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Why Different Exposed Facets of SnO2 Nanomaterials Exhibit Different Performances in Electrochemical Detection of HMIs?
Author: YANG Meng
Update time: 2017-02-26
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Recently, some investigations have found that tin dioxide (SnO2) as a novel modified material can dramatically increase the currents and sensitivities during the electrochemical detection of heavy metal ions (HMIs). Unfortunately, researchers always simply attribute the enhanced electrochemical performance to the relatively large adsorption capacity of enlarged microscopic surface area. Although some experimental studies have been done, little concern has been paid to the understanding and exploration of the mechanism of the electroanalysis behavior from the viewpoint of crystal facets, in particular, the lack of first-principles theoretical studies at atomic level.

Aiming at this, a study team led by Prof. HUANG Xingjiu in Institute of Intelligent Machines (IIM), Hefei Institutes of Physical Science, managed to find out why different exposed facets of SnO2 nanomaterials exhibit different performances in electrochemical detection of HMIs, and the article was published in Analytical Chemistry. (http://pubs.acs.org/journal/ancham) 

In this work, through the electroanalysis studies from the three different shapes of octahedral, elongated dodecahedral and lance-shaped SnO2 nanoparticles, a novel exposed facet dependent electrochemical detection behavior are reported. The octahedral SnO2 nanoparticles are mainly composed of {221} facets, while the exposed surfaces of lance-shaped SnO2 nanoparticles are dominated with {110} facets. The sequence of sensitivity toward Pb(II) and Cd(II) is lance-shaped > elongated dodecahedral > octahedral SnO2 nanoparticles. The results demonstrate that SnO2 nanoparticles exposed by low-energy {110} facets show excellent sensing performance than those exposed by high-energy {221} facets towards HMIs.  

Meanwhile, researchers explored the reasons for the different electrochemical performance in depth by using density-functional theory (DFT) calculations and Xray absorption fine structure (XAFS) analyses, and these results indicated that SnO2 {110} facet possessed the lower diffusion energy and longer Pb−O bond length, which maed adsorbed HMIs more easily diffuse to the interface of electrode. Thus, the low-energy {110} facet of SnO2 showed excellent electrochemical performance in HMIs detection.  

Through detailed experimental and theoretical investigation, a reliable interpretation of the mechanism for electroanalysis of HMIs with nanomaterials exposed by different crystal facets has been provided. Also, it provides a deep insight into the understanding of the key factors to improve the electroanalysis performance in HMIs detection.

This work was supported by the National Natural Science Foundation of China (21377131, U1532123, 61474122, 21475133,21277146, and 61573334).

Figure 1. Electrochemical detection of HMIs and sensing mechanism studies. a), b) and c) Representative SEM images of the three different shapes of SnO2 nanoparticles. d) and e) Calibration plots of bare GCE, octahedral, elongated dodecahedral, and lance-shaped SnO2 nanoparticles modified GCE toward different concentrations of Pb(II) and Cd(II), respectively. f) and g) The transtion-state (TS) structure for Pb(II) on SnO2 {110} and {221} surface, respectively. h) and i) Pb LIII-XAFS spectra of Pb(II)-adsorbed octahedral, elongated dodecahedral and lance-shaped SnO2 nanoparticles, respectively. (Imaged by YANG Meng)

Article link: http://pubs.acs.org/doi/abs/10.1021/acs.analchem.6b04977

Title: Tin Oxide Crystals Exposed by Low-Energy {110} Facets for Enhanced Electrochemical Heavy Metal Ions Sensing: X-ray Absorption Fine Structure Experimental Combined with Density-Functional Theory Evidence

Key words: Tin oxide; {110} facet; Electrochemical sensing; XAFS and DFT

Prof. HUANG Xing-Jiu, Ph. D Principal Investigator

Institute of Intelligent Machines, Chinese Academy of Sciences (http://www.iim.cas.cn/) Hefei, Anhui 230000, China

Tel: 86-551-6559-1167

Email: xingjiuhuang@iim.ac.cn

 

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