蛭石基FeCeOx催化剂及CO选择性催化还原NO
Vermiculite-supported FeCe bimetallic catalyst for selective catalytic reduction of NO with CO
高飞 1刘志松 1潘珂珂 1刘敏敏 1代斌 1但建明 1于锋2
作者信息
- 1. 石河子大学化学化工学院化工绿色过程兵团重点实验室,新疆石河子 832003
- 2. 石河子大学化学化工学院化工绿色过程兵团重点实验室,新疆石河子 832003;石河子大学兵团工业技术研究院碳中和与环境催化技术研究室,新疆石河子 832003
- 折叠
摘要
以CO为还原剂去除NO的选择性催化还原(CO-SCR)技术受到了广泛关注.本文以天然矿物蛭石为载体,采用共沉淀辅助浸渍法(CP-IM)制备了蛭石负载的铁铈双金属氧化物(FeCe/VMT)用于CO-SCR脱硝反应.表征结果显示,相比传统的浸渍法(IM),共沉淀辅助浸渍制备的FeCe/VMT催化剂具有更大的比表面积(106.9m2/g)和更多氧空位,可以提供更多的活性位点.共沉淀过程形成更多Fe3+,并促进了 FeCe间的协同作用,有利于提高CO-SCR的催化活性和稳定性.性能测试表明,在300℃和50000h-1的空速下,NO转化率可达100％,48h后NO转化率几乎无衰减.当温度降至250℃时,NO的转化率依然可以达到97％.同时,利用原位红外光谱和密度泛函理论计算技术,揭示了相应的催化反应机理,为制备大比表面积的负载型催化剂提供了一种方法.
Abstract
NO removal by CO selective catalytic reduction(CO-SCR)has gained great attentions.In this paper,vermiculite-supported Fe-Ce bimetallic oxides(FeCe/VMT)for CO-SCR were prepared by coprecipitation-assisted impregnation(CP-IM)with the natural mineral vermiculite as the carrier.The characterization results showed that compared with the traditional impregnation method(IM),FeCe/VMT(CP-IM)prepared by coprecipitation-assisted impregnation had larger specific surface area(106.9m2/g)and more oxygen vacancies due to more active sites available.The enhanced synergistic effect between FeCe was beneficial to the increase of both catalytic activity and stability in CO-SCR reaction.Performance tests showed that NO conversion reached 100％at 300℃ with 50000h-1 gas hourly space velocity(GHSV),and the performance of the catalyst didn't decrease within 48h.When the temperature dropped to 250℃,the conversion of NO could still reach 97％.At the same time,in situ infrared spectroscopy and density functional theory were used to reveal the corresponding catalytic mechanism.This research provided a promising method for preparing supported catalysts with large specific surface area.
关键词
催化剂/一氧化碳/选择催化还原/纳米材料/多相反应Key words
catalyst/carbon monoxide/selective catalytic reduction(SCR)/nanomaterials/multiphase reaction引用本文复制引用
基金项目
兵团区域创新计划(2021BB005)
兵团科技创新团队计划(2020CB006)
兵团重大科技计划(2018AA002)
出版年
2024
国家科技期刊平台
NSTL
万方数据