Multivariate calibration strategies for the simultaneous quantification of aluminium and vanadium in Ti6Al4V alloys

Abstract

The detection of wear tribocorrosion residues released from orthopaedic implants, such as aluminium and vanadium liberated from Ti6Al4V alloys, is essential to assess their clinical performance. In this work, for the first time to our knowledge, a simple, effective, pre-treatment-free and low-cost methodology for the simultaneous detection of aluminium and vanadium in biological matrices is developed. Both metals, present in a simulated body fluid matrix, form a complex with quercetin, which present overlapping UV–Vis spectra. To overcome this problem, we analyse and compare different chemometric tools, including Partial Least-Squares (PLS), interval Successive Projections Algorithm coupled with Partial Least Squares (iSPA-PLS) and Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). iSPA-PLS provided the best results for the determination of aluminium and vanadium, using pre-processed data with baseline correction offset. For vanadium, the best performance resulted in ratio performance to deviation for prediction (RPDPred) values of 7.9847, detection limit (LoD) of 0.4725 ppm, quantification limit (LoQ) of 1.4318 ppm, and REP of 4.9708 employing two sets of 20 total intervals, while for aluminium, the best performance resulted in RPDPred values of 3.8331, LoD of 0.2111 ppm, LoQ of 0.6398 ppm, and relative error of prediction (REP) of 10.3546 employing three sets of 23 total intervals. Additionally, the methodology was employed in the detection of aluminium and vanadium residues released from 1 mm thick, 10 mm diameter Ti6Al4V alloy discs in Hank's Solution (simulated biological fluid), detecting residues after twelve weeks of immersion.