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Finding stable multi-component materials by combining cluster expansion and crystal structure predictions
Linköping University, Department of Physics, Chemistry and Biology, Materials design. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-5973-0065
Linköping University, Department of Physics, Chemistry and Biology, Materials design. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Physics, Chemistry and Biology, Materials design. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-5036-2833
2023 (English)In: npj Computational Materials, E-ISSN 2057-3960, Vol. 9, no 1, article id 21Article in journal (Refereed) Published
Abstract [en]

A desired prerequisite when performing a quantum mechanical calculation is to have an initial idea of the atomic positions within an approximate crystal structure. The atomic positions combined should result in a system located in, or close to, an energy minimum. However, designing low-energy structures may be a challenging task when prior knowledge is scarce, specifically for large multi-component systems where the degrees of freedom are close to infinite. In this paper, we propose a method for identification of low-energy crystal structures within multi-component systems by combining cluster expansion and crystal structure predictions with density-functional theory calculations. Crystal structure prediction searches are applied to the Mo2AlB2 and Sc2AlB2 ternary systems to identify candidate structures, which are subsequently used to explore the quaternary (pseudo-binary) (MoxSc1-x)(2)AlB2 system through the cluster expansion formalism utilizing the ground-state search approach. Furthermore, we show that utilizing low-energy structures found within the cluster expansion ground-state search as seed structures within crystal structure predictions of (MoxSc1-x)(2)AlB2 can significantly reduce the computational demands. With this combined approach, we not only correctly identified the recently discovered Mo(4/3)Sc(2/3)AlB(2)i-MAB phase, comprised of in-plane chemical ordering of Mo and Sc and with Al in a Kagome lattice, but also predict additional low-energy structures at various concentrations. This result demonstrates that combining crystal structure prediction with cluster expansion provides a path for identifying low-energy crystal structures in multi-component systems by employing the strengths from both frameworks.

Place, publisher, year, edition, pages
NATURE PORTFOLIO , 2023. Vol. 9, no 1, article id 21
National Category
Theoretical Chemistry
Identifiers
URN: urn:nbn:se:liu:diva-192169DOI: 10.1038/s41524-023-00971-3ISI: 000929023800001OAI: oai:DiVA.org:liu-192169DiVA, id: diva2:1741777
Note

Funding Agencies|Linkoeping University

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2024-02-02
In thesis
1. Explorations of boron-based materials through theoretical simulations
Open this publication in new window or tab >>Explorations of boron-based materials through theoretical simulations
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis focuses on boron-based materials, notable for their structural complexity and unique combination of ceramic and metallic properties. These properties typically result in materials with high mechanical strength, electrical conductivity, and melting points. Among these materials are MAB phases, a family of layered materials comprised of a transition metal (M), an A-element (typically an element from Group 13-14), and boron (B). The layered nature of these materials provides a pathway towards the realization of 2D materials, coined MBenes (or boridene), through chemical exfoliation.

While the potential for discovering novel materials is immense, their realization often demands extensive experimental efforts. Theoretical models may here be used as a filter by guiding experimental endeavours. The work presented herein aims to leverage theoretical models and to develop frameworks suitable for reliable thermodynamical predictions in hope of the discovery of additional boron-based materials.

First-principles calculations, particularly density functional theory (DFT), have extensively been employed in this thesis to determine the ground state energy of materials and predict their stability or tendency to decompose. However, first-principles calculations typically rely on a pre-defined crystal structure which may be constructed through a priori information or obtained through the use of crystal structure prediction (CSP) frameworks. We herein explore both of these approaches by i) systematically substituting elements in known low-energy structures, and ii) deriving novel low-energy structures by combining CSP with cluster expansion (CE) models.

The first approach is herein exemplified when considering the low-energy structures of V3B2 (P4/mbm) and Cr5B3 (I4/mbm). These structures are comprised of two M-sites in addition to boron and thus form the general compositions M’2M’’B2 and M’4M’’B3, respectively. In a follow-up project, this approach was refined by probing the Materials Project database for additional binary boron-based materials with structures of this nature. The M-sites of these candidate structures were further populated with elements ranging from Group 2 to 14 with the aim of discovering novel ternary boron-based materials.

Alternatively, a hybrid method of the two techniques is herein explored in which manually designed hexagonal structures were made based on orthorhombic low-energy counterpart structures. A set of structural polymorphs for the M2AB2, M3AB4, M4AB6, MAB, and M4AB4 compositions were studied with varying stacking sequences followed by the evaluation of their thermodynamical stability.

The second approach requires little to no structural information but is typically limited to considering fewer material systems due to a higher computational cost. This approach is herein applied to study low-energy basins within the complex phase space of (MoxSc1-x)2AlB2 and (M’xM’’1-x)3AlB4 systems with the aim of finding novel quaternary boron-based materials. A framework, suitable for exploring chemical phase spaces of complex systems, was herein developed by combining CSP and CE models with DFT calculations. The suggested framework is initiated by performing CSP simulations on the n-1 dimensional systems. Identified low-energy structures are subsequently used as input lattices to construct CE models for the n-dimensional system. The low-energy basins found in the n-dimensional system may potentially be used as seed structures in a comprehensive CSP simulation or as input structures for high-throughput screening. This approach, not only provides an efficient pathway to identify low-energy basins of complex material systems, but also attempts to bridge the gap in materials discovery with or without prerequisite information.

The aspiration of bridging the gap between state-of-the-art simulation techniques, whether reliant on a priori information or not, is rooted in the intention of enhancing the foundation of materials discovery. The refinement of these theoretical simulations serves to guide and augment experimental efforts for the synthesis of novel materials which is pivotal for addressing and achieving current and future sustainability goals.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2024. p. 71
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 2365
Keywords
Density Functional Theory, Thermodynamic Stability, Borides, Crystal Structure Prediction, Cluster Expansion, High-throughput
National Category
Materials Chemistry
Identifiers
urn:nbn:se:liu:diva-200613 (URN)10.3384/9789180754804 (DOI)9789180754798 (ISBN)9789180754804 (ISBN)
Public defence
2024-03-01, Online through Zoom (contact henrietta.winslow@liu.se) and Planck, F Building, Campus Valla, Linköping, 09:15 (English)
Opponent
Supervisors
Note

Funding agencies: The Swedish Research Council (grant numbers 2019-05047, 2022-06099, 2022-06725 and 2018-05973) and the Knut and Alice Wallenberg (KAW) foundation (grant number KAW 2020.0033)

Available from: 2024-02-02 Created: 2024-02-02 Last updated: 2024-02-02Bibliographically approved

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