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Network-Structured BST/MBO Composites Made from Core-Shell-Structured Granulates

Häuser, Kevin ; Zhou, Zhiren ; Agrawal, Prannoy ; Jakoby, Rolf ; Maune, Holger ; Binder, Joachim R. (2023)
Network-Structured BST/MBO Composites Made from Core-Shell-Structured Granulates.
In: Materials, 2023, 16 (2)
doi: 10.26083/tuprints-00023272
Artikel, Zweitveröffentlichung, Verlagsversion

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Kurzbeschreibung (Abstract)

A finite element method (FEM)-based simulation approach to predict the tunability in composite materials was developed and tested with analytical data. These tests showed good prediction capabilities of the simulation for the test data. The simulation model was then used to predict the tunability of a network-structured composite, where the dielectric phase formed clusters in a paraelectric network. This was achieved by simulating a reciprocal core-shell unit cell of said network. The simulation showed a high tunability for this network model, exceeding the tunability of the analytically evaluated layered, columnar, and particulate model. The simulation results were experimentally verified with a Ba₀.₆Sr₀.₄TiO₃/Mg₃B₂O₆ (BST/MBO) composite, where core-shell granulates were made with a two-step granulation process. These structured samples showed higher tunability and dielectric loss than the unstructured samples made for comparison. Overall, the structured samples showed higher tunability to loss ratios, indicating their potential for use in tunable radio frequency applications, since they may combine high performance with little energy loss.

Typ des Eintrags: Artikel
Erschienen: 2023
Autor(en): Häuser, Kevin ; Zhou, Zhiren ; Agrawal, Prannoy ; Jakoby, Rolf ; Maune, Holger ; Binder, Joachim R.
Art des Eintrags: Zweitveröffentlichung
Titel: Network-Structured BST/MBO Composites Made from Core-Shell-Structured Granulates
Sprache: Englisch
Publikationsjahr: 2023
Ort: Darmstadt
Publikationsdatum der Erstveröffentlichung: 2023
Verlag: MDPI
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Materials
Jahrgang/Volume einer Zeitschrift: 16
(Heft-)Nummer: 2
Kollation: 16 Seiten
DOI: 10.26083/tuprints-00023272
URL / URN: https://tuprints.ulb.tu-darmstadt.de/23272
Zugehörige Links:
Herkunft: Zweitveröffentlichung DeepGreen
Kurzbeschreibung (Abstract):

A finite element method (FEM)-based simulation approach to predict the tunability in composite materials was developed and tested with analytical data. These tests showed good prediction capabilities of the simulation for the test data. The simulation model was then used to predict the tunability of a network-structured composite, where the dielectric phase formed clusters in a paraelectric network. This was achieved by simulating a reciprocal core-shell unit cell of said network. The simulation showed a high tunability for this network model, exceeding the tunability of the analytically evaluated layered, columnar, and particulate model. The simulation results were experimentally verified with a Ba₀.₆Sr₀.₄TiO₃/Mg₃B₂O₆ (BST/MBO) composite, where core-shell granulates were made with a two-step granulation process. These structured samples showed higher tunability and dielectric loss than the unstructured samples made for comparison. Overall, the structured samples showed higher tunability to loss ratios, indicating their potential for use in tunable radio frequency applications, since they may combine high performance with little energy loss.

Freie Schlagworte: ceramic composite, FEM, tunability, dielectric behavior
Status: Verlagsversion
URN: urn:nbn:de:tuda-tuprints-232725
Zusätzliche Informationen:

This article belongs to the Special Issue Advances in Synthesis and Characterization of Dielectric Ceramics

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau
Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Mikrowellentechnik und Photonik (IMP)
Hinterlegungsdatum: 24 Feb 2023 09:55
Letzte Änderung: 27 Feb 2023 15:28
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