Elsevier

Applied Catalysis A: General

Volume 521, 5 July 2016, Pages 90-95
Applied Catalysis A: General

Design of visible light responsive photocatalysts for selective reduction of chlorinated organic compounds in water

https://doi.org/10.1016/j.apcata.2015.11.018Get rights and content

Highlights

  • DFT calculation was performed for β-Bi2O3 photocatalyst modified with 32 elements.

  • Photocatalysts good at COCs reduction were designed by theoretical calculation.

  • Periodic change of photocatalyst feature is from the periodicity of doped elements.

Abstract

Periodic density functional theory (DFT) calculations were performed for β-Bi2O3 photocatalyst that was modified with 32 elements. Our focus was to design visible light responsive photocatalysts for selective reduction of chlorinated organic compounds (COCs) in water. The wanted photocatalysts should have (1) a moderate adsorption potential for COCs; (2) a wide adsorption spectrum for harvesting visible light; and (3) a reduction potential enough to destroy COCs. Based on these assumptions, a combined grand canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulation study was used to investigate the adsorption and diffusion behaviors of COCs in 32 modified β-Bi2O3; a Becke-three-parameter-Lee-Yand-Par (B3LYP) DFT method was used to calculate the energy band structures and redox potentials of different modified β-Bi2O3. Sequentially, these modified β-Bi2O3 were synthesized by solvothermal method, and the photo-reactivity of them were quantified in terms of the conduction band (CB) electron reduction using pentachlorophenol (PCP), trichloroethylene (TCE), and γ-hexachlorocyclohexane (HCH) as model COCs. The results demonstrated that the adsorption, photoabsorption, and photo-reactivity of modified β-Bi2O3 appear to be a complex function of the periodicity of 32 doped elements, which can be explained by the structural changes on the crystalline form and energy band structure. Based on this principle, a series of competent photocatalysts were believed to be efficient on the reduction of COCs. We designed and synthesized: (1) Ti-β-Bi2O3 photocatalyst that performed best on reduction of PCP (37.2 μmol L−1) with apparent quantum yield (ΦPCP) of 1.20%; (2) Sr-β-Bi2O3 photocatalyst for TCE (76.2 μmol L−1) reduction (ΦTCE 1.03%); and, (3) Zr-β-Bi2O3 photocatalyst for HCH (27.5 μmol L−1) reduction (ΦHCH 0.67%).

Introduction

Photocatalytic degradation of chlorinated organic compounds (COCs) is an important application of photocatalysis in the field of environmental remediation [1], [2]. COCs comprise a large group of synthetic organic chemicals. Many of them are known or potential threats to ecosystem and human health [3], [4], [5]. Well-known organic pollutants, such as chlorophenols (CPs) [6], chloroethenes (CEs) [7], and organic chlorinated pesticides (OCPs) [8], are among the most prevalent COCs and occurred worldwide in the environment.

Photocatalysis is a promising alternative method for degradation of COCs because this process can use solar light [9], [10]. However, the degradation efficiency of COCs by conventional photocatalysis in actual wastewater is relatively low [11]. The main drawbacks include the following aspects: (1) the photocatalytic activity of conventional photocatalysts need further strengthened; (2) the visible light absorption of conventional photocatalysts is insufficient to harness the full advantage of clean sunlight energy [12]; (3) both pollutants and harmless compounds are reduced/oxidized by photocatalysis, thereby wasting photo-generated carriers and decreasing the photocatalytic destruction of the target compounds [13], [14].

The photocatalytic degradation of COCs can be improved by reinforcing the photo-reactivity of photocatalyst [15], [16]. However, determining the optimum photocatalytic activity, photoabsorbability, and selectivity of a photocatalyst is quite challenging. This is determined by the internal process of photocatalysis. For example, let us consider the impact of the energy band structure of photocatalyst on reducing power of electron (e) in conduction band (CB) or oxidizing power of the hole (h+) in valence band (VB), and the wave length of light that is absorbed that creates an exciton. Higher CB edge potential of a photocatalyst might provide more active reductive electrons and lower potential at VB edge might yield holes with greater oxidizing power. Inevitably, this means extending of the band gap. While narrowing the band gap will enhance its photoabsorptivity in the region of visible light [17]. The “narrowing” (for harvesting more visible light), on one hand, constituted a contradiction with the “extending” (for greater redox power). On the other hand, the narrowed band gap make extra energy of photons (with more energy than the band gap) is lost through collisions in a process known as “relaxation” [18], [19]. Therefore, a photocatalyst with suitable energy band structure is desired to be designed precisely. Unfortunately, the photocatalysts and its impact on the band gap, quantum yield, conduction band reduction power and valence band hole oxidizing power are not yet fully understood. The experimental screening of the optimal photocatalyst is expensive and laborious. Therefore, the customized development of photocatalyst for selective removal of specific COCs is still a tough problem.

In the present study, we tried to design one or more visible light responsive photocatalysts, using computational simulation to selectively reduce COCs in water. More importantly, we intended to verify the relationships between the simulations and experimental principles based on the theoretical calculation, characterization and experimental verification. Herein, β-Bi2O3 was selected as the template for theoretical analysis because β-Bi2O3, as a semiconductor with photocatalytic activity, which is easy to make and can be easily doped to create a wide variety of photocatalytic properties [20], [21]. Computational simulations was employed to design and screen new photocatalysts theoretically. The photocatalytic experiments were then conducted to calibrate the results of the computational prediction using pentachlorophenol (PCP), tetrachloroethylene (TCE), and γ-hexachlorocyclohexane (HCH) as model COCs.

Section snippets

Preparation and characterization

Modified β-Bi2O3 were prepared by a solvothermal method, as described in our previous work [20]. The present method is different from the reported method that the tetrabutyl titanate was replaced by various nitrates or chloride of specific element. Exceptionally, the preparations of Tc-, Ru-, and Rh-β-Bi2O3 were failed (see Supplementary data). We tried to keep consistent in each synthesizing process because the following calculations were based on the assumption that the crystal forms and

Selective adsorption of COCs

The photocatalytic reaction rate is determined by both adsorption coefficients and photoreaction reaction rates [28]. A moderate adsorption is the necessary prerequisite to a photocatalytic reaction. Therefore, a combined GCMC and MD simulation study was performed to investigate the adsorption and diffusion behaviors of COCs in β-Bi2O3. As shown in Fig. 1, the PCP molecule quickly moves to a place 0.4–0.5 nm from the surface of after 150 ps. Adsorption simulation between other COCs and modified

Conclusions

In the present study, our first focus was to design optimized visible light responsive photocatalysts for selective reduction of COCs in water. To achieve this goal, we calculated the adsorbability, photoabsorptivity, and photocatalytic activity of 32 modified β-Bi2O3 photocatalysts, then synthesized these photocatalysts and verified the calculation results by characterizations and experiments. On this level, we designed Ti-β-Bi2O3, Sr-β-Bi2O3, and Zr-β-Bi2O3 photocatalysts to efficiently

Acknowledgements

This work was supported by National Natural Science Foundation of China (Project 21207004), Beijing Natural Science Foundation (8142025), and Specialized Research Fund for the Doctoral Program of Higher Education (Project 20120003120027), Special Funds of State Key Joint Laboratory of Environment Simulation and Pollution Control (11Y06ESPCN) and the Fundamental Research Funds for the Central Universities (2012LYB10).

This work was also partially supported by Brook Byers Institute for Sustainable

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