2022 Impact factor 2.8
Special Topics

Open Calls for Papers

EPJ ST Special Issue: Biomimetic and Cellular Membranes

Guest Editor: Tripta Bhatia

Cells are confined and compartmentalized by membranes that are typically composed of hundreds of different types of lipids. Although the concept of synthetic membrane processes was introduced several years ago, recent studies have revealed new developments and exciting results with studies of biomimetic models that are used as reference systems for the cell. Structural complexity has been shown to build up in model membrane systems based on fundamental physical principles that could potentially validate the relationship between membrane phase, pattern formation, protein activity, and phase transition. Understanding the coupling between physical properties and functions opens rational methods for manipulating cellular function and dysfunction. Studies in synthetic and cell biology have generated insight into the nature of cell assembly from molecular building blocks. Hence, this issue of EPJ ST in the area of biomimetic and cellular membranes is devoted to the current state of the art in the field and an outlook on the soft matter of life to point out the directions for further studies.

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EPJ ST Special Issue: Routes to Synchronization and Collective Behavior in Higher-Order Networks

Guest Editors: Sajad Jafari, Fatemeh Parastesh, Eckehard Schӧll

Real networks are composed of many interconnected dynamical systems. Network science has provided efficient tools and platforms for studying these networks. However, recent developments have shown that classical networks are not beneficial enough for investigating complex dynamics and behaviors in special cases. It has been revealed that the links are not limited to connecting two nodes but more nodes. Therefore, the interactions can go beyond pairwise connections, constructing group interactions or higher-order interactions whose introduction to the network helps to reach further developments. The higher-order interactions have been found in diverse fields, including neurology, social science, and ecology, and significantly influence their emergent behaviors. Consequently, the study of higher-order interactions has recently been the focus of many scientists.

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EPJ ST Special Issue: b-quark physics as a precision laboratory: status and future prospects

Guest Editors: Rusa Mandal (lead editor), B. Ananthanarayan, Daniel Wyler

The proposed collection of articles is to bring together in-depth discussions of the current status of b-quark physics as well as of the prospects for the future.

The mass of the b-quark and its small decay rate have made it eminently suitable for studying the strong and the weak interactions. On one hand, the mass is high enough to allow reliable perturbative calculations of the strong interaction, due to the onset of asymptotic freedom, to have led to successful effective theories (HQET, SCET) and also to allow decays with a large number of final states. On the other hand, it is low enough to have led to the further development of various methods to handle the strong interactions at low energies, such as aspects of chiral perturbation theory or lattice methods. The small rate, due to the CKM suppression factors, makes it ideal for studies of the weak interactions, in particular the rare decays and CP violating effects. Most importantly, this has led to a solid basis for understanding CP violation, and the entire CKM mixing matrix. Before the advent of the higher energies available at LHC, B-physics indeed dominated phenomenological activities in particle physics. Today, there is intensive work at the LHCb-detector, at CERN, and at the Belle-II-detector, Tsukuba Japan.

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EPJ ST Special Issue: Machine Learning in Quantum Many Body and Physical Systems

Editors: Roberta Citro and Silvia Scarpetta

This special topic will cover different aspects of machine learning for the description of quantum many-body and physics systems, from both solid state, statistical mechanics and computer science. Recently many successfull applications of machine learning has given novel insights in several domains in physics.

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Managing Editors
Anne Ruimy and Vijala Kiruvanayagam (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Dear Sabine, Sandrine, and Nicolas, your professional and efficient management supported our editing tasks enormously and made the whole process smooth and pleasant. The web-based SAGA system was very helpful for handling the workflow. Thank you all for your high commitment!

Jan Freund, ICBM, University of Oldenburg, Germany

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

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