Tomáš Mančal is an Associate Professor of Physics at Charles University in Prague, Czech Republic. He obtained his PhD in Physics from Humboldt University in Berlin and worked as a postdoc at the University of California Berkeley and Lawrence Berkeley National Laboratory. He joined the Faculty of Mathematics and Physics at the Charles University in 2007. His research interests include nonlinear spectroscopy and open quantum systems in application to biological and chemical problems.

By Mariano de Souza

Over the last decades, it has become clear that electronic correlation effects can give rise to exotic manifestations of matter. Examples include Mott and charge-ordered phases, superconductivity, and various types of long-range magnetic ordering. Molecular conductors [1-3] have served as an appropriate playground for their exploration. The so-called ‘Mott insulators’, having an odd number of conduction electrons per unit cell, according to band theory, should be metals. That this is not the case is due to the same order of magnitude of the hopping terms and the on-site Coulomb repulsion (“Hubbard parameters“). Interestingly enough, superconductivity can be induced by applying moderate hydrostatic pressure. In this presentation, fundamental aspects of the Mott Physics, classical/quantum critical phenomena, and the Grüneisen parameter [4-6], including the breakdown of the Grüneisen ratio near a finite-temperature critical endpoint, are reviewed. Further perspectives are discussed as well.

1 – M. de Souza, J-P. Pouget, J. Phys.: Condens. Matter 25, 343201 (2013)
2 – M. de Souza, L. Bartosch, J. Phys.: Condens. Matter 27, 053203 (2015)
3 – P- Lunkenheimer et al., Nature Materilas 11, 755 (2012)
4 – G.O. Gomes, H.E. Stanley, M. de Souza, Scientific Reports 9, 12006 (2019)
5 – L. Squillante et al., Scientific Reports 11, 9431 (2021) and Materials Research Bulletin 142, 111413 (2021)

By Werner Janse van Rensburg

For the past 15 years the Centre for High Performance Computing (CHPC) has built a sustainable opportunity for enabling HPC-focused research for South Africa and the region. In particular, the Materials Science user base of the CHPC is not only one of the largest, it has also consistently shown significant research outputs by diverse institutions. However, the question remains: has the potential of the CHPC fully been realised by the scientific community?

This talk will provide an overview of the role the CHPC (within the National Integrated Cyber Infrastructure System – NICIS) has played to afford state-of-the-art HPC resources for the research community. In particular, the focus will be on successes in supporting the Materials Science / Computational Chemistry community and on creating awareness of opportunities that may still be eluding some researchers. Indeed, if the CHPC is still an untapped opportunity for some (or many), this talk will strive to bridge that gap.

By Tomáš Mančal

Virtually all energy powering the processes in the biosphere originates from the Sun. Photosynthesizing organisms have developed a delicate hierarchy of nanoscopic machinery that supports the processes of light energy capture, excitation energy transfer, and charge separation and transport. These so-called primary processes of photosynthesis represent the first steps of light- to chemical energy conversion in the light-harvesting organisms. Unlike the natural photosynthetic light- to energy conversion as a whole, which has an efficiency of only a few percent, its primary processes are highly efficient. Nearly every captured photon converts to a separated charge. This high efficiency rests on only a few elementary design principles that the photosynthetic machinery follows. In this lecture, we will lay down the fundamental quantum physics describing the electronic structure and the energy transfer function of the natural photosynthetic light-harvesting antennas. The relation between the spatial structure of the antennas and their photosynthetic function will be explained in terms of a few basic physical principles universally valid across quantum and classical physics, namely, energy conservation, resonance interaction, and equilibrium thermodynamics. We will also discuss the role of quantum effects in nanoscopic systems that inevitably rest on the quantum to classical physics boundary.

By Regina Maphanga

Computer modelling has increasingly become a driving force in the discovery and design of novel materials. The computational simulation methods are influencing all areas of study, with a great impact in physics, materials science, chemistry, biology and engineering. With the advancement of computing powers, complex materials and their properties are increasingly investigated. Over the past two decades, modelling of materials moved from conventional methods development and purely computational studies towards the discovery and design of novel materials guided by modelling results, data mining and machine learning together with a closer collaboration between predictions and experimental validation. This presentation will demonstrate advances made from molecular modeling to applying machine learning models to predict the properties of energy materials.

By Édgar Roldán

Stochastic thermodynamics is an emerging field that studies the thermodynamics of systems driven out of equilibrium in the presence of fluctuations. Unprecedented joint theoretical and experimental advances have revealed novel universal thermodynamic laws at the mesoscale, which includes fundamental constraints for biological processes. A paradigmatic case study of nonequilibrium fluctuations are the spontaneous oscillations of mechanosensory hair bundles responsible for sound transduction. The pursuit of understanding the motion of such biologically-relevant systems has brought to 40 years of biophysical modelling using stochastic theory, yet a precise thermodynamic characterisation of sound transduction is an open challenge. This colloquium will showcase recent progress in the application of biophysics and stochastic thermodynamics to analyse fluctuations of hair-cell bundles responsible for sound transduction in the bullfrog’s sacculus. Through a holistic theory-experiment approach, it has been shown that spontaneous hair-cell bundle fluctuations are nonequilibrium, i.e. active. Moreover, using time-irreversibility measures and thermodynamic uncertainty relations we have estimated the rate of entropy production of hair-bundle fluctuations in different experimental, physiological conditions [1]. Furthermore, we have introduced and solved analytically a non-Markovian model that we have employed successfully in parametric inference and to predict the minimal energetic cost required to sustain spontaneous otoacoustic emissions in the ear of the bullfrog [2].

[1] É Roldán et al., New Journal of Physics 23, 083013 (2021)
[2] G Tucci et al., arXiv:2201.12171 (2022)

By Konstantinos Zoubos

I will provide an overview of how fundamental concepts from QFT, such as path integrals, the renormalisation group and topological configurations such as solitons, can be used to improve our understanding of condensed matter systems. Particular applications that I will focus on are the study of phase transitions and the associated critical exponents, as well as topologically ordered states in quantum spin chains.

By Victor S. Aigbodion and C.O. Ujah

Computational modelling in materials science and engineering involves solving materials-related problems using computer programming. There are various mathematical models for analyzing problems at multiple length and time scales, which help in appreciating the evolution of material structures and how these structures control material properties efficiently. With this knowledge, materials selection for specific applications and materials design for advanced applications can be done.
There are different computational models applied to various material categories. At the electronic level, Density Functional Theory (DFT) is the preferred computational model. At the atomistic simulation level, Molecular Dynamics (MD) and Monte Carlo (MC) techniques are the preferred tools. At the nano and micron simulation levels, the Phase-field Method (PFM) is the most appropriate model. At the structural level, the Finite Element Method (FEM) is the most useful computational technique.
Computer simulations, besides being a connecting link between analytical and experimental approaches for analysing hypothetical problems, are also an exploratory research tool used under physical conditions that cannot be feasible in real laboratory experiments. Hence, computer simulation has established its applications in systems where the gap between theoretical prediction and laboratory measurements is large. Therefore, there is always a close synergy between computational modelling and experimental analysis. The cooperation is in the form that the experimental analyst designs experiments that make the job of modelling easier, while the modeller models real systems that can be empirically feasible.
Computational modelling has made simulations of practical interest in material science and engineering for advanced, smart and robust product designs and testing feasible.

In this section, current trends in the area of computational condensed matter and materials physics and chemistry will be discussed. The development of novel techniques, catalysis and materials design and engineering using both experimental and theoretical methods will be emphasised. Different novel materials ranging from 2D to 3D systems will be addressed as well as beneficial systems that look into the current state of the green/sustainable economy. This section would provide perspective on future direction in the area of computational condensed matter and materials physics and chemistry.