有机质紫外-可见光谱蕴含丰富的分子结构、电子云分布方面的信息。针对真实环境中有机质光团众多相互干扰的问题，借助量子化学计算、瞬态光学实验、高分辩质谱、NMR等先进方法，揭示多化学态有机质的紫外-可见光谱信号与活性分子中质子、电子迁移内在关联，从光的量子性认识真实环境水体中复杂有机质光谱信号蕴含的总量、组分、活性方面的信息。以俘获水体光量子信息为目标，研制满足实验室科研、在线、遥感观测功能需要的智能感知新方法、新技术及关键仪器装备。

有机质紫外-可见光谱量子信息识别

代表性论文：

(1) Zhang, C. et al., Interpreting pH-dependent differential UV/VIS absorbance spectra to characterize carboxylic and phenolic chromophores in natural organic matter. Water Res 244, 120522  (2023).

(2) Chen, B. et al., Interpreting main features of the differential absorbance spectra of chlorinated natural organic matter: Comparison of the experimental and theoretical spectra of model compounds. Water Res 185, 116206-116206 (2020). 

(3) Yan, M. et al., Investigating the features in differential absorbance spectra of NOM associated with metal ion binding: A comparison of experimental data and TD-DFT calculations for model compounds. Water Res 124, 496-503 (2017).