Ab initio property predictions of quinary solid solutions using small binary cells
The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density...
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Published in | Computational materials science Vol. 238; no. C; p. 112924 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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01.04.2024
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Abstract | The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. In this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.
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•Properties of two high entropy alloys are modelled using the SSOS approach.•We show small binary cells are sufficient to predict several properties of interest.•NbTaTiHfZr and MoNbTaVW systems are searched for optimal Pugh’s ratio compositions. |
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AbstractList | The Set of Small Ordered Structures (SSOS) approach is an ab initio technique for modelling random solid solutions in which many small structures are averaged so that their correlation functions match those of a desired composition. SSOS has been shown to be effective in reducing the cost of density functional theory calculations relative to other well-known techniques such as cluster expansions and special quasirandom structures for modelling solid solutions. In this work, we demonstrate that SSOS’s can be constructed using cells with only a subset of elements while still accurately modelling multi-component systems. Specifically, we show that small binary cells can effectively model two quinary high entropy alloys – NbTaTiHfZr and MoNbTaVW – accurately capturing properties such as formation energy, lattice parameters, elastic constants, and root-mean-square atomic displacements. Overall, this insight is useful for those looking to construct databases of such small structures for predicting the properties of multi-component solid solutions, as it greatly decreases the number of structures that needs to be considered.
[Display omitted]
•Properties of two high entropy alloys are modelled using the SSOS approach.•We show small binary cells are sufficient to predict several properties of interest.•NbTaTiHfZr and MoNbTaVW systems are searched for optimal Pugh’s ratio compositions. |
ArticleNumber | 112924 |
Author | Rothchild, Eric Kuner, Matthew C. Asta, Mark D. Chrzan, Daryl C. |
Author_xml | – sequence: 1 givenname: Matthew C. orcidid: 0000-0002-8218-8558 surname: Kuner fullname: Kuner, Matthew C. email: matthewkuner@berkeley.edu organization: Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA – sequence: 2 givenname: Eric surname: Rothchild fullname: Rothchild, Eric organization: Materials, Physical, and Chemical Sciences Center, Sandia National Laboratories, Albuquerque, New Mexico 87185, USA – sequence: 3 givenname: Mark D. orcidid: 0000-0002-8968-321X surname: Asta fullname: Asta, Mark D. organization: Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA – sequence: 4 givenname: Daryl C. surname: Chrzan fullname: Chrzan, Daryl C. organization: Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA |
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Cites_doi | 10.1002/zamm.19290090104 10.21105/joss.05995 10.1103/PhysRevLett.65.353 10.1103/PhysRevMaterials.3.113608 10.1007/s11669-009-9570-6 10.1016/j.actamat.2014.11.014 10.1016/j.actamat.2020.10.044 10.1103/PhysRevB.59.1758 10.1016/j.msec.2020.110959 10.1080/14786440808520496 10.1038/s41524-019-0173-4 10.1103/PhysRevB.77.224115 10.1016/j.jmps.2021.104389 10.1002/adma.201701678 10.1016/j.matchemphys.2017.06.038 10.1103/PhysRevB.102.174209 10.1016/j.calphad.2013.06.006 10.1016/j.actamat.2016.08.081 10.1186/2193-9772-3-12 10.3389/fmats.2020.00290 10.1063/1.4812323 10.1038/s41598-022-16082-w 10.1103/PhysRevLett.77.3865 10.1080/21663831.2016.1221861 10.1016/j.commatsci.2020.110213 10.1103/PhysRevB.88.155105 10.1063/1.4966659 10.1016/j.actamat.2023.119104 10.1016/j.jallcom.2015.07.209 10.1557/jmr.2018.153 10.3390/e18050189 10.3389/fmats.2017.00036 10.1103/PhysRev.156.809 10.1016/j.intermet.2010.05.014 10.1038/sdata.2015.9 10.1103/PhysRevLett.116.105501 10.1016/j.commatsci.2012.10.028 10.1016/S0364-5916(02)80006-2 10.1103/PhysRevB.5.2382 10.1038/s41598-023-49258-z 10.1038/s41578-019-0121-4 10.1103/PhysRevB.54.11169 10.1007/s10853-012-6260-2 10.1016/j.actamat.2023.119117 10.1103/PhysRevB.50.17953 10.1557/jmr.2018.152 10.1016/j.matlet.2016.08.060 10.1103/PhysRevB.81.224202 10.1016/j.commatsci.2012.02.015 10.1088/0370-1298/65/5/307 10.1016/j.jmst.2021.03.024 10.1002/cpe.3505 10.1016/j.intermet.2019.01.004 10.1016/j.jallcom.2021.160776 10.1103/PhysRevMaterials.1.023404 |
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Keywords | Set of small ordered structures (SSOS) High entropy alloys (HEAs) Random solid solutions High-throughput density functional theory (HT-DFT) Disorder Small structures |
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SubjectTerms | Disorder High entropy alloys (HEAs) High-throughput density functional theory (HT-DFT) Random solid solutions Set of small ordered structures (SSOS) Small structures |
Title | Ab initio property predictions of quinary solid solutions using small binary cells |
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