Liu Yang, Huixiang Ang Edison, Zhong Xiu, Lu Hao, Yang Jun, Gao Fei, Yu Chao, Zhu Jiawei, Zhu Chengzhang, Zhou Yu, Yang Fu, Yuan Enxian, Yuan Aihua
School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, Jiangsu, China.
Natural Sciences and Science Education, National Institute of Education, Nanyang Technological University, Singapore 637616, Singapore.
J Colloid Interface Sci. 2023 Dec 15;652(Pt A):418-428. doi: 10.1016/j.jcis.2023.08.106. Epub 2023 Aug 18.
The oxygen vacancy modulation of interface-engineered FeO nanograins over carbon nanofiber (Fe@CNF) was achieved to improve electrocatalytic nitrogen reduction reaction (NRR) activity and stability via facile electrospinning and tuning thermal procedure. The optimal catalyst calcined at 800 ℃ (Fe@CNF-800) was endowed with abundant nanograin boundaries and optimized oxygen vacancy (V) concentration of iron oxides, thereby affording 37.1 μg h mg (-0.2 V vs. reversible hydrogen electrode (RHE)) NH yield and rational Faraday efficiency (10.2%), with 13.6 times atomic activity enhancement compared to of that commercial FeO. The interfacial effect of assembled nanograins in particles correlated with the formation of V and more intrinsic active sites, which is conducive to the trapping and activation of nitrogen (N). The in-situ X-ray photoelectron spectroscopy (XPS) measurement revealed the real consumption of adsorbed oxygen when introducing N by the trapping effect of V. Density-Functional-Theory (DFT) calculation validates the promotive hydrogenation effect and elimination of hydrogen intermediate (H*) interacted with N transferring toward oxygen of the support. The optimal catalyst shows a lasting NRR activity at least 90 h, outperforming most reported Fe-based NRR catalysts.
通过简便的静电纺丝和热程序调节,实现了对碳纳米纤维负载的界面工程化FeO纳米颗粒(Fe@CNF)的氧空位调制,以提高电催化氮还原反应(NRR)的活性和稳定性。在800℃煅烧的最佳催化剂(Fe@CNF-800)具有丰富的纳米晶界和优化的铁氧化物氧空位(V)浓度,从而实现了37.1 μg h mg(相对于可逆氢电极(RHE)为-0.2 V)的NH产率和合理的法拉第效率(10.2%),与商业FeO相比,原子活性提高了13.6倍。颗粒中组装纳米颗粒的界面效应与V的形成和更多本征活性位点相关,这有利于氮(N)的捕获和活化。原位X射线光电子能谱(XPS)测量表明,通过V的捕获效应引入N时,吸附氧会真正消耗。密度泛函理论(DFT)计算验证了与N相互作用并向载体氧转移的氢中间体(H*)的促进氢化作用和消除。最佳催化剂表现出至少90 h的持久NRR活性,优于大多数报道的铁基NRR催化剂。