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Optimizing the environmentally friendly silica-cellulose aerogel composite for acoustic insulation material derived from newspaper and geothermal solid waste using a central composite design

纤维素 材料科学 复合数 气凝胶 复合材料
作者
S. Silviana,Ferry Hermawan,Joshua Indracahya,Dinda Ajeng Lestari Kusumawardhani,Febio Dalanta
出处
期刊:Journal of Sol-Gel Science and Technology [Springer Science+Business Media]
卷期号:103 (1): 226-243 被引量:29
标识
DOI:10.1007/s10971-022-05831-y
摘要

This study aims to explore the combination of newspaper waste-derived cellulose and silica from geothermal solid waste to produce the silica-cellulose (Si-cellulose) aerogel as an enhanced sound insulation composite material. Cellulose was used as the matrix, while silica was applied as the impregnated particle to improve the characteristics and sound absorption ability of the composite. Subsequently, two datasets of central composite design (CCD) were used to generate the regression models the aerogel with the independent variables of cellulose and polyethylene glycol (PEG) concentrations as well as sound absorption coefficient (SAC) as the response. The generated regression models were evaluated using root-mean-square error (RMSE), analysis of variance (ANOVA), model adequacy, as well as diagnostics through normal plot of residuals, Cook’s distance, leverage, and predicted vs. residuals plots. The generated response surface plots suggest that the maximum SAC will be achieved by maximizing the cellulose composition. Based on several characterizations, it was concluded that the embedded silica changed the physical, chemical, mechanical, and thermal stability of the fabricated composite evidenced by the enhanced acoustic insulation performance. Furthermore, the optimum point for Si-cellulose aerogel was found at cellulose and PEG compositions of 25%-w and 1.78%-w/v, respectively, which produced the predicted maximum SAC of 0.9896 with a desirability score of 0.967. Based on the validation experiment results, the actual SAC was 0.9992 with a difference from the predicted value of 0.96%, indicating that the generated model can precisely predict the actual SAC value for utilizing Si-cellulose as an acoustic insulation material. Graphical abstract

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