Special Issue "Nonequilibrium Thermodynamics and Stochastic Processes"
Deadline for manuscript submissions: 20 March 2022.
Interests: nonequilibrium thermodynamics; statistical physics; energy conversion physics and technology; energy systems; thermoelectricity; condensed matter physics; quantum physics; physical chemistry; biophysics
As it did for classical thermodynamics, a phenomenological approach drove the development of nonequilibrium thermodynamics, at the heart of which lie the local equilibrium assumption and the minimum entropy production hypothesis. Linear response theory, which specializes in close-to-equilibrium problems, constitutes an important milestone as it provides deep insights into the actual physical processes at work and their rates during the evolution of natural and artificial systems. Extending the scope of nonequilibrium thermodynamics to systems far from equilibrium still is an open challenge. Development of stochastic thermodynamics is a decisive progress as it provides a framework where key classical thermodynamic concepts, heat, work and entropy, find a definition at the level of individual trajectories pertinent notably to small-scale, far from equilibrium systems. Quantum thermodynamics constitutes also an active front of research: open quantum dynamics, coherence and dissipation at the quantum level can contribute to the fundamental base upon which equilibrium and nonequilibrium thermodynamics would rest, and from which the first and second laws would naturally emerge. Last, but perhaps not least, machine learning may also reveal itself as a powerful tool to gain unprecedented insight into the nonequilibrium properties of any complex system, both close and far from equilibrium, and undergoing phase transitions.
This Special Issue aims to gather articles which will cover a wide range of systems and problems pertaining to nonequilibrium and stochastic thermodynamics and will provide a unifying vision of the field underpinned by entropy and information theory. It is anticipated that contributions will essentially contain theoretical developments, but submission of manuscripts reporting basic experimental results analyzed in the frame of theories pertinent to the Special Issue, as well as those discussing emerging technologies derived from nonequilibrium and stochastic thermodynamics are particularly welcome.
Prof. Dr. Henni Ouerdane
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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 1800 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.
- Energy conversion, including thermoelectric, electrochemical, chemical reactions, etc.
- Classical and quantum dissipative systems
- Mesoscopic systems
- Stochastic thermodynamics: MEMS, molecular motors, colloids, biomolecules
- Non-Markovian dynamics
- Fluctuation theorems
- Open quantum systems
- Quantum thermodynamics
- Machine learning methods