Affinity of Keratin Peptides for Cellulose and Lignin: A Fundamental Study toward Advanced Bio-Based Materials.

Langmuir : the ACS journal of surfaces and colloids(2022)

引用 3|浏览3
暂无评分
摘要
Keratin is a potential raw material to meet the growing demand for bio-based materials with special properties. Keratin can be obtained from feathers, a by-product from the poultry industry. One approach for keratin valorization is to use the protein to improve the properties of already existing cellulose and lignin-based materials to meet the requirements for replacing fossil-based plastics. To ensure a successful combination of keratin with lignocellulosic building blocks, keratin must have an affinity to these substrates. Hence, we used quartz crystal microbalance with a dissipation monitoring (QCM-D) technique to get a detailed understanding of the adsorption of keratin peptides onto lignocellulosic substrates and how the morphology of the substrate, pH, ionic strength, and keratin properties affected the adsorption. Keratin was fractionated from feathers with a scalable and environmentally friendly deep eutectic solvent process. The keratin fraction used in the adsorption studies consisted of different sized keratin peptides (about 1-4 kDa), which had adopted a random coil conformation as observed by circular dichroism (CD). Measuring keratin adsorption to different lignocellulosic substrates by QCM-D revealed a significant affinity of keratin peptides for lignin, both as smooth films and in the form of nanoparticles but only a weak interaction between cellulose and keratin. Systematic evaluation of the effect of surface, media, and protein properties enabled us to obtain a deeper understanding of the driving force for adsorption. Both the structure and size of the keratin peptides appeared to play an important role in its adsorption. The keratin-lignin combination is an attractive option for advanced material applications. For improved adsorption on cellulose, modifications of either keratin or cellulose would be required.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要