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Viewpoint - Understanding Mg corrosion in the body for biodegradable medical implants
Abstract
Abstract Accurate prediction of Mg corrosion rates within the body (in vivo) based on laboratory tests (in vitro) is a key challenge for Mg alloys in medical applications. Estimates based on in vitro measurements overestimate the measured Mg corrosion rate in vivo. This indicates that the medical environment and the biocorrosion mechanism is not fully characterised. We summarise (i) the relevant Mg metallurgy, and (ii) the solution factors that influence Mg corrosion in vitro. We analyse the reasons for the disparity between the corrosion rates in vivo and the expected corrosion rates based on in vitro testing, and suggest promising areas of research.
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Cited by
A review on magnesium alloys for biomedical applications
Zhang, T., Wang, W., Liu, J., Wang, L., Tang, Y., & Wang, K. (2022) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2022.953344 · Cited by 208
Wang, Z., Liu, B., Yin, B., Zheng, Y., Tian, Y., & Wen, P. (2022) · Frontiers in Chemistry · doi:10.3389/fchem.2022.1066103 · Cited by 30
“The mechanical properties of L-PBF components can be significantly improved by mixing nanoparticles with metals (Atrens et al., 2018).”
Background
Metadata
- Authors
- Atrens, A., Johnston, S., Shi, Z., & Dargusch, M. S.
- Venue
- Scripta Materialia
- Publisher
- Elsevier BV
- Published
- 2018-09
- Volume
- 154
- Pages
- 92-100
- ISSN
- 1359-6462 (ISSN-L)
- OpenAlex
- W2806075725
- Cited by
- 203
- References
- 0
- FWCI
- 8.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Viewpoint - Understanding Mg corrosion in the body for biodegradable medical implants. https://app.cochat.ai/papers/10.1016/j.scriptamat.2018.05.021
- The paper
- Atrens, A., Johnston, S., Shi, Z., & Dargusch, M. S. (2018). Viewpoint - Understanding Mg corrosion in the body for biodegradable medical implants. Scripta Materialia. https://doi.org/10.1016/j.scriptamat.2018.05.021
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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.
