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穆林
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Associate Professor Supervisor of Doctorate Candidates Supervisor of Master's Candidates
Paper Publications
[1] 王震.穆林,尚妍,尹洪超,东明.缪洪超.An innovative application of machine learning in prediction of the syngas properties of biomass chemical looping gasification based on extra trees regression algorithm[J],Energy,275
[2] 尹洪超.穆林,东明,Huo, Zhaoyi.黄贤坤,奚溪.Insight into the structural feature, ash transformation behavior, and alkali metal heat release characteristic of industrial lignin via experimental and equilibrium evaluation[J],Fuel,2024,343
[3] 穆林.Zhang, Bin,Huang, Xiankun,尹洪超,尚妍,Huo, Zhaoyi.王震.Surface reaction mechanisms of CO with Fe-based oxygen carrier supported by CaO and K2CO3 in chemical looping combustion: Case study[J],Chemical Engineering Science,2024,271
[4] 穆林.Wang, Ranyu,Zhang, Bin,尚妍,尹洪超.翟镇德.Evaluation of thermokinetics methodology, parameters, and coke characterization of co-pyrolysis of bituminous coal with herbaceous and agricultural biomass[J],Biomass Conversion and Biorefinery,2024,13(7):5957-5972
[5] 穆林.尹洪超,东明.王然宇,谢彭未,李永麟,黄贤坤.Comparative investigation on the pyrolysis of crop, woody, and herbaceous biomass: Pyrolytic products, structural characteristics, and CO2 gasification[J],Fuel,2024,335
[6] Huang, Xiankun.Wang, Shuoshuo,Zhu, Xiaoli,Bai, Zhang,穆林,Gong, Liang.Research on Modeling the Lignin Waste Molecular Structure and Pyrolytic Reactions Using Reaxff Md Method[J],SSRN,2024
[7] 穆林.尚妍,浦航,东明.王震,孙萌.Machine learning model with a novel self-adjustment method: A powerful tool for predicting biomass ash fusibility and enhancing its potential applications[J],RENEWABLE ENERGY,2024,237
[8] 张宇.王奉明,王彦红,穆林,东明.一体化加力燃烧室燃烧特性模拟与机器学习燃烧性能预测[J],北京航空航天大学学报,2024
[9] 王储.穆林,Chen, Dengyu,东明,Wang, Liang.曲航辰.Visual liquefaction process of biomass pyrolysis vapors during indirect heat exchange: Experimental description, prediction, and verification[J],Renewable Energy,2024,237
[10] 穆林.尚妍,Wang, Liang,东明,王储.王震,孙萌.Adsorption and Reaction Mechanism of Inert Carriers (Al2O3 and TiO2) Loaded with Fe2O3 in Chemical Looping Gasification Based on Density Functional Theory[J],ENERGY & FUELS,2024,38(21):20817-20830
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