3 research outputs found

    Computational modelling of A2BO4 materials for solid oxide fuel cells

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    Solid oxide fuel cells are a clean, attractive and highly efficient alternative to traditional methods of power generation. However, their high operating temperature prevents their widespread use, as it makes them prohibitively expensive and causes stability issues. In response to this, new materials which exhibit fast oxide ion conduction at low-intermediate temperatures have gained considerable research interest. In this thesis, atomic scale computational modelling techniques have been employed to investigate defects, dopants and oxide ion conductivity in the A2BO4 materials; Cd2GeO4 and Ba2TiO4. Calculations suggest that these materials' parent structures are poor oxide ion conductors due to their highly unfavourable intrinsic defect formation energies of 3.00-10.56 eV defect-1. Results also indicate that oxide ion interstitials can be formed in Cd2GeO4through trivalent doping of the Cd sites. In Ba2TiO4, monovalent and trivalent doping of its Ba and Ti sites respectively induces the formation of oxide ion vacancies. In both materials, strong dopant-oxide ion defect associations are present. Interestingly, only Cd2GeO4 shows enhanced oxide ion migration upon doping, the defects in Ba2TiO4 being effectively immobile. This suggest that the oxide ion vacancies are more intensely associated with their causal dopant ions. With an average migration barrier of ~0.79 eV, oxide ions diffuse in Cd2GeO4 via a “knock-on” mechanism down the a-axis and a stepwise mechanism along the c-axis. Despite this, defect trapping confines the interstitials to the dopant rich regions of the cell, resulting in poor oxide ion diffusion on the order of 1x10-8 cm2 s-1 at 1273 K. Generally, defects are found to be more stable in the α’-phase of Ba2TiO4, suggesting, in agreement with experiment, that they are likely to stabilise the α’-phase at reduced temperatures. Subsequent investigations, also in accord with experiment, reveal carbonate impurities are likely to be common in pristine and doped Ba2TiO4 systems alike, and that their presence will stabilise the α’-phase. The hydroxide type defects formed upon water incorporation are shown to be low in energy in Ba2TiO4 systems containing oxide ion vacancies or interstitials. Both carbonate and hydroxide type defects are shown to bind aggressively to any oxide ion defects present, reducing their mobility

    A computational study of doped olivine structured Cd2GeO4: local defect trapping of interstitial oxide ions

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    Computational modelling techniques have been employed to investigate defects and ionic conductivity in Cd2GeO4. We show due to highly unfavourable intrinsic defect formation energies the ionic conducting ability of pristine Cd2GeO4 is extremely limited. The modelling results suggest trivalent doping on the Cd site as a viable means of promoting the formation of the oxygen interstitial defects. However, the defect cluster calculations for the first time explicitly suggest a strong association of the oxide defects to the dopant cations and tetrahedral units. Defect clustering is a complicated phenomenon and therefore not trivial to assess. In this study the trapping energies are explicitly quantified. The trends are further confirmed by molecular dynamic simulations. Despite this, the calculated diffusion coefficients do suggest an enhanced oxide ion mobility in the doped system compared to the pristine Cd2GeO4

    Structure and ion transport of lithium-rich Li1+xAlxTi2−x(PO4)3 with 0.3

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    © 2020 Elsevier B.V. New solid state electrolytes are becoming increasingly sought after in the drive to replace flammable liquid electrolytes. To this end, several Li conducting solids have been identified as promising candidates including Li stuffed garnets and more recently Li-rich materials such as Li1+xAlxTi2−x(PO4)3 with 0.3Ti4+ compared to Li+–>Al3+. Furthermore, our calculated ionic conductivities are in excellent agreement with experimental values, highlighting the robustness of our computational models
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