Vanderfleet Oriana M, Osorio Daniel A, Cranston Emily D
Chemical Engineering Department, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L8.
Materials Science and Engineering Department, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L8.
Philos Trans A Math Phys Eng Sci. 2018 Feb 13;376(2112). doi: 10.1098/rsta.2017.0041.
Cellulose nanocrystals (CNCs) are emerging nanomaterials with a large range of potential applications. CNCs are typically produced through acid hydrolysis with sulfuric acid; however, phosphoric acid has the advantage of generating CNCs with higher thermal stability. This paper presents a design of experiments approach to optimize the hydrolysis of CNCs from cotton with phosphoric acid. Hydrolysis time, temperature and acid concentration were varied across nine experiments and a linear least-squares regression analysis was applied to understand the effects of these parameters on CNC properties. In all but one case, rod-shaped nanoparticles with a high degree of crystallinity and thermal stability were produced. A statistical model was generated to predict CNC length, and trends in phosphate content and zeta potential were elucidated. The CNC length could be tuned over a relatively large range (238-475 nm) and the polydispersity could be narrowed most effectively by increasing the hydrolysis temperature and acid concentration. The CNC phosphate content was most affected by hydrolysis temperature and time; however, the charge density and colloidal stability were considered low compared with sulfuric acid hydrolysed CNCs. This study provides insight into weak acid hydrolysis and proposes 'design rules' for CNCs with improved size uniformity and charge density.This article is part of a discussion meeting issue 'New horizons for cellulose nanotechnology'.
纤维素纳米晶体(CNCs)是一类新兴的纳米材料,具有广泛的潜在应用。CNCs通常通过用硫酸进行酸水解来制备;然而,磷酸具有生成热稳定性更高的CNCs的优势。本文提出了一种实验设计方法,用于优化用磷酸从棉花中水解制备CNCs的过程。在九个实验中改变了水解时间、温度和酸浓度,并应用线性最小二乘回归分析来了解这些参数对CNCs性能的影响。除了一种情况外,在所有实验中都制备出了具有高度结晶度和热稳定性的棒状纳米颗粒。生成了一个统计模型来预测CNCs的长度,并阐明了磷酸盐含量和zeta电位的趋势。CNCs的长度可以在相对较大的范围内调节(238 - 475nm),并且通过提高水解温度和酸浓度可以最有效地缩小多分散性。CNCs的磷酸盐含量受水解温度和时间的影响最大;然而,与硫酸水解的CNCs相比,其电荷密度和胶体稳定性被认为较低。本研究深入了解了弱酸水解,并提出了具有改进的尺寸均匀性和电荷密度的CNCs的“设计规则”。本文是“纤维素纳米技术的新视野”讨论会议特刊的一部分。