Selective determination of aromatic amino acids by magnetic hydroxylated MWCNTs and MOFs based composite

- An efficient MSPE-HPLC-UV method was established for AAAs determination.
- An explored composite of MOFs and magnetic CNTs was employed for the MSPE of AAAs.
- The MSPE mechanisms were attributed to multiple hydrogen bonding and π-π EDA interactions.
- The proposed method was evaluated by MSPE of Trp, Tyr and Phe from Lanzhou lily samples.

A novel magnetic solid-phase extraction (MSPE) based method was established for aromatic amino acids (AAAs) selective determination. Central to the method was the adopted extractant. An explored composite of metal organic frameworks (MOFs) and magnetic carbon nanotubes (CNTs) was employed for that, which exhibited superior adsorption affinity and selectivity to AAAs as compared to other amino acids with the mechanisms attributed to multiple hydrogen bonding and π-π electron-donor-acceptor (EDA) interactions. The morphology, structure and magnetic behavior of the composite were characterized and related MSPE procedure was established. Critical extraction conditions including pH, extraction time, temperature and salt addition were investigated and optimized. Subsequently the concentrations of three AAAs tryptophan (Trp), tyrosine (Tyr) and phenylalanine (Phe) in Lanzhou lily were determined by the composite based MSPE procedure coupled with high performance liquid chromatography-ultraviolet detection (HPLC-UV). The composite provided a superior sample clean-up function and many of the matrix interferences were eliminated, thus ensured AAAs were accurately and efficiently determined. The results showed that the method had good linearities with the linear coefficients above 0.99, desirable recoveries ranged from 88.0% to 96.8% with the RSD less than 5.1%, satisfactory precision and low limits of detection (LODs) which were respectively 0.04, 0.11, and 0.87 ng/g for Trp, Tyr and Phe. The composite based MSPE-HPLC-UV method has great potentials for the AAAs selective determination from complex matrix samples.