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Automated workflow for analyzing thermodynamic stability in polymorphic perovskite alloys

Araujo, Luis Octavio de; Rêgo, Celso R. C. 1; Wenzel, Wolfgang 1; Piotrowski, Maurício Jeomar; Dias, Alexandre Cavalheiro; Guedes-Sobrinho, Diego
1 Institut für Nanotechnologie (INT), Karlsruher Institut für Technologie (KIT)

Abstract:

In this first-principles investigation, we explore the polymorphic features of pseudo-cubic alloys, focusing on the impact of mixing organic and inorganic cations on their structural and electronic properties, configurational disorder, and thermodynamic stability. Employing an automated cluster expansion within the generalized quasichemical approximation (GQCA), our results reveal how the effective radius of the organic cation (rMA = 2.15 Å, rFA = 2.53 Å) and its dipole moment (μMA = 2.15 D, μFA = 0.25 D), influences Glazer’s rotations in the A 1−xCsxPbI 3 (A = MA, FA) sublattice, with MA-based alloy presenting a higher critical temperature (527 K) and being stable for x > 0.60 above 200 K, while its FA analog has a lower critical temperature (427.7 K) and is stable for x < 0.15 above 100 K. Additionally,
polymorphic motifs magnify relativistic effects, impacting the thermodynamic behavior of the systems. Our methodology leverages the SimStack framework, an automated scientific workflow that enables the nuanced modeling of polymorphic alloys. This structured approach allows for comprehensive calculations of thermodynamic properties, phase diagrams, optoelectronic insights, and power conversion efficiencies while meticulously incorporating crucial relativistic effects like spinorbit coupling (SOC) and quasi-particle corrections. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000175644
Veröffentlicht am 28.10.2024
Originalveröffentlichung
DOI: 10.1038/s41524-024-01320-8
Scopus
Zitationen: 1
Web of Science
Zitationen: 1
Dimensions
Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Nanotechnologie (INT)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2024
Sprache Englisch
Identifikator ISSN: 2057-3960
KITopen-ID: 1000175644
Erschienen in npj Computational Materials
Verlag Nature Research
Band 10
Heft 1
Seiten Art.-Nr.: 146
Vorab online veröffentlicht am 04.07.2024
Nachgewiesen in Web of Science
Dimensions
Scopus
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