EPJ B Highlight - Testing particle scattering and reflection in graphene

Band structures for the left and right ferromagnetic regions. Credit: W. Yan., et al., EPJ B (2023)

Testing the quantum effects of Andreev reflection in the wonder material could have positive implications for quantum technology

Humanity stands on the verge of two major revolutions: the boom in 2-dimensional supermaterials like graphene with incredible properties and the introduction of quantum computers with processing power that vastly outstrips standard computers.

Understanding materials like graphene, made of single sheets of atoms, means better investigations of the properties they display at an atomic level. This includes how electrons behave around superconductors — materials that, when cooled to temperatures near absolute zero, can conduct electricity without energy loss.

When a superconductor is sandwiched between metal materials, a type of scattering called crossed Andreev reflection may appear, and in an s-wave superconductor junction, the Andreev reflection usually induces correlated opposite spin in electrons. This can be used to induce entanglement, a quantum phenomenon that is critical for quantum computers.

In a new paper in EPJ B, author Rui Shen, from the National Laboratory of Solid State Microstructures and School of Physics at Nanjing University, China, and his co-authors theoretically assess nonlocal transport and crossed Andreev reflection in a ferromagnetic s-wave superconductor junction composed of the gapped graphene lattices.


EPJ E Highlight – How hydrophobicity shapes protein assemblies

Hydrophobic dipoles align in parallel. Credit: Angel Mozo-Villarías et al. 2023

Using an electrical analogy, researchers show how a distribution of hydrophobic charges draws proteins into parallel alignment in a macromolecule assembly

Through a nuanced balance of electrical and hydrophobic forces, biological molecules self-assemble into the large functional structures that maintain life’s vital functions. Understanding how proteins self-assemble requires knowledge of both forces. But while predicting the electrical interactions of individual proteins is simple, deriving their hydrophobic ones is less straightforward. In a study published in EPJ E, Angel Mozo-Villarias, of the Autonomous University of Barcelona, Spain, and his colleagues develop a formulation for how proteins align into membrane-like structures based on hydrophobic interactions. The model could help to predict the configuration of macromolecular assemblies at any scale, providing a useful tool for novel materials and drug discovery research.


EPJ D Highlight - Machine learning hunts for the right mix of hydrogen isotopes for future nuclear fusion power plants

The Sun, where nuclear fusion of hydrogen proceeds in a dense plasma. New research uses machine learning to look for the right mix of hydrogen isotopes for technology that replicates this process on Earth. Credit: ESA/NASA/SOHO

New research is an initial step in the use of deep learning to help determine the right mix of hydrogen isotopes to use in fusion power plants of the future

The process that powers the stars, nuclear fusion, is proposed as a future power source for humanity and could provide clean and renewable energy free of the radioactive waste associated with current nuclear fission plants.

Just like the fusion process that sends energy spilling out from the Sun, future nuclear fusion facilities will slam together isotopes of the universe’s lightest element, hydrogen, in an ultra-hot gas or “plasma” contained by a powerful magnetic field to create helium with the difference in mass harvested as energy.

One thing that scientists must know before the true advent of fusion power here on Earth is what mix of hydrogen isotopes  to use— primarily “standard” hydrogen, with one proton in its atomic nucleus, deuterium with one proton and one neutron in its nucleus, and tritium with a nucleus of one proton and two neutrons. This is currently done with spectroscopy for prototype fusion devices called tokamaks, but this analysis can be time-consuming.

In a new paper in EPJ D, author Mohammed Koubiti, Associate Professor at the Aix-Marseille Universite, France, assesses the use of machine learning in connection with plasma spectroscopy to determine the ratios of hydrogen isotopes for nuclear fusion plasma performance.


EPJ Plus Focus Point Issue: Focus Point on Environmental and Multiplicity Effects on Planet Formation

Guest Editors: Giuseppe Lodato and Carlo Felice Manara

Star formation does not take place in isolation, and young stars are subject to different kind of interactions with their natal environment. Dynamical encounters with other young stars and photoevaporation of the protostellar disc due to the intense UV field of neighbouring stars are just a couple of examples of how the environment affects star formation. Since planets are born during the star formation process, such effects may naturally affect also planet formation itself. The aim of this focus point is to define the state of the art of our knowledge in this particular field and to provide a few highlights of interesting new research avenues to pursue.

All articles are available here and are freely accessible until 24 October 2023. For further information, read the Editorial.

EPJ D Topical Issue: Electron-Driven Processes from Single Collisions to High-Pressure Plasmas

Guest Editors: Jose L. Lopez, Michael Brunger, and Holger Kersten

The special Topical Issue of the European Physics Journal D (EPJ D) on “Electron-Driven Processes from Single Collisions to High-Pressure Plasmas” is published to honor Kurt H. Becker, who served as Editor-in-Chief for the journal from 2010 to 2016, on his 70th birthday. Electron-driven processes from single collisions to high-pressure plasmas definitely occupy a central position in atomic and plasma physics. Considering this, the Guest Editors compilated a broad range of original manuscripts that encompass the area of electron-atom and electron-molecular collisions, respectively, low-temperature plasma research and aligning with Kurt Becker’s emphasis on science innovation and entrepreneurship. Hence, the papers focus on various recent scientific and technological advances in this given area of physics, chemistry and technology of non-thermal plasmas.


EPJ B Colloquium - Density-matrix renormalization group: a pedagogical introduction

Schematic representation of the connection between the original and the tensor-network-based formulations of the density-matrix renormalization group method

The physical properties of a quantum many-body system can, in principle, be determined by diagonalizing the respective Hamiltonian, but the dimensions of its matrix representation scale exponentially with the number of degrees of freedom. Hence, only small systems that are described through simple models can be tackled via exact diagonalization. To overcome this limitation, numerical methods based on the renormalization group paradigm have been put forth, that restrict the quantum many-body problem to a manageable subspace of the exponentially large full Hilbert space. A striking example is the density-matrix renormalization group (DMRG), which has become the reference numerical method to obtain the low-energy properties of one-dimensional quantum systems with short-range interactions.


EPJ ST Highlight - Capturing the evolution of complex quantum systems

Representing the HEOM mathematical structure

Through a new survey, researchers show how mathematical representations named ‘tensor trains’ can help to capture and simulate the dynamics of evolving quantum systems across a range of different scenarios.

Many quantum systems are heavily influenced by their surrounding environments, making them incredibly challenging to describe theoretically. To capture the dynamics and evolution of these systems, researchers often use mathematical representations named ‘tensor trains’. Through new research published in EPJ ST, a team of researchers from four different institutions in France show how tensor trains can be implemented to describe and simulate quantum systems.


EPJPV Highlight - How cool is floating PV

Example of effect of wind on two panels

The Editors-in-Chief of EPJ Photovoltaics, Pere Roca i Cabarrocas and Jean-Louis Lazzari, are pleased to highlight an important paper published recently in the Special Issue on ‘WCPEC-8: State of the Art and Developments in Photovoltaics’.

The article “How cool is floating PV? A state-of-the-art review of floating PV's potential gain and computational fluid dynamics modeling to find its root cause” is the result of the joint efforts of Gofran Chowdhury (imec, EnergyVille and University of Leuven), Mohamed Haggag (imec and University of Leuven), and Jef Poortmans (imec, EnergyVille, University of Hasselt and University of Leuven).


EPJ B Highlight - How a transparent conductor responds to strain

A single crystal unit of SrVO3

First-principles calculations show how to manipulate some transition metal oxides’ optical and electronic properties for use in thin-film devices.

Liquid crystal displays, touchscreens, and many solar cells rely on thin-film crystalline materials that are both electrically conductive and optically transparent. But the material most widely used in these applications, indium tin oxide (ITO), is brittle and susceptible to cracking. Researchers seeking alternatives have set their sights on strontium vanadate (SrVO3), a material that ticks all the boxes for a transparent conductor. In a study published in EPJ B, Debolina Misra, of the Indian Institute of Information Technology, Design and Manufacturing, Kancheepuram, India, and her colleagues now calculate how SrVO3‘s optical and electron transport properties vary in response to strain. Their simulations provide a detailed mechanism for tuning these properties to optimize the material’s utility in different devices and applications.


EPJ ST Highlight - Many-body interactions feel the heat: Introducing thermal field theory

A many-body process at zero temperature which becomes much more complicated when temperature is a factor. Credit: Robert Lea

Thermal field theory seeks to explain many-body dynamics at non-zero temperatures not considered in conventional quantum field theory.

Quantum field theory is a framework used by physicists to describe a wide range of phenomena in particle physics and is an effective tool to deal with complicated many-body problems or interacting systems.

Conventional quantum field theory describes systems and interactions at zero temperature and zero chemical potential, and interactions in the real world certainly do occur at non-zero temperatures. That means scientists are keen to discover what effects may arise as a result of non-zero temperature and what new phenomena could arise due to a thermal background. In order to understand this, physicists turn to a recipe for quantum field theory in a thermal background — thermal field theory.

In a new paper in EPJ ST, Munshi G. Mustafa, Senior Professor at the Saha Institute of Nuclear Physics, Kolkata, India, introduces a thermal field theory in a simple way weaving together the details of its mathematical framework and its application.


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