Raman spectroscopy of biomedical polyethylenes

Publication date: Available online 27 March 2017
Source:Acta Biomaterialia
Author(s): Giuseppe Pezzotti
With the development of three-dimensional Raman algorithms for local mapping of oxidation and plastic strain, and the ability to resolve molecular orientation patterns with microscopic spatial resolution, there is an opportunity to re-examine many of the foundations on which our understanding of biomedical grade ultra-high molecular weight polyethylenes (UHMWPEs) are based. By implementing polarized Raman spectroscopy into an automatized tool with an improved precision in non-destructively resolving Euler angles, oxidation levels, and microscopic strain, we become capable to make accurate and traceable measurements of the in vitro and in vivo tribological responses of a variety of commercially available UHMWPE bearings for artificial hip and knee joints. In this paper, we first review the foundations and the main algorithms for Raman analyses of oxidation and strain of biomedical polyethylene. Then, we critically re-examine a large body of Raman data previously collected on different polyethylene joint components after in vitro testing or in vivo service, in order to shed new light on an area of particular importance to joint orthopedics: the microscopic nature of UHMWPE surface degradation in the human body. A complex scenario of physical chemistry appears from the Raman analyses, which highlights the importance of molecular-scale phenomena besides mere microstructural changes. The availability of the Raman microscopic probe for visualizing oxidation patterns unveiled striking findings related to the chemical contribution to wear degradation: chain-breaking and subsequent formation of carboxylic acid sites preferentially occur in correspondence of third-phase regions, and they are triggered by emission of dehydroxylated oxygen from ceramic oxide counterparts. These findings profoundly differ from more popular (and simplistic) notions of mechanistic tribology adopted in analyzing joint simulator data.

Graphical abstract

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