9,10-dioxo-octadecanedioic acid monomethyl ester | 115080-95-0

• 分子结构分类: 有机化合物 - 脂质和类脂质分子 - 脂肪酰基
• 英文名称: 9,10-dioxo-octadecanedioic acid monomethyl ester
• 英文别名: 9,10-Dioxo-octadecandisaeure-monomethylester
• CAS: 115080-95-0
• 化学式: C₁₉H₃₂O₆
• 分子量: 356.459
• InChiKey: HDLYLNRBZOTFOL-UHFFFAOYSA-N

物化性质

• 熔点：
  80-83 °C(Solv: ethyl acetate (141-78-6))
• 沸点：
  476.9±30.0 °C(Predicted)
• 密度：
  1.065±0.06 g/cm3(Predicted)

计算性质

• 辛醇/水分配系数(LogP)：
  3.84
• 重原子数：
  25.0
• 可旋转键数：
  17.0
• 环数：
  0.0
• sp3杂化的碳原子比例：
  0.79
• 拓扑面积：
  97.74
• 氢给体数：
  1.0
• 氢受体数：
  5.0

反应信息

• 作为产物：
  描述：

  alkaline earth salt of/the/ methylsulfuric acid 在 铬酸 、 丙酮 作用下， 生成 壬二酸 、 9,10-dioxo-octadecanedioic acid monomethyl ester
  参考文献：
  名称：

  Using Direct Current Resistivity Sounding and Geostatistics to Aid in Hydrogeological Studies in the Choshuichi Alluvial Fan, Taiwan

  摘要：

  AbstractGround water reservoirs in the Choshuichi alluvial fan, central western Taiwan, were investigated using direct‐current (DC) resistivity soundings at 190 locations, combined with hydrogeological measurements from 37 wells. In addition, attempts were made to calculate aquifer transmissivity from both surface DC resistivity measurements and geostatistically derived predictions of aquifer properties.DC resistivity sounding data are highly correlated to the hydraulic parameters in the Choshuichi alluvial fan. By estimating the spatial distribution of hydraulic conductivity from the kriged well data and the cokriged thickness of the correlative aquifer from both resistivity sounding data and well information, the transmissivity of the aquifer at each location can be obtained from the product of kriged hydraulic conductivity and computed thickness of the geoelectric layer. Thus, the spatial variation of the transmissivities in the study area is obtained.Our work is more comparable to Ahmed et al. (1988) than to the work of Niwas and Singhal (1981). The first “constraint” from Niwas and Singhal's work is a result of their use of linear regression. The geostatistical approach taken here (and by Ahmed et al. [1988]) is a natural improvement on the linear regression approach.

  DOI：

  10.1111/j.1745-6584.2002.tb02501.x