five

OPTIMIZATION OF LIPASE IMMOBILIZATION ON MAGHEMITE AND ITS PHYSICO-CHEMICAL PROPERTIES

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://figshare.com/articles/dataset/OPTIMIZATION_OF_LIPASE_IMMOBILIZATION_ON_MAGHEMITE_AND_ITS_PHYSICO-CHEMICAL_PROPERTIES/8987360
下载链接
链接失效反馈
官方服务:
资源简介:
ABSTRACT Nanomaterial-based biocatalysts have emerged as current carriers suitable for enzyme immobilization. The nano-sized materials provide large surface area for enzyme attachment, thus increasing the probability for its efficient catalyst activity. By using magnetized nanomaterials, enhancement of the downstream processing is evident as it eases the immobilized enzyme separation from the reaction mixture further. Lipase / maghemite composites were prepared by initial maghemite surface modification to cater to the needs for biocatalyst attachment. Surface modification using chitosan and subsequent cross-linking with glutaraldehyde provide a suitable environment for the enzyme to be immobilized. Optimization of the conditions for lipase immobilization was carried out using a response surface methodology (RSM) experimental design to obtain the precise optimized conditions for the process. Selected process variables involved were chosen and optimized conditions for lipase immobilization were 9 hour incubation time, 55°C incubation temperature and 12 % (v/v) glutaraldehyde content. The optimized immobilized lipase activity was 1.8 U. Characterizations of the on synthesized materials were also performed. The size distribution of maghemite nanomaterials was mainly within the range of 2-3 nm. Thermal properties of the synthesized maghemite was investigated using DSC and TGA analyses and we found that maghemite changes to hematite at 456.3°C. Magnetic properties of both untreated and lipase immobilized maghemite were studied using VSM and both were superparamagnetic nanomaterials with saturation magnetizations of 34.3 and 80.3, respectively.
创建时间:
2019-03-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作