Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the unde...Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the undesired characteristics of the process, including high carbon footprint, necessitate alternative ammonia synthesis methods, and among them is chemical looping ammonia production(CLAP) that uses nitrogen carrier materials and operates at atmospheric pressure with high product selectivity and energy efficiency. To date, neither a systematic review nor a perspective in nitrogen carriers and CLAP has been reported in the critical area. Thus, this work not only assesses the previous results of CLAP but also provides perspectives towards the future of CLAP. It classifies, characterizes, and holistically analyzes the fundamentally different CLAP pathways and discusses the ways of further improving the CLAP performance with the assistance of plasma technology and artificial intelligence(AI).展开更多
基金supported by the DNL Cooperation Fund,CAS(DNL180402)the support from the University of Wyoming。
文摘Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However,the undesired characteristics of the process, including high carbon footprint, necessitate alternative ammonia synthesis methods, and among them is chemical looping ammonia production(CLAP) that uses nitrogen carrier materials and operates at atmospheric pressure with high product selectivity and energy efficiency. To date, neither a systematic review nor a perspective in nitrogen carriers and CLAP has been reported in the critical area. Thus, this work not only assesses the previous results of CLAP but also provides perspectives towards the future of CLAP. It classifies, characterizes, and holistically analyzes the fundamentally different CLAP pathways and discusses the ways of further improving the CLAP performance with the assistance of plasma technology and artificial intelligence(AI).
