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Accueil > Emplois & stages > Sujets de master > Discovery of Original Solid-State Phases with the TBAIRSS Algorithm

Discovery of Original Solid-State Phases with the TBAIRSS Algorithm

Laboratoire de chimie et physique quantiques (LCPQ) ; Thierry Leininger
TEAM NAME : « Modelling, Aggregates, Dynamics »
LABORATORY WEBSITE : http://www.lcpq.ups-tlse.fr/
INTERNSHIP SUPERVISOR PHONE AND EMAIL : 0561556836 ; jerome.cuny@irsamc.ups- tlse.fr

Discovery and Characterisation of Original Solid- State Phases with the Tight-Binding Ab Initio Random Structure Searching Algorithm (TBAIRSS).


Understanding the structure and phase changes associated with battery electrodes is key in optimizing their electrochemical performance in the view to develop high-capacity batteries. In particular, the characterisation of the phases associated with charging and discharging is challenging and tremendously expensive to implement experimentally, especially during charge and discharge, which limits our understanding of those processes. As such, theoretical screening of candidate structures before experimental synthesis is a key step in developing more robust batteries.

The laboratory of quantum chemistry and quantum physics (LCPQ) has expertise in extensive potential energy surface (PES) exploration through the world-wide recognised development of the density-functional based tight-binding (DFTB) method. Up to now, this expertise have been limited to finite-size systems, mainly atomic and molecular aggregates. The PES topology of aggregates and solid-state compounds are very different and necessitate different methodologies for their exploration. For solid-state systems, the ab initio random structure searching (AIRSS) approach [1] is an efficient way to search for low-energy phases of materials on the “periodic- crystal“ PES. Over the last ten years, its development has been a step-change in materials science due to its strong predictive ability of new solid-state phases. From high-pressure phases [2], conversion electrodes [3] or nano-phase change memory [4], time and again its predictions have been subsequently experimentally verified. However, as for other PES exploration approaches, the computational bottleneck of AIRSS lies in the huge number of energy evaluations (several thousands in the better cases) which are required to properly explore the PES. Up to now, it has exclusively been combined with density functional theory (DFT) calculations which limits AIRSS applications in terms of chemical complexity and system sizes.

The aim of this internship is to cement a new collaboration between LCPQ and Andrew J. Morris from the University of Birmingham by validating the coupling of AIRSS and DFTB to search for new low-energy phases of battery materials. The main objective will be to develop a workflow allowing AIRSS calculations with DFTB, called TBAIRSS. Once properly optimised, this package will first be tested on monoatomic systems such as C, Si, P and B. The resulting structures obtained at various pressures will be compared to AIRSS+DFT results. Once validated TBAIRSS will be used to explore the PES of more complex systems such as boron carbides and silicon oxides which display a large variety of phases and Ge-Se phase change materials. If successful, the application of TBAIRSS to the description of new battery materials will then be approached.

[1] C. J. Pickard et al., Phys. Rev. Lett. 97, 045504 (2006). [2] I. Errea et al., Nature 532, 81 (2016). [3] J. Stratford et al, J. Am. Chem. Soc. 139 7273-7286 (2017). M. Mayo et al., Chem. Mater. 28 2011-2021 (2016). L. Marbella et al J. Am. Chem Soc. ASAP (2018). [4] A. Vasylenko et al., ACS Nano ASAP (2018). P. V. C. Medeiros et al., ACS Nano 11, 6178, (2017).