The sustainability of methane catalytic decomposition is significantly enhanced by the production of high-quality value-added carbon products such as carbon nanotubes(CNTs).Understanding the production yields and prop...The sustainability of methane catalytic decomposition is significantly enhanced by the production of high-quality value-added carbon products such as carbon nanotubes(CNTs).Understanding the production yields and properties of CNTs is crucial for improving process feasibility and sustainability.This study employs machine learning technique to develop and analyze predictive models for the carbon yield and mean diameter of CNTs produced through methane catalytic decomposition.Utilizing comprehensive datasets from various experimental studies,the models incorporate variables related to catalyst composition,catalyst preparation,and operational parameters.Both models achieved high predictive accuracy,with R^(2)values exceeding 0.90.Notably,the reduction time during catalyst preparation was found to critically influence carbon yield,evidenced by a permutation importance value of 39.62%.Additionally,the use of Mo as a catalytic metal was observed to significantly reduce the diameter of produced CNTs.These findings highlight the need for future machine learning and simulation studies to include catalyst reduction parameters,thereby enhancing predictive accuracy and deepening process insights.This research provides strategic guidance for optimizing methane catalytic decomposition to produce enhanced CNTs,aligning with sustainability goals.展开更多
Twenty-nine European partners are developing an RFID-based application and supply-chain analysis system that may be used to increase sawmill eff iciency and raw materials usage,improve logistic operations and minimize...Twenty-nine European partners are developing an RFID-based application and supply-chain analysis system that may be used to increase sawmill eff iciency and raw materials usage,improve logistic operations and minimize environmental impacts.展开更多
A new dual-composition catalyst based on Ni-Mo/MgO with high efficiency of producing carbon nanotubes （CNTs） from methane was reported recently. In the present article, with this type of catalyst, the impact of such...A new dual-composition catalyst based on Ni-Mo/MgO with high efficiency of producing carbon nanotubes （CNTs） from methane was reported recently. In the present article, with this type of catalyst, the impact of such experimental parameters as reaction temperature, reaction time, concentration of H2, flow rate ratio of CH4 to H2 on yield and graphitization were investigated, leading to the following optimal growth conditions： reaction time 60min, reaction temperature 900℃, CH4：H2 about 100：20mL/min, under which high-yield multi-walled CNTs bundles were synthesized. Raman measurement indicated that the as-synthesized product was well-graphitized, and the purity was estimated over 95% by TG-DSC analysis. In terms of the above results, an explanation of high-efficiency formation of CNTs bundles and the co-catalysis mechanism of Ni-Mo/MgO were suggested. 2007 Chinese Societv of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V.展开更多
Nanofibrous carbonaceous materials （NFC） as a new class of materials having many applications, can catalyze the selective oxidation of H2S to sulfur. The correlation between NFC structure and its activity and select...Nanofibrous carbonaceous materials （NFC） as a new class of materials having many applications, can catalyze the selective oxidation of H2S to sulfur. The correlation between NFC structure and its activity and selectivity in H2S oxidation was determined. It is demonstrated that selectivity can be improved if NFC with more ordered structure be synthesized and the portion of the original catalyst in carbon be reduced by increasing the carbon accumulated in the catalyst.展开更多
基金supported by the Agency for Science,Technology and Research(A*STAR),Singapore,under the project Methane Pyrolysis for Hydrogen and Carbon Nanotube Production via Novel Catalytic Membrane Reactor System(No.U2102d2011)。
文摘The sustainability of methane catalytic decomposition is significantly enhanced by the production of high-quality value-added carbon products such as carbon nanotubes(CNTs).Understanding the production yields and properties of CNTs is crucial for improving process feasibility and sustainability.This study employs machine learning technique to develop and analyze predictive models for the carbon yield and mean diameter of CNTs produced through methane catalytic decomposition.Utilizing comprehensive datasets from various experimental studies,the models incorporate variables related to catalyst composition,catalyst preparation,and operational parameters.Both models achieved high predictive accuracy,with R^(2)values exceeding 0.90.Notably,the reduction time during catalyst preparation was found to critically influence carbon yield,evidenced by a permutation importance value of 39.62%.Additionally,the use of Mo as a catalytic metal was observed to significantly reduce the diameter of produced CNTs.These findings highlight the need for future machine learning and simulation studies to include catalyst reduction parameters,thereby enhancing predictive accuracy and deepening process insights.This research provides strategic guidance for optimizing methane catalytic decomposition to produce enhanced CNTs,aligning with sustainability goals.
文摘Twenty-nine European partners are developing an RFID-based application and supply-chain analysis system that may be used to increase sawmill eff iciency and raw materials usage,improve logistic operations and minimize environmental impacts.
基金This work was supported financially by the National Natural Science Foundation of China （No. 20506010） Beijing Novel Program （2006A74）Natural Science Fund of Shanxi Province （No. 20063004）.
文摘A new dual-composition catalyst based on Ni-Mo/MgO with high efficiency of producing carbon nanotubes （CNTs） from methane was reported recently. In the present article, with this type of catalyst, the impact of such experimental parameters as reaction temperature, reaction time, concentration of H2, flow rate ratio of CH4 to H2 on yield and graphitization were investigated, leading to the following optimal growth conditions： reaction time 60min, reaction temperature 900℃, CH4：H2 about 100：20mL/min, under which high-yield multi-walled CNTs bundles were synthesized. Raman measurement indicated that the as-synthesized product was well-graphitized, and the purity was estimated over 95% by TG-DSC analysis. In terms of the above results, an explanation of high-efficiency formation of CNTs bundles and the co-catalysis mechanism of Ni-Mo/MgO were suggested. 2007 Chinese Societv of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V.
文摘Nanofibrous carbonaceous materials （NFC） as a new class of materials having many applications, can catalyze the selective oxidation of H2S to sulfur. The correlation between NFC structure and its activity and selectivity in H2S oxidation was determined. It is demonstrated that selectivity can be improved if NFC with more ordered structure be synthesized and the portion of the original catalyst in carbon be reduced by increasing the carbon accumulated in the catalyst.
