研究简报

丹酚酸B的热稳定性及其热分解动力学研究

  • 王韶旭 ,
  • 谭志诚 ,
  • 车如心 ,
  • 李彦生
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  • a 大连交通大学环境与化学工程学院 大连 116028;
    b 中国科学院大连化学物理研究所中国离子液体实验室和热化学实验室 大连 116023

收稿日期: 2011-04-07

  修回日期: 2011-09-28

  网络出版日期: 2012-02-25

基金资助

国家自然科学基金(Nos.20903017, 21073189);大连市科学技术基金(No.2010J21DW010);中国博士后科学基金(No.20080431141)资助项目.

Thermal Stability and Kinetics of Thermal Decomposition of Salvianolic Acid B

  • WANG Shao-Xu ,
  • TAN Zhi-Cheng ,
  • CHE Ru-Xin ,
  • LI Yan-Sheng
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  • a College of Environmental Science & Engineering, Dalian Jiaotong University, Dalian 116028;
    b China Ionic Liquid Laboratory and Thermochemistry Laboratory, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023

Received date: 2011-04-07

  Revised date: 2011-09-28

  Online published: 2012-02-25

Supported by

Project supported by the National Natural Science Foundation of China (Nos.20903017, 21073189);Dalian Science and Technology Foundation (No. 2010J21DW010) and China Postdoctoral Science Foundation (No.20080431141).

摘要

用TG-DTG 方法研究了丹参的有效成分丹酚酸B 的热降解过程. 热重分析结果表明该物质的失重过程分两步进行. 笫一步为脱去吸附水, 其温度范围为305~373 K, 第二步为丹酚酸B 分子骨架大规模降解, 其温度范围在413~864 K. 用Friedman 和Ozawa-Flynn-Wall 两种方法分别计算出该药物降解过程中的三个阶段的活化能, 采用多步线性回归方法, 并参考常用的15 种热解机理函数, 确定了丹酚酸B 热降解过程最佳动力学模型为Fn-F2-F1.

本文引用格式

王韶旭 , 谭志诚 , 车如心 , 李彦生 . 丹酚酸B的热稳定性及其热分解动力学研究[J]. 化学学报, 2012 , 70(02) : 212 -216 . DOI: 10.6023/A1104075

Abstract

The processes of thermal decomposition of salvianolic acid B were studied by TG-DTG. The TG-DTG curves showed that the process of mass loss of the substance proceeded in two steps. The first step could be attributed to the expulsion of water in the temperature range of 305~373 K. The second step was corresponding to the large scale degradation of salvianolic acid B in the temperature range of 413~864 K.The activation energies E of thermal degradation process of three stages were obtained by Friedman method and Ozawa-Flynn-Wall method. According to 15 mechanism functions, the possible kinetic model of thermal degradation process was estimated to be Fn-F2-F1 through the multiple linear regression method.

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