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Cited by 2,529

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

The metallurgy and processing science of metal additive manufacturing

Sames, W. J., List, F. A., Pannala, S., Dehoff, R. R., Babu, S. S.·2016·International Materials Reviews

Abstract

Additive manufacturing (AM), widely known as 3D printing, is a method of manufacturing that forms parts from powder, wire or sheets in a process that proceeds layer by layer. Many techniques (using many different names) have been developed to accomplish this via melting or solid-state joining. In this review, these techniques for producing metal parts are explored, with a focus on the science of metal AM: processing defects, heat transfer, solidification, solid-state precipitation, mechanical properties and post-processing metallurgy. The various metal AM techniques are compared, with analysis of the strengths and limitations of each. Only a few alloys have been developed for commercial production, but recent efforts are presented as a path for the ongoing development of new materials for AM processes.

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Metadata

Authors
Sames, W. J., List, F. A., Pannala, S., Dehoff, R. R., & Babu, S. S.
Venue
International Materials Reviews
Published
2016-03-07
Volume
61
Issue
5
Pages
315-360
ISSN
  • 0950-6608 (ISSN-L)
  • 1743-2804
OpenAlex
W2324464036
Cited by
2,529
References
2
FWCI
167.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The metallurgy and processing science of metal additive manufacturing. https://app.cochat.ai/papers/10.1080/09506608.2015.1116649
The paper
Sames, W. J., List, F. A., Pannala, S., Dehoff, R. R., & Babu, S. S. (2016). The metallurgy and processing science of metal additive manufacturing. International Materials Reviews. https://doi.org/10.1080/09506608.2015.1116649

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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.