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Cited by 255

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

IC-Compatible Polysilicon Surface Micromachining

Sniegowski, J. J., de Boer, M. P.·2000·Annual Review of Materials Science

Abstract

▪ Abstract Polysilicon surface micromachining is advancing significantly and many new applications are moving beyond the prototyping phase. Recent technical successes are leading to excitement concerning various uses of devices in optical, wireless, sensor, and many other areas. Incorporation of state-of-the-art integrated circuit (IC) fabrication methods, such as planarization by chemical mechanical polishing (CMP), has enabled extension to a five-level technology. This has opened significant design space, especially for microactuator applications. Recent advancement of in situ microdiagnostics for materials and surface properties has enhanced our understanding of device reliability and performance and will allow devices to operate near well-known materials limits. New IC-compatible materials will further enhance the capabilities of microsystems in terms of performance, reliability, and operation in harsh environments.

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Crossref · 10.1146/annurev.matsci.30.1.299

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Metadata

Authors
Sniegowski, J. J., & de Boer, M. P.
Venue
Annual Review of Materials Science
Published
2000-08
Volume
30
Issue
1
Pages
299-333
ISSN
0084-6600 (ISSN-L)
OpenAlex
W2151380664
Cited by
255
References
24
FWCI
15.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: IC-Compatible Polysilicon Surface Micromachining. https://app.cochat.ai/papers/10.1146/annurev.matsci.30.1.299
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Sniegowski, J. J., & de Boer, M. P. (2000). IC-Compatible Polysilicon Surface Micromachining. Annual Review of Materials Science. https://doi.org/10.1146/annurev.matsci.30.1.299

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.