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Research Article

Adsorption and oxidation of arsenic by ultra-long α-MnO2 nanowires with the (1 1 0) surface

, , , , , , , , & show all
Received 11 Aug 2016, Accepted 16 Jan 2017, Published online: 31 Jul 2022
 

Abstract

There are many areas in the world where ground water has been contaminated by arsenic. MnO2 is one of the most inexpensive materials which can both adsorb arsenic and oxide arsenite [As(III)] to arsenate [As(V)]. In this study, the Ultra-long α-MnO2 nanowires with the (1 1 0) surface are used to remove As(III) and As(V) from solutions under different conditions. The adsorption kinetics for both As(III) and As(V) fit well with the pseudo-second-order kinetic model. For example, the pseudo-second-order adsorption kinetic constants are 0.076 × 103 and 0.077 × 103 g μg−1 min−1 at pH 7 for As(III) and As(V), respectively. At the same time, compared to the Freundlich model the Langmuir model better describes the adsorption equilibrium isotherms. For example, the maximum adsorption capacity values of the α-MnO2 nanowires obtained from the Langmuir model are 1.012 × 103 and 1.158 × 103 μg g−1 at pH 7 for As(III) and As(V), respectively. The adsorption capacities of α-MnO2 nanowires are affected by the pH value and increase with the initial arsenic concentration. Furthermore, the As(III) oxidation rate can be denoted by the pseudo-zero-order kinetic model and is related to O2 concentration, the light source used, the initial concentration of As(III), and the pH value. For example, the pseudo-zero-order kinetic equation is y = −0.90x + 163.6 with 4 L min−1 of O2, dark condition, 0.2 × 103 μg L−1 of As(III) and at pH 7. Finally, the oxidation mechanism is investigated and the oxidant in this reaction should be related with O2 not Mn(II). Besides its special structure and easy separation ability, it is a promising material to remove arsenic from water.

Additional information

Funding

This work is supported by the National Natural Science Foundation of China (20803014, 21173022, 21373104), the Guangdong University funding program 253151020 and the National Natural Science Foundation of Guangdong Province (2016A030313704).

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