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Published on: March 29, 2019
Modulation of Bi2 MoO6 -Based Materials for Photocatalytic Water Splitting and Environmental Application: a Critical
Hanbo Yu1,2, Longbo Jiang1,2, Hou Wang1,2,3
1College of Environmental Science and Engineering, Hunan University, Changsha, 410082, P. R. China.
Abstract:
Highly active photocatalysts driving chemical reactions are of paramount importance toward renewable energy substitutes and environmental protection. As a fascinating Aurivillius phase material, Bi2 MoO6 has been the hotspot in photocatalytic applications due to its visible light absorption, nontoxicity, low cost, and high chemical durability. However, pure Bi2 MoO6 suffers from low efficiency in separating photogenerated carriers, small surface area, and poor quantum yield, resulting in low photocatalytic activity. Various strategies, such as morphology control, doping/defect-introduction, metal deposition, semiconductor combination, and surface modification with conjugative π structures, have been systematically explored to improve the photocatalytic activity of Bi2 MoO6 . To accelerate further developments of Bi2 MoO6 in the field of photocatalysis, this comprehensive Review endeavors to summarize recent research progress for the construction of highly efficient Bi2 MoO6 -based photocatalysts. Furthermore, benefiting from the enhanced photocatalytic activity of Bi2 MoO6 -based materials, various photocatalytic applications including water splitting, pollutant removal, and disinfection of bacteria, were introduced and critically reviewed. Finally, the current challenges and prospects of Bi2 MoO6 are pointed out. This comprehensive Review is expected to consolidate the existing fundamental theories of photocatalysis and pave a novel avenue to rationally design highly efficient Bi2 MoO6 -based photocatalysts for environmental pollution control and green energy development.
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In hypothesis testing, a sample statistic is converted to a test statistic using z, t, or chi-square distribution. A critical region is an area under the curve in probability distributions demarcated by the critical value. When the test statistic falls in this region, it suggests that the null hypothesis must be rejected. As this region contains all those values of the...
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