期刊
INDUSTRIAL CROPS AND PRODUCTS
卷 93, 期 -, 页码 76-87出版社
ELSEVIER
DOI: 10.1016/j.indcrop.2016.01.048
关键词
Cellulose nanocrystals; Acid hydrolysis; Central composite design; Yield; Sulfate group density
资金
- National Research Initiative of the USDA Cooperative State Research, Education and Extension Service [2005-35504-16088]
- National Science Foundation [CHE-0724126, DMR-0907567]
- Virginia Agricultural Experiment Station
- USDA National Institute of Food and Agriculture, Hatch/Multi State project [1002269]
- Institute for Critical Technology and Applied Science
- Macromolecules and Interfaces Institute
- Omnova Solutions, Inc.
- NIFA [690024, 1002269] Funding Source: Federal RePORTER
Cellulose nanocrystals (CNCs) are most commonly prepared by sulfuric acid hydrolysis of a purified cellulose starting material but the effects of hydrolysis conditions on CNC yield and properties are incompletely understood. In this study, we use a rotatable central composite experimental design to elucidate parameter interactions between three design factors, acid concentration (x(1)), hydrolysis temperature (x(2)), and hydrolysis time (x(3)), over a broad range of process conditions and determine their effect on yield and sulfate group density. Parameter ranges are 55-65 wt.% for xi, 45-65 degrees C for x(2), and 30-180 min for x(3). Regression models of the experimental yield data reveal significant two-factor interactions of x(1) with each x(2) and x(3), whereas x(2) has no significant two-factor interaction with x(3). The models predict maximum yields of 66-69% at optimum process conditions of 57-58 wt.% (x1), 64-67 degrees C (x(2)), and 134-156 min (x(3)). At these conditions, the sulfate group density is predicted to be between 241 and 265 mmol/kg. The sulfate group density is linearly dependent on acid concentration and hydrolysis temperature and not dependent on hydrolysis time. Maximum sulfate group density can only be achieved at the expense of yield. The results presented here provide a foundation for subsequent, sequential optimization using narrower parameter ranges, allowing further optimization of the hydrolysis conditions and potentially enabling higher yield. (C) 2016 Elsevier B.V. All rights reserved.
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