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Cited by 454

The DOI matches its Crossref record; 110 of the 110 references it cites were found in a registry or an index.

Next generation ferroelectric materials for semiconductor process integration and their applications

Open access
Mikolajick, T., Slesazeck, S., Mulaosmanovic, H., Park, M. H., Fichtner, S., Lomenzo, P. D., Hoffmann, M., Schroeder, U.·2021·Journal of Applied Physics

Abstract

Ferroelectrics are a class of materials that possess a variety of interactions between electrical, mechanical, and thermal properties that have enabled a wealth of functionalities. To realize integrated systems, the integration of these functionalities into semiconductor processes is necessary. To this end, the complexity of well-known ferroelectric materials, e.g., the perovskite class, causes severe issues that limit its applications in integrated systems. The discovery of ferroelectricity in hafnium oxide-based materials brought a renewed interest into this field during the last decade. Very recently, ferroelectricity was also verified in aluminum scandium nitride extending the potential of seeing a wealth of ferroelectric functions in integrated electronics in the future. This paper discusses the prospects of both material systems in various applications.

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Crossref · 10.1063/5.0037617

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Metadata

Authors
Mikolajick, T., Slesazeck, S., Mulaosmanovic, H., Park, M. H., Fichtner, S., Lomenzo, P. D., Hoffmann, M., & Schroeder, U.
Venue
Journal of Applied Physics
Published
2021-03-11
Volume
129
Issue
10
ISSN
  • 0021-8979 (ISSN-L)
  • 1089-7550
OpenAlex
W3133940875
Cited by
454
References
110
FWCI
19.87
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Next generation ferroelectric materials for semiconductor process integration and their applications. https://app.cochat.ai/papers/10.1063/5.0037617
The paper
Mikolajick, T., Slesazeck, S., Mulaosmanovic, H., Park, M. H., Fichtner, S., Lomenzo, P. D., Hoffmann, M., & Schroeder, U. (2021). Next generation ferroelectric materials for semiconductor process integration and their applications. Journal of Applied Physics. https://doi.org/10.1063/5.0037617

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.