Atomistic Study of a CaTiO₃‐Based Mixed Conductor: Defects, Nanoscale Clusters, and Oxide‐Ion Migration

Abstract

Mixed oxide‐ion and electronic conductivity can be exploited in dense ceramic membranes for controlled oxygen separation as a means of producing pure oxygen or integrating with catalytic oxidation. Atomistic simulation has been used to probe the energetics of defects, dopant‐vacancy association, nanoscale cluster formation, and oxide‐ion transport in mixed‐conducting CaTiO3. The most favorable energetics for trivalent dopant substitution on the Ti site are found for Mn3+ and Sc3+. Dopant‐vacancy association is predicted for pair clusters and neutral trimers. Low binding energies are found for Sc3+ in accordance with the high oxide‐ion conductivity of Sc‐doped CaTiO3. The preferred location for Fe4+ is in a hexacoordinated site, which supports experimental evidence that Fe4+ promotes the termination of defect chains and increases disorder. A higher oxide‐ion migration energy for a vacancy mechanism is predicted along a pathway adjacent to an Fe3+ ion rather than Fe4+ and Ti4+, consistent with the higher observed activation energies for ionic transport in reduced CaTi(Fe)O3–δ.

The application of a new potential model to the rare-earth doping of SrTiO3 and CaTiO3

“…24 The increased strength of the Ti-O interaction from this potential means that the energy required to remove a Ti or O ion is far greater than for the Lewis-Catlow potential. The same is also true for these vacancies in CaTiO 3 when comparing our results with the results of Mather et al 7 where again the Lewis and Catlow Ti-O potential was used. Although no defect energies were reported for CaTiO 3 by Bassoli et al, 9 a similar potential set to Mather et al was used and it is therefore reasonable to assume the energies would also be similar.…”

Nanoscale Iron Redistribution during Thermochemical Decomposition of CaTi1–xFexO3−δ Alters the Electrical Transport Pathway: Implications for Oxygen-Transport Membranes, Electrocatalysis, and Photocatalysis

“…Here, we hypothesize that the lower decomposition temperature is a combined effect of (i) higher Fe concentration and (ii) more surface area in our porous samples: the greater surface area facilitates oxygen vacancy (V O •• ) formation at the solid surface even at the low temperatures used in our study, which then electrostatically attract reduced Fe cations (Fe Ti / and Fe Ti // ) to the surface. Fe migration to regions of higher oxygen vacancy concentration is likely driven by their negative binding energy with oxygen vacancies Fe Ti / –V O •• in dimer and trimer defect clusters . That we observe Fe metal and oxides via decomposition at significantly lower temperatures than Salles et al’s CaTi 0.9 Fe 0.1 O 3−δ suggests that there is a balance between increased ceramic surface area, Fe concentration, and thermochemical stability.…”

“…Fe migration to regions of higher oxygen vacancy concentration is likely driven by their negative binding energy with oxygen vacancies Fe Ti / –V O •• in dimer and trimer defect clusters. 7 That we observe Fe metal and oxides via decomposition at significantly lower temperatures than Salles et al’s CaTi 0.9 Fe 0.1 O 3−δ suggests that there is a balance between increased ceramic surface area, Fe concentration, and thermochemical stability.…”

“…Fe migration to regions of higher oxygen vacancy concentration is likely driven by their negative binding energy with oxygen vacancies Fe Ti / −V O •• in dimer and trimer defect clusters. 7 That we observe Fe metal and oxides via decomposition at significantly lower temperatures than Salles et al's CaTi 0.9 Fe 0.1 O 3−δ suggests that there is a balance between Surprisingly, on the surface of the perovskite grain, there is a ∼200 nm thick transition layer (outlined by white dashed lines in Figure 3a−e) with a decreasing concentration gradient of Ca and Ti and an increasing concentration gradient of Fe. Within the transition layer, there is a non-uniform distribution of Fe, with so-called "Fe-rich nanodomains" and "Fe-poor nanodomains" appearing bright and dark, respectively, in both Fe EDX maps (Figure 3c,g) and HAADF images (Figure 3a,f).…”

Lithium Battery Materials LiMPO4 (M = Mn, Fe, Co, and Ni): Insights into Defect Association, Transport Mechanisms, and Doping Behavior

“…As demonstrated by previous studies on complex oxides, , our simulation methods can model accurately the electrostatic, polarization, and elastic strain energies, which are the predominant terms in any local association process. The clusters considered comprised combinations of antisite defects, lithium vacancies, and hole species in the Li M PO 4 (M = Mn, Fe, Co, and Ni) systems.…”