Highly Selective Nitrite Hydrogenation to Ammonia over Iridium Nanoclusters: Competitive Adsorption Mechanism

Wet denitrification is a promising approach to control nitrogen oxides (NOx) produced in fossil fuel combustion. Yet, the highly concentrated nitrite (NO2-) wastewater generated poses a major threat to the aqueous environment. Here, iridium nanoclusters (d = 1.63 nm) deposited on TiO2 were applied for NO2- reduction to ammonia (NRA), showing an exceptional NH4+ selectivity of 95% and a production rate of 20.51 mgN center dot L-1 center dot h(-1), which held significant potential for NO2- wastewater purification and ammonia resource recovery. Notably, an interesting nonfirst-order NO2- hydrogenation kinetics was observed, which was further confirmed to result from the competitive adsorption mechanism between H-2 and NO2- over iridium. The NRA pathways on the Ir(111) surface were explored via density functional theory calculations with the NO2-*. NO*-> HNO*-> HNOH*-> H2NOH*. NH2*-> NH3* identified as the most energetically favorable pathway and the NO*. HNO* confirmed as the rate-determining step. In situ DRIFTS further experimentally verified the generation of HNO* intermediate during NO* hydrogenation on Ir(111). To verify NRA kinetics at varied NO2- concentrations or H-2 pressures, a kinetic model was derived based on the Langmuir-Hinshelwood competitive adsorption mechanism. These findings provide mechanistic insights into the NRA pathways on Ir nanocatalysts, which will be beneficial for wet denitrification waste stream decontamination and valorization.

Automated summary

The use of iridium nanoclusters deposited on TiO2 for the reduction of NO2- to ammonia shows high selectivity and production rate, making it a promising method for the purification of NO2- wastewater and recovery of ammonia resources. The competitive adsorption mechanism between H-2 and NO2- on iridium leads to interesting non-first-order NO2- hydrogenation kinetics. The NRA pathways on the Ir(111) surface were explored, providing mechanistic insights for wet denitrification waste stream decontamination and valorization.