Photo-Thermal Synergistic Catalytic Oxidative Dehydrogenation of Propane over a Spherical Superstructure of Boron Carbon Nitride Nanosheets
APPLIED SURFACE SCIENCE(2023)
China Univ Petr East China | Shandong Energy Grp Co Ltd | Nanjing Univ | QingHai Salt Lake Ind Co Ltd
Abstract
The oxidative dehydrogenation of propane (ODHP) is an attractive reaction for increasing the production of light olefins due to its favorable thermodynamic and kinetic characteristics. However, the overoxidation of propene to thermodynamically favored COx leads to a trade-off between propane conversion and propene selectivity, limiting the optimization of the overall catalytic performance. Here we show that photo-thermal synergistic catalysis driven by a spherical superstructure of semiconducting boron carbon nitride nanosheets (SS-BCNNSs) breaks the conversion-selectivity trade-off, resulting in a remarkable enhancement of propane conversion, along with a well-maintained selectivity for propene under mild conditions. The mechanism study shows that the introduction of light irradiation during the ODHP process could change the reaction order, activate the reactants, and reduce the activation energy for ODHP. DFT calculations reveal that the photogenerated electrons provided by SS-BCNNSs promote oxygen adsorption and significantly reduce the energy barrier for generating active B-O center dot species, which in turn produces more active sites and enhances the reactivity.
MoreTranslated text
Key words
Photo-thermal synergistic catalysis,Oxidative dehydrogenation of propane,Boron carbon nitride,Metal-organic framework
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING 2024
被引用0
In Situ Growth of MOF from Wood Aerogel Toward Bromide Ion Adsorption in Simulated Saline Water.
LANGMUIR 2024
被引用0
Advancements of MOFs in the Field of Propane Oxidative Dehydrogenation for Propylene Production
Molecules 2024
被引用0
Sustainable Energy & Fuels 2024
被引用0
Catalyst development for O<sub>2</sub>-assisted oxidative dehydrogenation of propane to propylene
CHEMICAL COMMUNICATIONS 2024
被引用0
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper