Recent Progress in Morphology-Tuned Nanomaterials for the Electrochemical Detection of Heavy Metals

Heavy metals are one of the most important classes of environmental pollutants which are toxic to living beings. Many efforts are made by scientists to fabricate better sensors for the identification and quantification of heavy metal ions (HMI) in water and food samples to ensure good health. Electr...

Full description

Saved in:
Bibliographic Details
Published in:Nanomaterials (Basel, Switzerland) Switzerland), 2022-11, Vol.12 (22), p.3930
Main Authors: Gibi, Chinchu, Liu, Cheng-Hua, Barton, Scott C, Wu, Jerry J
Format: Article
Language:English
Subjects:
Alzheimer's disease
Analysis
Chemical sensors
dimensions
Electrocatalysts
Electrochemical analysis
electrochemical sensors
Electrochemistry
Enzymes
Graphene
Heavy metals
Metal ions
Metals
Methods
Morphology
Nanomaterials
Nanoparticles
Nanostructured materials
Nanotechnology
Pollutants
Properties
Quantum dots
Review
Selectivity
Sensitivity enhancement
Sensors
Voltammetry
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Heavy metals are one of the most important classes of environmental pollutants which are toxic to living beings. Many efforts are made by scientists to fabricate better sensors for the identification and quantification of heavy metal ions (HMI) in water and food samples to ensure good health. Electrocatalysts have been demonstrated to play an important role in enhancing the sensitivity and selectivity of HMI detection in electrochemical sensors. In this review, we presented morphologically well-tuned nanomaterials used as efficient sensor materials. Based on the molecular dimensions, shapes, and orientation, nanomaterials can be classified into 0-D, 1-D, 2-D, and 3-D nanomaterials. Active surface areas with significant exposure of active sites and adsorption-desorption abilities are extensively varied with dimensionality, which in turn ultimately influence the sensing performance for HMI.
ISSN:2079-4991
2079-4991
DOI:10.3390/nano12223930