- Published on 02 February 2021
Novel approaches in graph theory have enabled researchers to reveal the characteristic configurations of neurons which arise as our brains process pain
The many different sensations our bodies experience are accompanied by deeply complex exchanges of information within the brain, and the feeling of pain is no exception. So far, research has shown how pain intensity can be directly related to specific patterns of oscillation in brain activity, which are altered by the activation and deactivation of the ‘interneurons’ connecting different regions of the brain. However, it remains unclear how the process is affected by ‘inhibitory’ interneurons, which prevent chemical messages from passing between these regions. Through new research published in EPJ B, researchers led by Fernando Montani at Instituto de Física La Plata, Argentina, show that inhibitory interneurons make up 20% of the circuitry in the brain required for pain processing.
- Published on 29 January 2021
Microscopically very different physical, biological and cultural systems all evolve through a sequence of stages, each characterized by stationary fluctuations around constant values of relevant macroscopic observables. Sudden and rapid changes, called quakes, induce transitions from one stage to the next and reveal the non-equilibrium nature of the dynamics. The duration of the stages increases over time, producing a multi-scaled dynamical behavior known in physics under the name of ``physical aging'', and rooted in all cases in a hierarchically structured underlying configuration space. Record Dynamics (RD) is a coarse-graining approach treating the staged evolution of complex metastable systems with the same statistical tools. This colloquium paper reviews RD methods and ideas that have gradually evolved over time and shows how RD can be applied to selected cases of biological and physical origin. The main property described is that quakes are a log-Poisson process and that the coarse-grained dynamics is therefore log-time homogeneous. The bibliography points the interested reader to the original RD papers and their background.
- Published on 07 December 2020
Improved modelling techniques have enabled a group of researchers to better predict how damaging conditions in the brain can be triggered by complex dynamics in branching networks of neurons.
Within the staggeringly complex networks of neurons which make up our brains, electric currents display intricate dynamics in the electric currents they convey. To better understand how these networks behave, researchers in the past have developed models which aim to mimic their dynamics. In some rare circumstances, their results have indicated that ‘tipping points’ can occur, where the systems abruptly transition from one state to another: events now commonly thought to be associated with episodes of epilepsy. In a new study published in EPJ B, researchers led by Fahimeh Nazarimehr at the University of Technology, Tehran, Iran, show how these dangerous events can be better predicted by accounting for branches in networks of neurons.
- Published on 04 December 2020
Two-dimensional (2D) materials are condensed matter systems whose thickness varies from a single atom, as in graphene, to few atoms, as in transition metal dichalcogenides (TMDs). These exceedingly thin materials present, nevertheless, strong light-matter interaction.
EPJ B Colloquium - Hierarchically nanostructured thermoelectric materials: challenges and opportunities for improved power factors
- Published on 26 November 2020
The field of thermoelectric materials has undergone a revolutionary transformation over the last couple of decades as a result of the ability to nanostructure and synthesize myriads of materials and their alloys. The ZT figure of merit, which quantifies the performance of a thermoelectric material has more than doubled after decades of inactivity, reaching values larger than two, consistently across materials and temperatures. Central to this, is the drastic reduction in the materials’ thermal conductivity due to the hierarchical scattering of phonons on the purposely included numerous interfaces, boundaries, dislocations, point defects, phases, etc. However, as the thermal conductivity has reached amorphous values, these benefits are reaching their limits. Any further benefits would come from the power factor, namely the product of the electronic conductivity and Seebeck coefficient squared. These quantities need to be maximized, however, they are in general inversely related, which makes power factor improvement a significant challenge.
- Published on 06 November 2020
New research reveals that applying a magnetic field to a chiral metamaterial can change the way it polarises light.
Optical activity in chiral molecules has become a hot topic in physics and optics, representing the ability to manipulate the polarized state of light. Understanding how molecules rotate the plane of plane-polarized light has widespread applications, from analytic chemistry to biology and medicine — where it can, for example, be used to detect the amount of sugar in a substance. A new study published in EPJ B by Chengping Yin of the Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials, South China, aims to derive an analytical model of optical activity in black phosphorous under an external magnetic field.
- Published on 25 September 2020
Calculations involving ‘imaginary’ magnetic fields show how the transitioning behaviours of antiferromagnets are subtly shaped by their lattice arrangements.
Antiferromagnets contain orderly lattices of atoms and molecules, whose magnetic moments are always pointed in exactly opposite directions to those of their neighbours. These materials are driven to transition to other, more disorderly quantum states of matter, or ‘phases,’ by the quantum fluctuations of their atoms and molecules – but so far, the precise nature of this process hasn’t been fully explored. Through new research published in EPJ B, Yoshihiro Nishiyama at Okayama University in Japan has found that the nature of the boundary at which this transition occurs depends on the geometry of an antiferromagnet’s lattice arrangement.
- Published on 23 September 2020
Molecular dynamics simulations have shown that the mysteriously high efficiency of polymer LEDs arises from interactions between triplet excitons in their polymer chains, and unpaired electrons in their molecular impurities.
Polymer LEDs (PLEDs) are devices containing single layers of luminescent polymers, sandwiched between two metal electrodes. They produce light as the metal layers inject electrons and holes into the polymer, creating distortions which can combine to form two different types of electron-hole pair: either light-emitting ‘singlets,’ or a non-emitting ‘triplets.’ Previous theories have suggested that the ratio between these two types should be around 1:3, which would produce a light emission efficiency of 25%. However, subsequent experiments showed that the real value can be as high as 83%. In new research published in EPJ B, physicists in China, led by Yadong Wang at Hebei North University, found that this higher-than-expected efficiency can be reached through interactions between triplet excitons, and impurities embedded in the polymer.
- Published on 03 September 2020
Recent emerging interest in experiments of single-polymer dynamics have encouraged computational physicists to revive their understanding of these phenomena, particularly in the nonequilibrium context. In a Colloquium recently published in EPJB, authors from Institut für Theoretische Physik at the University of Leipzig discuss the currently evolving approaches of investigating the evolution dynamics of homopolymer collapse using computer simulations.
- Published on 03 August 2020
Through fresh analysis of a method first proposed by Alan Turing to explain the diversity of natural patterns, a team of researchers offer new explanations of how living systems can order themselves on large scales.
In 1952, Alan Turing published a study which described mathematically how systems composed of many living organisms can form rich and diverse arrays of orderly patterns. He proposed that this ‘self-organisation’ arises from instabilities in un-patterned systems, which can form as different species jostle for space and resources. So far, however, researchers have struggled to reproduce Turing patterns in laboratory conditions, raising serious doubts about its applicability. In a new study published in EPJ B, researchers led by Malbor Asllani at the University of Limerick, Ireland, have revisited Turing’s theory to prove mathematically how instabilities can occur through simple reactions, and in widely varied environmental conditions.