- Published on 02 December 2019
An existing technique is better suited to describing superconductivity in pure, single-layer graphene than current methods.
Made up of 2D sheets of carbon atoms arranged in honeycomb lattices, graphene has been intensively studied in recent years. As well as the material’s diverse structural properties, physicists have paid particular attention to the intriguing dynamics of the charge carriers its many variants can contain. The mathematical techniques used to study these physical processes have proved useful so far, but they have had limited success in explaining graphene’s ‘critical temperature’ of superconductivity, below which its’ electrical resistance drops to zero. In a new study published in EPJ B, Jacques Tempere and colleagues at the University of Antwerp in Belgium demonstrate that an existing technique is better suited for probing superconductivity in pure, single-layer graphene than previously thought.
- Published on 16 October 2019
By considering the crystal structures of atomic clusters in new ways, researchers may be able to better assess whether the groups have distinctive shapes, or whether they are amorphous.
Too large to be classed as molecules, but too small to be bulk solids, atomic clusters can range in size from a few dozen to several hundred atoms. The structures can be used for a diverse range of applications, which requires a detailed knowledge of their shapes. These are easy to describe using mathematics in some cases; while in others, their morphologies are far more irregular. However, current models typically ignore this level of detail; often defining clusters as simple ball-shaped structures. In research published in EPJ B, José M. Cabrera-Trujillo and colleagues at the Autonomous University of San Luis Potosí in Mexico propose a new method of identifying the morphologies of atomic clusters. They have now confirmed that the distinctive geometric shapes of some clusters, as well as the irregularity of amorphous structures, can be fully identified mathematically.
- Published on 18 September 2019
A new agent-based computer modelling technique has been applied to the growth and sliding movement of colonies of bacteria
As many people will remember from school science classes, bacteria growing on solid surfaces form colonies that can be easily visible to the naked eye. Each of these is a complex biological system in its own right; colonies display collective behaviours that indicate a kind of 'social intelligence' and grow in fractal patterns that can resemble snowflakes. Despite this complexity, colony growth can be modelled using principles of basic physics. Lautaro Vassallo and his co-workers in Universidad Nacional de Mar del Plata, Argentina have modelled such growth using a novel method in which the behaviour of each of the bacteria is simulated separately. This work has now been published in the journal EPJ B.
- Published on 11 September 2019
The conductivity of dual layers of graphene greatly depends on the states of carbon atoms at their edges; a property which could have important implications for information transmissions on quantum scales.
Made from 2D sheets of carbon atoms arranged in honeycomb lattices, graphene displays a wide array of properties regarding the conduction of heat and electricity. When two layers of graphene are stacked on top of each other to form a ‘bilayer’, these properties can become even more interesting. At the edges of these bilayers, for example, atoms can sometimes exist in an exotic state of matter referred to as the ‘quantum spin Hall’ (QSH) state, depending on the nature of the interaction between their spins and their motions, referred to as their ‘spin-orbit coupling’ (SOC). While the QSH state is allowed for ‘intrinsic’ SOC, it is destroyed by ‘Rashba’ SOC. In an article recently published in EPJ B, Priyanka Sinha and Saurabh Basu from the Indian Institute of Technology Guwahati showed that these two types of SOC are responsible for variations in the ways in which graphene bilayers conduct electricity.
- Published on 02 August 2019
Mathematical analysis reveals that the exponential patterns in RNA diffusion rates linked to small-scale diffusive behaviours
Recent studies have revealed that within cells of both yeast and bacteria, the rates of diffusion of RNA proteins – complex molecules that convey important information throughout the cell – are distributed in characteristic exponential patterns. As it turns out, these patterns display the highest possible degree of disorder, or ‘entropy’, of all possible diffusion processes within the cell. In new research published in EPJ B, Yuichi Itto at Aichi Institute of Technology in Japan explores this behaviour further by zooming in to study local fluctuations in the diffusion rates of RNA proteins. By associating these small-scale diffusion rates with time-varying values for entropy, he finds that the rates of change of entropy in certain time intervals are larger in areas with higher RNA diffusion rates.
- Published on 24 July 2019
New study explains why it is not possible to couple nano-scale microwave generators known as spin-torque oscillators together in series to generate a macroscopic strength signal
Spin-torque oscillators (STOs) are nanoscale devices that generate microwaves using changes in magnetic field direction, but those produced by any individual device are too weak for practical applications. Physicists have attempted - and, to date, consistently failed - to produce reliable microwave fields by coupling large ensembles. Michael Zaks from Humboldt University of Berlin and Arkady Pikovsky from the University of Potsdam in Germany have now shown why connecting these devices in series cannot succeed, and, at the same time, suggested other paths to explore. Their work was recently published in EPJ B.
- Published on 23 July 2019
Computer simulations show that the evolution of material structures during creep deformation can modify material properties.
The properties of many materials can change permanently when they are pushed beyond their limits. When a given material is subjected to a force, or ‘load’, which is stronger than a certain limit, it can become so deformed that it won’t return to its original shape, even after the load is removed. However, heavy loads aren’t strictly necessary to deform materials irreversibly; this can also occur if they are subjected to lighter loads over long periods of time, allowing a slow process called ‘creep’ to take place. Physicists have understood for some time that this behaviour involves sequences of small, sudden deformations, but until now, they have lacked a full understanding of how creep deformation affects material properties over time. In new research published in EPJ B, Michael Zaiser and David Castellanos at the University of Erlangen-Nuremberg in Germany analysed the characteristic ways in which material structures evolve during the early stages of creep deformation.
- Published on 02 July 2019
A new analysis of the bid-ask spread of stock prices reveals that placements and deletions of trade orders can affect stock prices as much as trades themselves
The first rule on the stock market is to buy low and sell high. Economists are well aware of how this behaviour changes the prices of stocks, but in reality, trades alone don’t tell the whole story. Parties like banks and insurance companies rarely trade stocks themselves; instead, they place orders for traders to do so on their behalf, which can be canceled at any time if they are no longer interested. The amount payed by those placing orders is affected by a highly variable quantity called the bid-ask ‘spread’ – the difference between the price initially quoted for a stock, and the final bidding price. In a new study published in EPJ B, Stephan Grimm and Thomas Guhr from Duisburg-Essen University in Germany compare the influences that three price-changing events have on these spread changes. Their work sheds new light on the intricate inner workings of the stock market.
- Published on 12 June 2019
Computational micromagnetics has become an indispensable tool for the theoretical investigation of magnetic structures. Classical micromagnetics has been successfully applied to a wide range of applications including magnetic storage media, magnetic sensors, permanent magnets and more. The recent development of spintronics devices has led to various extensions to the micromagnetic model in order to account for spin-transport effects. Now, Claas Abert of the University of Vienna has prepared a comprehensive Review Article on the subject for EPJ B, aiming to provide an overview of the analytical micromagnetic model as well as its numerical implementation. The main focus is put on the integration of spin-transport effects with classical micromagnetics.
- Published on 12 June 2019
A new model, published in EPJ B and exploring how epidemics spread, could help prevent infections and forest fires from getting out of hand
Recently, epidemics like measles have been spreading due to the lack of vaccinations, and forest fires have become increasingly frequent due to climate change. Understanding how both these things spread, and how to stop them, is more important than ever. Now, two researchers from the National Scientific and Technical Research Council in Bariloche, Argentina, have studied the way epidemics spread in heterogeneous populations. Their findings were recently published in European Physical Journal B.