Comprehensive Evaluation and Prediction of the Effectiveness of H2O2-assisted Na2CO3 Pretreatment of Corn Stover Using Multivariate Analysis |
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Authors: | Xiaoyan Feng Xuejin Xie Yidong Zhang Guang Yu Chao Liu Bin Li Qiu Cui |
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Affiliation: | 1.Key Laboratory of Biofuels, Shandong Engineering Laboratory of Single Cell Oil, Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong Province, 266101, China;2.Shandong Energy Institute, Qingdao, Shandong Province, 266101, China;3.Dalian National Laboratory for Clean Energy, Dalian, Liaoning Province, 116023, China |
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Abstract: | In this study, multivariate analysis methods, including a principal component analysis (PCA) and partial least square (PLS) analysis, were applied to reveal the inner relationship of the key variables in the process of H2O2-assisted Na2CO3 (HSC) pretreatment of corn stover. A total of 120 pretreatment experiments were implemented at the lab scale under different conditions by varying the particle size of the corn stover and process variables. The results showed that the Na2CO3 dosage and pretreatment temperature had a strong influence on lignin removal, whereas pulp refining instrument (PFI) refining and Na2CO3 dosage played positive roles in the final total sugar yield. Furthermore, it was found that pretreatment conditions had a more significant impact on the amelioration of pretreatment effectiveness compared with the properties of raw corn stover. In addition, a prediction of the effectiveness of the corn stover HSC pretreatment based on a PLS analysis was conducted for the first time, and the test results of the predictability based on additional pretreatment experiments proved that the developed PLS model achieved a good predictive performance (particularly for the final total sugar yield), indicating that the developed PLS model can be used to predict the effectiveness of HSC pretreatment. Therefore, multivariate analysis can be potentially used to monitor and control the pretreatment process in future large-scale biorefinery applications. |
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Keywords: | lignocellulose pretreatment corn stover Na2CO3 principle component analysis partial least square analysis |
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