Abstract
While multidimensional sensors are powerful platforms towards
multitarget analyses, the successive synthesis/fabrication of multiple
probes and measurements to each one of these units still damage the
device miniaturization, scalability, cost, consumption of samples,
operational simplicity, precision, and analysis time. Herein, we
describe an electrochemical sensing array that affords the
discrimination of metal ions from a single ready-to-use probe and
experiment. The sensing probe consisted of commercial stainless-steel
capillaries, which defined a microfluidic circuit and acted as electric
double-layer parallel capacitors into devices prototyped by a fast,
cleanroom-free, and green technique. The probes assured differential
responses due to heterogeneous interactions with samples and
multichannel capacitance outputs. In addition, we address an effective
strategy to further improve the repeatability and recognition ability of
the sensor by using oxidized multi-walled carbon nanotubes as a single
bulk probe. The nanotubes provided differential electrostatic
adsorptions of ions, then increasing the variance of the capacitance
responses. The approach was successfully applied in the identification
of samples of mineral water, lake, and petroleum according to the
presence of metal ions. Using supervised machine learning tasks, the
sensor assured reproducible, sensitive, and accurate classification of
dozens of lake samples spiked with multiple heavy metals in accordance
with their safe limits. Remarkably, simultaneous quantification of the
individual concentration of these ions was also possible from universal
impedimetric assays by treating the data through multi-output
regression. The sensor will be of significance for advanced
discriminations from a single ordinary probe and measurement in a direct
mode using scalable chips.
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