This paper presents experimental evidence that thin (< approximately 200 nm) boron coatings, deposited with a (vacuum) cathodic arc technique on pre-polished Co-Cr-Mo surfaces, could potentially extend the life of metal-on-polymer orthopedic devices using cast Co-Cr-Mo alloy for the metal component. The primary tribological test used a linear, reciprocating pin-on-disc arrangement, with pins made of ultra-high molecular weight polyethylene. The disks were cast Co-Cr-Mo samples that were metallographically polished and then coated with boron at a substrate bias of 500 V and at about 100 degrees C. The wear tests were carried out in a saline solution to simulate the biological environment. The improvements were manifested by the absence of a detectable wear track scar on the coated metal component, while significant polymer transfer film was detected on the uncoated (control) samples tested under the same conditions. The polymer transfer track was characterized with both profilometry and Rutherford Backscattering Spectroscopy. Mechanical characterization of the thin films included nano-indentation, as well as additional pin-on-disk tests with a steel ball to demonstrate adhesion, using ultra-high frequency acoustic microscopy to probe for any void occurrence at the coating-substrate interface.
Federal rule changes governing natural gas pipelines have made non-destructive techniques, such as instrumented indentation testing (IIT), an attractive alternative to destructive tests for verifying properties of steel pipeline segments that lack traceable records. Ongoing work from Pacific Gas and Electric Company’s (PG&E) materials verification program indicates that IIT measurements may be enhanced by incorporating chemical composition data. This paper presents data from PG&E’s large-scale IIT program that demonstrates the predictive capabilities of IIT and chemical composition data, with particular emphasis given to differences between ultimate tensile strength (UTS) and yield strength (YS). For this study, over 80 segments of line pipe were evaluated through tensile testing, IIT, and compositional testing by optical emission spectroscopy (OES) and laboratory combustion. IIT measurements of UTS were, generally, in better agreement with destructive tensile data than YS and exhibited about half as much variability as YS measurements on the same sample. The root-mean squared error for IIT measurements of UTS and YS, respectively, were 27 MPa (3.9 ksi) and 43 MPa (6.2 ksi). Next, a machine learning model was trained to estimate YS and UTS by combining IIT with chemical composition data. The agreement between the model’s estimated UTS and tensile UTS values was only slightly better than the IIT-only measurements, with an RMSE of 21 MPa (3.1 ksi). However, the YS estimates showed much greater improvement with an improved RMSE of 27 MPa (3.9 ksi). The experimental, mechanical, and metallurgical factors that contributed to IIT’s ability to consistently determine destructive UTS, and the differences in its interaction with composition as compared to YS, are discussed herein.
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