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Shape Memory and Superelasticity
Erschienen in: Shape Memory and Superelasticity 4/2023

25.07.2023 | ORIGINAL RESEARCH ARTICLE

Shape Memory Materials Analysis and Research Tool (SM2ART): Finding Data Anomalies and Trends

verfasst von: P. E. Caltagirone, O. Benafan

Erschienen in: Shape Memory and Superelasticity | Ausgabe 4/2023

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Abstract

Typically, the first step in alloy selection and material production is to use handbooks, databases, or other materials guides to down-select to a specific composition and processing method for the desired application. This is true for conventional materials, such as steels, aluminums, and polymers, but until recently, no similar data source existed for shape memory materials (SMMs). There is no shortage of information in the SMM field; with over 90 years of research in the form of peer-reviewed articles, papers, and published data from companies; however, these data have not been accessible in a single location. This has posed many difficulties for the research and development of SMMs and has caused the field to move slowly. To remedy this, a web-based comprehensive repository known as the Shape Memory Materials Analysis and Research Tool (SM2ART) database has been developed. SM2ART provides unrestricted access to data from thousands of peer-reviewed articles and published data. These data are organized in a 2D and 3D visualization platform and provides viewers insight into shape memory alloys (SMAs), superelastic alloys, magnetic alloys, shape memory polymers (SMPs), and shape memory ceramics (SMCs). The work presented here provides a summary of the data available within the SM2ART database.
Vorheriger Artikel Novel C-Shaped Shape Memory Alloy Connectors for Vacuum Flanges: Modeling and Tests
Nächster Artikel Inhibition of Localized Corrosion of Ni–Ti Superelastic Alloy in Sodium Hypochlorite Solution by Sodium Carbonate Addition
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Metadaten
Titel
Shape Memory Materials Analysis and Research Tool (SM2ART): Finding Data Anomalies and Trends
verfasst von
P. E. Caltagirone
O. Benafan
Publikationsdatum
25.07.2023
Verlag
Springer US
Erschienen in
Shape Memory and Superelasticity / Ausgabe 4/2023
Print ISSN: 2199-384X
Elektronische ISSN: 2199-3858
DOI
https://doi.org/10.1007/s40830-023-00457-7

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