Fast Screening of Biological and Food Samples Using Miniplatforms Based on 3D Stochastic Microsensors

Abstract A novel approach for the enantioanalysis of aspartic acid employing miniplatforms containing stochastic enantioselective sensors as detection tools was validated using food and biological samples. The 3D stochastic sensors were based on the modification with β-cyclodextrin of a functionalized copper oxide nanoparticles and spheroidal copper particles nanographene powder matrix. Stochastic method was used for all measurements. The sensors proposed demonstrated low limits of determination (1 × 10-18 mol L-1), high sensitivities (the highest being recorded for the spheroidal copper particles nanographene powder matrix based sensor: 1.59 × 1010 s-1 mol-1 L for L-aspartic acid, and 6.85 × 108 s-1 mol-1 L for D-aspartic acid), and wide linear concentration ranges (up to 12 decades of concentrations) for the enantioanalysis of aspartic acid. Student t-test values recorded were less than 3, when data obtained using both proposed sensors were compared, proving that it is no significative differences between the results obtained using the new designed sensors. Recovery values higher than 99.00% were recorded for the determination of the enantiomers of aspartic acid despite the ratio on which they are found in the synthetic mixtures.