Detection and Direct Readout of Drugs in Human Urine Using Dynamic Surface-Enhanced Raman Spectroscopy and Support Vector Machines

Abstract

A new, novel, rapid method to detect and direct readout of drugs in human urine has been developed using dynamic surface-enhanced Raman spectroscopy (D-SERS) with portable Raman spectrometer on gold nanorods (GNRs) and a classification algorithm called support vector machines (SVM). The high-performance GNRs can generate gigantic enhancement and the SERS signals obtained using D-SERS on it have high reproducibility. On the basis of this feature of D-SERS, we have obtained SERS spectra of urine and urine containing methamphetamine (MAMP). SVM model was built using these data for fast identified and visual results. This general method was successfully applied to the detection of 3, 4-methylenedioxy methamphetamine (MDMA) in human urine. To verify the accuracy of the model, drug addicts' urine containing MAMP were detected and identified correctly and rapidly with accuracy more than 90%. The detection results were displayed directly without analysis of their SERS spectra manually. Compared with the conventional method in lab, the method only needs a 2 μL sample volume and takes no more than 2 min on the portable Raman spectrometer. It is anticipated that this method will enable rapid, convenient detection of drugs on site for the police.