YRM 2024 - 20th ETSF Young Researchers’ Meeting 2024
Location: Toulouse Nodes involved: CECAM-FR-GSO (managing node), CECAM-FR-RA.
Organisers
Welcome to ETSF-YRM24, the 20th ETSF Young Researcher's Meeting - 27th-31st May 2024, Toulouse, France.
Find us also here.
Registration and abstract summission are open until April 19th 2024. New registration deadline: April 26th 2024.
Register here: https://lcpq.github.io/yrm2024/registration/.
For any inquiries, contact us at yrm2024organizers@gmail.com.
The European Theoretical Spectroscopy Facility (ETSF, https://www.etsf.eu/) is a network of European research teams in the field of theoretical spectroscopy. The annual Young Researchers’ Meeting (YRM) is one of the many initiatives of ETSF. Its objective is to provide young researchers (MSc and PhD students, postdoctoral researchers) with the opportunity to share their work and acquaint themselves with state-of-the-art theoretical methods applied to different disciplines (physics, chemistry, materials sciences).
The scientific program will be divided into 5 sessions:
- electronic structure methods development
- optical properties of materials
- vibrational properties of materials and transport
- strongly correlated systems and magnetism
- machine learning in materials science
More about the scientific topics covered in YRM2024 :
1) Electronic structure methods development. Methods to compute accurate electronic structure are under constant improvement to study more and more complex systems, such as 2D materials [1], crystals, van der Waals heterostructures or hybrid molecules/solid systems. Typical methods are many-body GW approximation or standard Density Functional Theory. In particular for the latter, there are efforts in the direction of developing new functionals to study more diverse systems, such as Koopmans-compliant functionals for finite molecules.[2] 2) Optical properties. The interaction between light and matter is at the basis of spectroscopic probing and technological applications. In particular, spectroscopy techniques (both steady-state or time-resolved) applied to solids, molecules or hybrid systems allow to gain insight in fundamental processes otherwise not accessible. Optical responses, associated with different spectroscopy techniques, are computed numerically, with increasing precision on increasingly more challenging systems. Further development and application of existing methods, such as GW approximations, Bethe-Salpeter equation (BSE) or time-dependent DFT (TDDFT) [3][4][5] and their implementation in multiple software (VASP, SIESTA, Yambo, Elk..) have been crucial steps to access fundamental electronic mechanisms at work at the microscopic level. 3) Vibrational properties and transport. The description of phonon properties is needed to describe many phenomena in solids and molecules, such as spectroscopic observables, crystal dynamics or electronic transport.[6] In particular the latter, requires to properly account for coupling between electrons and phonons. The standard methods to compute phonon properties include Density Functional Perturbation Theory, in which deformation potentials are computed in a perturbative way, or frozen-phonons, in which quantities of interest are computed with finite-difference derivatives. For molecular systems, it is necessary to go beyond the Born-Oppenheimer approximation and treat the vibrational properties in a non-adiabatic way. An example is mixed quantum-classical non-adiabatic dynamics to describe finite-size systems accurately while also including the effect of the environment [7]. 4) Strongly correlated systems and magnetism. They include a wide class of materials, the most characteristic ones being the Mott insulators, geometrically frustrated pyrochlore magnets [8], 4f-electron systems [9], and unconventional superconductors. [10] Overall, their investigation attracts a large research interest due to the related novel unusual phenomena. Moreover, they constitute a playground for the study of complicated many-body processes. Their description requires models beyond the standard band theory, properly accounting for the electronic correlations, such as the dynamical mean field theory (DMFT) , slave particle approaches , Quantum Monte Carlo , and others. [11[12][13] 5) Machine learning in materials science. This session is specific to YRM 2024 and was motivated by the large number of talks on this topic in the previous YRM2023 edition. This trend reflects the increasing application of machine learning-based techniques in materials science in general, as well as in several other areas, notably machine learning in the chemical sciences, thermoelectric and photovoltaic materials design, lithium-ion battery development, and atomistic simulations. [14][15].
References
Sofia Canola (Institute of Physics of the Czech Academy of Sciences) - Organiser
France
Abdallah Ammar (LCPQ, CNRS) - Organiser
Karthikeyan SARAVANABAVAN (CEA) - Organiser
Italy
Leonardo Biancorosso (University of Trieste) - Organiser