PARTITIONING OF BAICALIN IN AQUEOUS TWO PHASES SYSTEM COMBINED WITH TEMPERATURE INDUCED PHASE SEPARATION

Li Wei; Zhu Ziqiang; Mei Lehe; Guan Yixin; Yang Lirong(Department of Chemical Engineering

您当前的位置：

首页 >

文章列表页 >

PARTITIONING OF BAICALIN IN AQUEOUS TWO PHASES SYSTEM COMBINED WITH TEMPERATURE INDUCED PHASE SEPARATION

更新时间：2025-12-16

- PARTITIONING OF BAICALIN IN AQUEOUS TWO PHASES SYSTEM COMBINED WITH TEMPERATURE INDUCED PHASE SEPARATION
- CIESC Journal Issue 1, (1998)
- 作者机构：
  
  浙江大学化工系!杭州310027,浙江大学化工系!杭州310027,浙江大学化工系!杭州310027,浙江大学化工系!杭州310027,浙江大学化工系,杭州,310027
- 作者简介：
- 基金信息：
- DOI：
  CLC： 642
- Online First：25 February 1998，
  
  Published：25 February 1998
- 稿件说明：
移动端阅览
Li Wei, Zhu Ziqiang, Mei Lehe, et al. PARTITIONING OF BAICALIN IN AQUEOUS TWO PHASES SYSTEM COMBINED WITH TEMPERATURE INDUCED PHASE SEPARATION[J]. CIESC Journal, 1998, (1).
DOI：

Li Wei, Zhu Ziqiang, Mei Lehe, et al. PARTITIONING OF BAICALIN IN AQUEOUS TWO PHASES SYSTEM COMBINED WITH TEMPERATURE INDUCED PHASE SEPARATION[J]. CIESC Journal, 1998, (1). DOI：

摘要

Abstract

Partition coefficients of baicalin in EOPO/potassium phosphate aqueous two phases system combined with temperature induced phase separation were measured.The effects on partition coefficients of salt addition

EOPO and potassium phosphate concentration were investigated.A method for baicalin extraction from Scutellaria baicalensis Georgi is proposed by using aqueous two phases extraction combined with temperature induced phase separation.

关键词

Keywords

references

Views

430

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Physics-informed spatio-temporal graph convolutional network for fermentation processes

Advantages and risks of swirling cooling granulation towers

Construction of transition metal-based nitrogen-doped carbon and their desulfurization performance

Heat transfer mechanisms, bottleneck identification and optimization in heat exchanger networks under variable operating conditions

A two-stage dual-channel deep learning model for chemical fault classification

Related Author

No data

Related Institution

No data

⁰