Synthesis of Co 0.5 Mn 0.1 Ni 0.4 C 2 O 4 ⋅ n  H 2 O Micropolyhedrons: Multimetal Synergy for High‐Performance Glucose Oxidation Catalysis

2019 ◽  
Vol 14 (13) ◽  
pp. 2259-2265 ◽  
Author(s):  
Nan Li ◽  
Qing Li ◽  
Meijuan Yuan ◽  
Xiaotian Guo ◽  
Shasha Zheng ◽  
...  
2020 ◽  
Vol 15 (13) ◽  
pp. 2036-2036
Author(s):  
Nan Li ◽  
Qing Li ◽  
Meijuan Yuan ◽  
Xiaotian Guo ◽  
Shasha Zheng ◽  
...  

Nanomaterials ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 202
Author(s):  
Yexin Dai ◽  
Jie Ding ◽  
Jingyu Li ◽  
Yang Li ◽  
Yanping Zong ◽  
...  

In this work, reduced graphene oxide (rGO) nanocomposites doped with nitrogen (N), sulfur (S) and transitional metal (Ni, Co, Fe) were synthesized by using a simple one-step in-situ hydrothermal approach. Electrochemical characterization showed that rGO-NS-Ni was the most prominent catalyst for glucose oxidation. The current density of the direct glucose alkaline fuel cell (DGAFC) with rGO-NS-Ni as the anode catalyst reached 148.0 mA/cm2, which was 40.82% higher than the blank group. The DGAFC exhibited a maximum power density of 48 W/m2, which was more than 2.08 folds than that of blank group. The catalyst was further characterized by SEM, XPS and Raman. It was speculated that the boosted performance was due to the synergistic effect of N, S-doped rGO and the metallic redox couples, (Ni2+/Ni3+, Co2+/Co3+ and Fe2+/Fe3+), which created more active sites and accelerated electron transfer. This research can provide insights for the development of environmental benign catalysts and promote the application of the DGAFCs.


2018 ◽  
Vol 115 (48) ◽  
pp. 12124-12129 ◽  
Author(s):  
Benjamin E. R. Snyder ◽  
Max L. Bols ◽  
Hannah M. Rhoda ◽  
Pieter Vanelderen ◽  
Lars H. Böttger ◽  
...  

A direct, catalytic conversion of benzene to phenol would have wide-reaching economic impacts. Fe zeolites exhibit a remarkable combination of high activity and selectivity in this conversion, leading to their past implementation at the pilot plant level. There were, however, issues related to catalyst deactivation for this process. Mechanistic insight could resolve these issues, and also provide a blueprint for achieving high performance in selective oxidation catalysis. Recently, we demonstrated that the active site of selective hydrocarbon oxidation in Fe zeolites, named α-O, is an unusually reactive Fe(IV)=O species. Here, we apply advanced spectroscopic techniques to determine that the reaction of this Fe(IV)=O intermediate with benzene in fact regenerates the reduced Fe(II) active site, enabling catalytic turnover. At the same time, a small fraction of Fe(III)-phenolate poisoned active sites form, defining a mechanism for catalyst deactivation. Density-functional theory calculations provide further insight into the experimentally defined mechanism. The extreme reactivity of α-O significantly tunes down (eliminates) the rate-limiting barrier for aromatic hydroxylation, leading to a diffusion-limited reaction coordinate. This favors hydroxylation of the rapidly diffusing benzene substrate over the slowly diffusing (but more reactive) oxygenated product, thereby enhancing selectivity. This defines a mechanism to simultaneously attain high activity (conversion) and selectivity, enabling the efficient oxidative upgrading of inert hydrocarbon substrates.


2021 ◽  
Vol 46 (5) ◽  
pp. 4055-4064
Author(s):  
Hongqi Shi ◽  
CongCong Tang ◽  
Zuchun Wang ◽  
Zejie Zhang ◽  
Wenjuan Liu ◽  
...  

2020 ◽  
Vol 63 (19-20) ◽  
pp. 1683-1699
Author(s):  
Annette Trunschke ◽  
Giulia Bellini ◽  
Maxime Boniface ◽  
Spencer J. Carey ◽  
Jinhu Dong ◽  
...  

AbstractThe “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions have been achieved in recent years and new catalysts are predicted today by using computational methods. To tackle the immense complexity of high-performance systems in reactions where selectivity is a major issue, analysis of scientific data by artificial intelligence and data science provides new opportunities for achieving improved understanding. Modern data analytics require data of highest quality and sufficient diversity. Existing data, however, frequently do not comply with these constraints. Therefore, new concepts of data generation and management are needed. Herein we present a basic approach in defining best practice procedures of measuring consistent data sets in heterogeneous catalysis using “handbooks”. Selective oxidation of short-chain alkanes over mixed metal oxide catalysts was selected as an example.


Nanoscale ◽  
2018 ◽  
Vol 10 (27) ◽  
pp. 13270-13276 ◽  
Author(s):  
Shasha Zheng ◽  
Bing Li ◽  
Yijian Tang ◽  
Qing Li ◽  
Huaiguo Xue ◽  
...  

Ultrathin nanosheet-assembled metal–organic framework hierarchical flowers have been regarded as very promising electrocatalysts for glucose oxidation reactions.


2020 ◽  
Author(s):  
Yanliang Zhou ◽  
Xiaoyu Li ◽  
Yicong Chai ◽  
Zihao Wu ◽  
Jian Lin ◽  
...  

Abstract It remains a challenge to make metal oxides with limited reducibility as active component rather than support or modifier for the oxidative dehydrogenation (ODH) of light alkanes. Here, we report a special TiO2 (M-TiO2) evolved from Ti3C2Tx MXene material to be a new kind of efficient catalyst in the ODH of ethane. The reactivity on this M-TiO2 is four times higher than that on P25 TiO2, endowing an excellent ethylene productivity of 15.4 gC2H4 gcat-1 h-1 that outperforms the previously reported catalysts. Experimental characterizations and theoretical calculations reveal the existence of both Ti and oxygen vacancy defects on M-TiO2. The Ti defect can increase the reducibility of M-TiO2 to reduce the activation barrier of ethane while the oxygen vacancy facilitates the adsorption of O2 to recover lattice oxygen, accounting for the high performance. This work enlightens the defect engineering of traditional metal oxide as a promising catalyst in the oxidation catalysis.


2020 ◽  
Vol 45 (38) ◽  
pp. 19163-19173
Author(s):  
Yahia H. Ahmad ◽  
Assem T. Mohamed ◽  
Ahmed El-Shafei ◽  
Siham Y. Al-Qaradawi ◽  
Amina S. Aljaber

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