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Machine-learning-aided Au-based single-atom alloy catalysts discovery for electrochemical NO reduction reaction to NH_(3)
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作者 Hui-Long Jin Qian-Nan Li +4 位作者 Yun-Yan Tian Shuo-Ao Wang Xing Chen jie-yu liu Chang-Hong Wang 《Rare Metals》 SCIE EI CAS CSCD 2024年第11期5813-5822,共10页
Direct electrochemical conversion of NO to NH_(3)has attracted widespread interest as a green and sustainable strategy for both ammonia synthesis and nitric oxide removal.However,designing efficient catalysts remains ... Direct electrochemical conversion of NO to NH_(3)has attracted widespread interest as a green and sustainable strategy for both ammonia synthesis and nitric oxide removal.However,designing efficient catalysts remains challenging due to the complex reaction mechanism and competing side reactions.Single-atom alloy(SAA)catalysts,which increase the atomic efficiency and the chance to tailor the electronic properties of the active center,have become a frontier in this field.Here,we performed a systematic screening of transition metal-doped Au SAAs(denoted as TM/Au,TM=Sc,Ti,V,Cr,Mn,Fe,Co,Ni,Cu,Zn,Ru,Rh,Pd,Ag and Pt)to find potential catalysts for electrochemical NO reduction reaction(NORR)to NH_(3).By employing a four-step screening strategy based on density functional theory(DFT)calculations,Zn/Au SAA has been identified as a promising NORR catalyst due to its superior structural stability,reaction activity and NH_(3)selectivity.The electron-involved steps on Zn/Au are thermodynamically spontaneous,which results in a positive limiting potential(U_(L))of 0.15 V.The preferred NO affinity compared to H adatom demonstrates that Zn/Au can effectively suppress the hydrogen evolution reaction.Machine-learning(ML)investigations were adopted to address the uncertainty between the physicochemical properties of SAAs and the NORR performance.We applied an extreme gradient boosting regression(XGBR)algorithm to predict the limiting potentials in terms of the intrinsic features of the reaction site.The coefficient of determination(R^(2))is 0.97 for the training set and 0.96 for the test set.The electronic structure an alysis combined with a compressed-sensing data-an alytics approach further quantitatively verifies the coeffect of d-band center,charge transfer and the radius of doped TM atoms,i.e.,features with the highest level of importance determined by the XGBR algorithm.This work provides a theoretical understanding of the complex NORR to NH_(3)mechanisms and sheds light on the rational design of SAA catalysts by combining DFT and ML investigations. 展开更多
关键词 NO reduction reaction Ammonia synthesis Single-atom alloy catalysts Machine learning
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Multisystem involvement in Chinese patients with neuromyopathic phenotype of mitochondrial trifunctional protein deficiency 被引量:1
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作者 Cui-Jie Wei Xing-Zhi Chang +7 位作者 Lin Ge Xiao-Na Fu Yan-Bin Fan jie-yu liu Shuang Wang Hai-Li Li Yan-Ling Yang Hui Xiong 《Chinese Medical Journal》 SCIE CAS CSCD 2020年第11期1358-1360,共3页
Mitochondrial trifunctional protein(MTP)is a multienzyme complex,which catalyzes the last three steps of mitochondrial p-oxidation of the long-chain fatty acids.Structurally,MTP consists of four a-subunits and four P-... Mitochondrial trifunctional protein(MTP)is a multienzyme complex,which catalyzes the last three steps of mitochondrial p-oxidation of the long-chain fatty acids.Structurally,MTP consists of four a-subunits and four P-subunits,which are encoded by HADHA gene(OMIM 600890)and HADHB gene(OMIM 143450),respectively.Mutations in HADHA or HADHB lead to varying degrees of decline in MTP activity,that in turn results in three types of clinical manifestations:a severe phenotype with neonatal onset,a hepatic phenotype with infantile onset,and a neuromyopathic phenotype with later onset. 展开更多
关键词 INVOLVEMENT HEPATIC PATIENTS
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