@article {SHAO2023130677, title = {Catalytic activation of formic acid using Pd nanocluster decorated graphitic carbon nitride for diclofenac reductive hydrodechlorination}, journal = {Journal of Hazardous Materials}, volume = {446}, year = {2023}, pages = {130677}, abstract = {Halogenated pharmaceuticals exhibit high toxicity if released to natural environment, and dehalogenation is a key process for their degradation. In this study, a reductive and directional dehalogenation technique, heterogenous formic acid (HCOOH) catalytic activation system, was proposed for diclofenac (DCF) dechlorination and detoxification. A functional material of Pd nanocluster decorated graphitic carbon nitride (Pd/g-C3N4) was developed for HCOOH activation. Although the optimized material (Pd1/g-C3N4) showed lower HCOOH decomposition rate (k1 = 0.287 {\textpm} 0.017~min-1) than the pristine Pd particles (k1 = 0.401 {\textpm} 0.031~min-1), it processed higher DCF degradation efficiency (97.9\% within 30~min) than Pd particles. The enhancement mechanism was revealed by both experiments and theoretical calculations. Firstly, the six-fold cavities of g-C3N4 acted as anchor sites, which offered strong coordination environment for Pd nanoclusters. Secondly, the strong coordination environment of Pd led to upshifted d-band center of Pd 4d with enhanced bonding state, and then promoted HCOOH adsorption on Pd/g-C3N4, thus facilitating HCOOH decomposition through formate pathway rather than carboxyl pathway. Thirdly, Pd/g-C3N4 ensured HCOOH selectively decomposed as dehydrogenation reaction, which generated more H* (adsorbed H on Pd) than the dehydration reaction. The H* was proved to be the dominant reductive species for DCF hydrodechlorination. Moreover, the toxicities of DCF dechlorination products were greatly reduced.}, keywords = {Catalytic reduction, Dechlorination, Diclofenac, Formic acid, Pd nanocluster}, issn = {0304-3894}, doi = {http://doi.org/10.1016/j.jhazmat.2022.130677}, url = {http://www.sciencedirect.com/science/article/pii/S0304389422024736}, author = {Feng Shao and Yixuan Gao and Wenhui Xu and Fengbin Sun and Long Chen and Li, Fan and Liu, Wen} }