{"title":"表面响应法优化微波辅助木渣脱木质素","authors":"A. Trifan, I. Călinescu, M. Vinatoru, A. Gavrila","doi":"10.4995/ampere2019.2019.9861","DOIUrl":null,"url":null,"abstract":"Efficient processing of vegetal biomass is a great challenge to current research studies. This work is focused on improving the yield of enzymatic hydrolysis of wood residues by removal of lignin using a alkaline wash assisted by microwave heating. The treatments were carried out for one hour in a pressurized microwave reactor (Synthwave-Milestone). The performance of the treatments was assessed by monitoring the concentration of lignin (determined by UV absorbance at 320 nm against a calibration curve). Each experiment was carried out in duplicate. The treatment conditions were established according to an experimental matrix constructed (in Design Expert 11) after the careful selection of the most important factors that affect the lignin removal from wood residue: concentration of NaOH solution, liquid to solid ratio and temperature. A central composite design was constructed with the independent factors mentioned above. ANOVA indicated adequate fitting of the model (correlation coefficient R2=0.95). The exploration of the experimental space (figure 1) with the fitted model indicates the dominant effect of temperature as independent factor. Optimization of experimental conditions within the experimental space was carried according to the following criteria: minimization of temperature, liquid to solid ratio and NaOH concentration and maximization of the response variable, the lignin concentration. The optimal solution (141 mg lignin / g dry wood residue) proposed by the model for these optimization criteria indicates a point in the region determined by the following coordinates: 0.4M NaOH, 1070C and a ratio of liquid to solid equal to 50. Fig. 1. 3D plot of lignin responses surfaces function of the independent factors with significant effectsAcknowledgment The authors acknowledge the financial support received from Competitiveness Operational Program 2014-2020, Priority axis 1, Project No. P_36_611, MySMIS code 107066, Innovative Technologies for Materials Quality Assurance in Health, Energy and Environmental - Center for Innovative Manufacturing Solutions of Smart Biomaterials and Biomedical Surfaces – INOVABIOMED.","PeriodicalId":277158,"journal":{"name":"Proceedings 17th International Conference on Microwave and High Frequency Heating","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"OPTIMIZATION OF MICROWAVE ASSISTED DELIGNIFICATION OF WOOD RESIDUES BY SURFACE RESPONSE METHODOLOGY\",\"authors\":\"A. Trifan, I. Călinescu, M. Vinatoru, A. Gavrila\",\"doi\":\"10.4995/ampere2019.2019.9861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient processing of vegetal biomass is a great challenge to current research studies. This work is focused on improving the yield of enzymatic hydrolysis of wood residues by removal of lignin using a alkaline wash assisted by microwave heating. The treatments were carried out for one hour in a pressurized microwave reactor (Synthwave-Milestone). The performance of the treatments was assessed by monitoring the concentration of lignin (determined by UV absorbance at 320 nm against a calibration curve). Each experiment was carried out in duplicate. The treatment conditions were established according to an experimental matrix constructed (in Design Expert 11) after the careful selection of the most important factors that affect the lignin removal from wood residue: concentration of NaOH solution, liquid to solid ratio and temperature. A central composite design was constructed with the independent factors mentioned above. ANOVA indicated adequate fitting of the model (correlation coefficient R2=0.95). The exploration of the experimental space (figure 1) with the fitted model indicates the dominant effect of temperature as independent factor. Optimization of experimental conditions within the experimental space was carried according to the following criteria: minimization of temperature, liquid to solid ratio and NaOH concentration and maximization of the response variable, the lignin concentration. The optimal solution (141 mg lignin / g dry wood residue) proposed by the model for these optimization criteria indicates a point in the region determined by the following coordinates: 0.4M NaOH, 1070C and a ratio of liquid to solid equal to 50. Fig. 1. 3D plot of lignin responses surfaces function of the independent factors with significant effectsAcknowledgment The authors acknowledge the financial support received from Competitiveness Operational Program 2014-2020, Priority axis 1, Project No. P_36_611, MySMIS code 107066, Innovative Technologies for Materials Quality Assurance in Health, Energy and Environmental - Center for Innovative Manufacturing Solutions of Smart Biomaterials and Biomedical Surfaces – INOVABIOMED.\",\"PeriodicalId\":277158,\"journal\":{\"name\":\"Proceedings 17th International Conference on Microwave and High Frequency Heating\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 17th International Conference on Microwave and High Frequency Heating\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4995/ampere2019.2019.9861\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 17th International Conference on Microwave and High Frequency Heating","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4995/ampere2019.2019.9861","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
OPTIMIZATION OF MICROWAVE ASSISTED DELIGNIFICATION OF WOOD RESIDUES BY SURFACE RESPONSE METHODOLOGY
Efficient processing of vegetal biomass is a great challenge to current research studies. This work is focused on improving the yield of enzymatic hydrolysis of wood residues by removal of lignin using a alkaline wash assisted by microwave heating. The treatments were carried out for one hour in a pressurized microwave reactor (Synthwave-Milestone). The performance of the treatments was assessed by monitoring the concentration of lignin (determined by UV absorbance at 320 nm against a calibration curve). Each experiment was carried out in duplicate. The treatment conditions were established according to an experimental matrix constructed (in Design Expert 11) after the careful selection of the most important factors that affect the lignin removal from wood residue: concentration of NaOH solution, liquid to solid ratio and temperature. A central composite design was constructed with the independent factors mentioned above. ANOVA indicated adequate fitting of the model (correlation coefficient R2=0.95). The exploration of the experimental space (figure 1) with the fitted model indicates the dominant effect of temperature as independent factor. Optimization of experimental conditions within the experimental space was carried according to the following criteria: minimization of temperature, liquid to solid ratio and NaOH concentration and maximization of the response variable, the lignin concentration. The optimal solution (141 mg lignin / g dry wood residue) proposed by the model for these optimization criteria indicates a point in the region determined by the following coordinates: 0.4M NaOH, 1070C and a ratio of liquid to solid equal to 50. Fig. 1. 3D plot of lignin responses surfaces function of the independent factors with significant effectsAcknowledgment The authors acknowledge the financial support received from Competitiveness Operational Program 2014-2020, Priority axis 1, Project No. P_36_611, MySMIS code 107066, Innovative Technologies for Materials Quality Assurance in Health, Energy and Environmental - Center for Innovative Manufacturing Solutions of Smart Biomaterials and Biomedical Surfaces – INOVABIOMED.