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Microwave characterization of two Ba_(0.6)Sr_(0.4)TiO_(3) dielectric thin films with out-of-plane and in-plane electrode structures

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先进陶瓷(英文) 2023年第8期12卷 1521-1532页

作者： Hanchi Ruan Theo Graves Saunders Henry Giddens Hangfeng Zhang achintha avin ihalage Jonas Florentin Kolb Matthew Blunt Sajad Haq Haixue Yan Yang Hao School of Electronic Engineering and Computer Science Queen Mary University of LondonLondon E14NSUK School of Engineering and Materials Science Queen Mary University of LondonLondon E14NSUK Department of Chemistry University College LondonLondon WC1H 0AJUK Advanced Services and Products QinetiQFarnborough GU140LXUK

Ferroelectric(FE)thin films have recently attracted renewed interest in research due to their great potential for designing novel tunable electromagnetic devices such as large intelligent surfaces(LISs).However,the mechanism of how a polar structure in the FE thin films contributes to desired tunable performance,especially within the microwave frequency range,which is the most widely used frequency range of electromagnetics,has not been illustrated *** this paper,we described several straightforward and cost-effective methods to fabricate and characterize Ba_(0.6)Sr_(0.4)TiO_(3)(BST)thin films at microwave *** prepared BST thin films here exhibit homogenous structures and great tunability(h)in a wide frequency and temperature range when the applied field is in the out-of-plane *** high tunability can be attributed to high concentration of polar *** response to the applied direct current(DC)field was directly visualized using a novel non-destructive near-field scanning microwave microscopy(NSMM)*** results have provided some intriguing insights into the application of the FE thin films for future programmable high-frequency devices and systems.

关键词： ferroelectric(FE) microwave tunability polarization thin film

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Analogical discovery of disordered perovskite oxides by crystal structure information hidden in unsupervised material fingerprints

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npj Computational Materials 2021年第1期7卷 659-670页

作者： achintha ihalage Yang Hao School of Electronic Engineering and Computer Science Queen Mary University of LondonLondonUK

Compositional disorder induces myriad captivating phenomena in ***-driven discovery of perovskite solid solutions has been a great challenge due to the analytical complexity introduced by ***,we demonstrate that an unsupervised deep learning strategy can find fingerprints of disordered materials that embed perovskite formability and underlying crystal structure information by learning only from the chemical composition,manifested in (A_(1-x)A'_(x))BO_(3) and A(B_(1-x)B'_(x))O_(3) *** phenomenon can be capitalized to predict the crystal symmetry of experimental compositions,outperforming several supervised machine learning(ML)*** educated nature of material fingerprints has led to the conception of analogical materials discovery that facilitates inverse exploration of promising perovskites based on similarity investigation with known *** search space of unstudied perovskites is screened from~600,000 feasible compounds using experimental data powered ML models and automated web mining tools at a 94%success *** concept further provides insights on possible phase transitions and computational modelling of complex *** proposed quantitative analysis of materials analogies is expected to bridge the gap between the existing materials literature and the undiscovered terrain.

关键词： perovskite crystal disordered

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