Monitoring of nanodiamonds in human urine using artificial neural networks

Abstract

This paper presents the results of application of the elaborated methods for monitoring of nanodiamonds in human urine using fluorescence spectroscopy. High efficiency of artificial neural networks applied for recognition and estimation of the concentration of nanodiamonds in urine with a strong autofluorescence background is demonstrated. It was found that minimal concentration of nanodiamonds with strong fluorescence containing nitrogen‐vacancy (NV) centers can be detected in urine by fluorescence spectroscopy at a level of 3.06 × 10−4 g L−1; while use of artificial neural networks for detection of weakly fluorescent detonation nanodiamonds provides reasonably high accuracy of detection, not worse than 6.8 × 10−3 g L−1.