanics form a unique framework to describe the state of these complex systems. It is also argued that the mesoscale attributes of particle systems, such as domain interaction, coherence length scale and transition clusters, govern their transient behaviour, which has attracted increasing attention. 

This Special Issue aims to collect state-of-the-art research on the application of information theory, statistical mechanics, as well as multiscale experimentation and modelling in analysing complex behaviours of particle systems, such as self-organisation, segregation and networks. Theoretical, experimental and numerical contributions dealing with entropy analysis, entropy generation, entropy production and entropy induced re-organisation/segregation in particle systems of various length scales fall within the scope of this Special Issue. Applications of information theory (such as Shannon entropy), machine learning and systems theory (such as artificial intelligence, neural networks) in analysing particle systems are also welcome.

Prof. Dr. Charley Chuan-yu Wu
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• particle systems
• statistical mechanics
• entropy production
• entropy-induced segregation
• granular temperature
• mesoscale modelling
• machine learning