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Published on: October 5, 2019
Cherenkov radiation enables hydrophobicity-selective transformation of photoactive micropollutants via singlet oxygen
Bin Yao1, Xiao Yang2, Miao Li3
1College of Environment and Ecology, Hunan Agricultural University, Changsha, 410128, China; Laboratory of Environmental Technology, INET, Tsinghua University, Beijing, 100084, PR China.
Abstract:
Ionizing radiation offers a promising chemical-free approach for water decontamination, with its degradation mechanism conventionally attributed to hydroxyl radical (•OH) oxidation through water radiolysis under ambient conditions. However, two unresolved issues challenge this •OH-centered view: the incomplete suppression of micropollutant degradation by excess •OH scavengers and the reported involvement of singlet oxygen (1O2) as a primary reactive species in the radiation-induced transformation of selected contaminants. Herein, using sulfadiazine (SDZ) and structurally related sulfonamide antibiotics (SAs) as model contaminants, we provide the first mechanistic evidence that Cherenkov radiation (CR), an intrinsic internal light source generated during ionizing radiation, can mediate self-sensitized photochemical transformation of photoactive micropollutants, thereby revealing an additional transformation route beyond conventional water radiolysis. 1O2 is the primary reactive intermediate, contributing 82 % to SDZ removal under ambient conditions. More importantly, we identify a previously unrecognized hydrophobicity-dependent structure-reactivity relationship within SAs, where the degradation rate constants strongly correlated with molecular hydrophobicity (R2 = 0.96). FFA/FFAm dual-probe analysis provided kinetic evidence that this selectivity was associated with the microheterogeneous availability of self-sensitized 1O2 around SAs. These findings reveal an overlooked CR-mediated self-sensitized photochemical pathway in ionizing radiation water treatment and establish hydrophobicity-regulated 1O2 microheterogeneity as a mechanistic basis for predicting and optimizing the selective transformation of photoactive micropollutants.
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