The influence of grain boundary area on the complexion time-temperature-transformation diagram of Eu-doped magnesium aluminate spinel

Krause, Amanda R.; Kundu, Animesh; Kosasang, Onthida; Vinci, Richard P.; Harmer, Martin P.

doi:10.1016/j.scriptamat.2019.11.041

Cited by 11 publications

(14 citation statements)

References 20 publications

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“…More detailed doping and sintering procedures are provided elsewhere. 13 Four specific combinations of doping concentration and annealing times were evaluated: 100 ppm-2 h, 100 ppm-8 h, 500 ppm-0 h, and 500 ppm-2 h. These processing conditions were investigated to compare the grain boundary complexions that exist before (100 ppm-2 h and 500 ppm-0 h) and after (100 ppm-8 h and 500 ppm-2 h) the complexion TTT start curves for each bulk doping concentration based on Figure 1. All annealed samples were polished to facilitate electron microscopy characterization.…”

Section: Methodsmentioning

confidence: 99%

“…Eu-rich secondary phase precipitation was not observed in any of the bulk specimens, so it is hereafter assumed all the Eu dissolved in the MgAl 2 O 4 matrix and segregated to grain boundaries. Eu excess coverages were estimated based on the grain size measurements using Equation (1) 13 :…”

Section: Bulk Microstructurementioning

confidence: 99%

“…Therefore, they proposed a model that considers doping concentration, average grain size, and area fraction of abnormal grains to predict excess grain boundary coverage and thus relate the complexions found in the 500 ppm and 100 ppm samples. 13 The model revealed that the grain boundary excess coverages were indeed similar at the onset of abnormal grain growth despite differences in doping concentration, grain size, and the heat treatment time. They concluded that complexion transitions and, thus, abnormal grain growth can be predicted from grain boundary coverage excess values rather than bulk composition.…”

mentioning

confidence: 93%

“…In the early stages of GBCE, equilibrium complexion diagrams, analogous to bulk phase diagrams, were developed to predict the temperatures, compositions, and/or pressures where specific complexions are stable 8‐10 . Complexion time‐temperature‐transformation (TTT) diagrams, analogous to TTT diagrams used for steel processing, have been more recently developed to capture the dynamic behavior or kinetics of complexion transformations 11‐13 …”

Section: Introductionmentioning

confidence: 99%

“…[8][9][10] Complexion time-temperaturetransformation (TTT) diagrams, analogous to TTT diagrams used for steel processing, have been more recently developed to capture the dynamic behavior or kinetics of complexion transformations. [11][12][13] The most complete complexion TTT diagrams have been experimentally created using Eu-doped MgAl 2 O 4 . An initial study by Schumacher et al used abnormal grain growth as a proxy for a complexion transition to construct a complexion TTT diagram for 500 ppm Eu-doped MgAl 2 O 4 .…”

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confidence: 99%

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Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

2021

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Grain boundaries exhibit "phase"-like behaviors in that they transform in structure and/or composition with concurrent changes in chemical potential and temperature. [1][2][3] Grain boundary transformations include structural transformations from planar to faceted grain boundaries, compositional transformations from pure to enriched grain boundaries, and finally, structural and compositional transformations from clean grain boundaries to ordered or disordered nanolayers. 4 The equilibrium structure and composition of a grain boundary have been coined a complexion. 5 The realization that grain boundaries have equilibrium states and transition has inspired the field of study termed grain boundary complexion engineering (GBCE). 6 GBCE exploits grain boundary complexion transitions to induce sudden changes in grain boundary properties (e.g., grain boundary mobility) as well as bulk material properties (e.g., toughness) and behavior (e.g., grain growth). 7 In general, tools are needed to predict and guide complexion

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Section: Methodsmentioning

confidence: 99%

Section: Bulk Microstructurementioning

confidence: 99%

mentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

2021

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Machine Learning‐Driven Biomaterials Evolution

et al. 2021

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Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been hampered by the relatively long development period required. In recent years, driven by the need to accelerate materials development, the applications of machine learning in materials science has progressed in leaps and bounds. The combination of machine learning with high‐throughput theoretical predictions and high‐throughput experiments (HTE) has shifted the traditional Edisonian (trial and error) paradigm to a data‐driven paradigm. In this review, each type of biomaterial and their key properties and use cases are systematically discussed, followed by how machine learning can be applied in the development and design process. The discussions are classified according to various types of materials used including polymers, metals, ceramics, and nanomaterials, and implants using additive manufacturing. Last, the current gaps and potential of machine learning to further aid biomaterials discovery and application are also discussed.

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Novel yellowish‐green single‐phased spinel Mg_1−xBa_xAl₂O₄:Mn²⁺ phosphor(s) for color rendering white‐light‐emitting diodes

Ain,

Fazal,

Iqbal

et al. 2024

Luminescence

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For white light‐rendering research activities, interpretation by using colored emitting materials is an alternative approach. But there are issues in designing the white color emitting materials. Particularly, differences in thermal and decay properties of discrete red, green, and blue emitting materials led to the quest for the search of a single‐phased material, able to emit primary colors for white light generation. The current study is an effort to design a simple, single‐phase, and cost‐effective material with the tunable emission of primary colors by a series of Mg1−xBaxAl2O4:Mn2+ nanopowders. Doping of manganese ion (Mn2+) in the presence of the larger barium cation (Ba2+) at tetrahedral‐sites of the spinel magnesium aluminate (MgAl2O4) structure led to the creation of antisite defects. Doped samples were found to have lower bandgaps compared with MgAl2O4, and hybridization of 3d‐orbitals of Mn2+ with O(2p), Mg(2s)/Al(2s3p) was found to be responsible for narrowing the bandgap. The distribution of cations at various sites at random results in a variety of electronic transitions between the valance band and oxygen vacancies as well as electron traps produced the antisite defects. The suggested compositions might be used in white light applications since they have three emission bands with centers at 516 nm (green), 464 nm (blue) and 622 nm (red) at an excitation wavelength of 380 nm. A detailed discussion to analyze the effects of the larger cationic radius of Ba2+ on the lattice strain, unit cell parameters, and cell volumes using X‐ray diffraction analysis is presented.

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The influence of grain boundary area on the complexion time-temperature-transformation diagram of Eu-doped magnesium aluminate spinel

Cited by 11 publications

References 20 publications

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

Machine Learning‐Driven Biomaterials Evolution

Novel yellowish‐green single‐phased spinel Mg_1−xBa_xAl₂O₄:Mn²⁺ phosphor(s) for color rendering white‐light‐emitting diodes

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The influence of grain boundary area on the complexion time-temperature-transformation diagram of Eu-doped magnesium aluminate spinel

Cited by 11 publications

References 20 publications

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl2O4

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl2O4

Machine Learning‐Driven Biomaterials Evolution

Novel yellowish‐green single‐phased spinel Mg1−xBaxAl2O4:Mn2+ phosphor(s) for color rendering white‐light‐emitting diodes

Contact Info

Product

Resources

About

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

Effect of Eu‐doping and grain boundary plane on complexion transitions in MgAl₂O₄

Novel yellowish‐green single‐phased spinel Mg_1−xBa_xAl₂O₄:Mn²⁺ phosphor(s) for color rendering white‐light‐emitting diodes