Structure-property quantitative correlations for the density of primary normal alcohols

被引:0
|
作者
Khasanshin, TS [1 ]
机构
[1] Mogilev Technol Inst, Mogilev, BELARUS
关键词
D O I
暂无
中图分类号
O59 [应用物理学];
学科分类号
摘要
The procedure is proposed for calculating and predicting the density of liquid primary normal alcohols at temperatures from 293 to 498 K and pressures from 0.1 to 50 MPa, based on correlation for the classes of substances that form homologous series, in which the physicochemical properties change monotonically. The coefficients of a generalized function are calculated, depending on the temperature, pressure, and the number of carbon atoms in an alcohol molecule. The calculation results are compared with the initial data. The discrepancy for the most reliable data is less than 0.3%.
引用
收藏
页码:873 / 882
页数:10
相关论文
共 50 条
  • [21] Structurally diverse quantitative structure-property relationship correlations of technologically relevant physical properties
    Katritzky, AR
    Maran, U
    Lobanov, VS
    Karelson, M
    JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2000, 40 (01): : 1 - 18
  • [22] QUANTITATIVE STRUCTURE-PROPERTY RELATIONSHIPS FOR NORMAL SATURATED AND UNSATURATED FATTY-ACIDS
    DUTT, NVK
    KUMAR, YVLR
    VEDANAYAGAM, HS
    JOURNAL OF THE AMERICAN OIL CHEMISTS SOCIETY, 1992, 69 (12) : 1263 - 1265
  • [23] A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure
    Liu, Fengping
    Cao, Chenzhong
    Cheng, Bin
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2011, 12 (04): : 2448 - 2462
  • [24] Predicting normal densities of amines using quantitative structure-property relationship (QSPR)
    Stec, M.
    Spietz, T.
    Wieclaw-Solny, L.
    Tatarczuk, A.
    Krotki, A.
    SAR AND QSAR IN ENVIRONMENTAL RESEARCH, 2015, 26 (11) : 893 - 904
  • [25] In silico predictions of tablet density using a quantitative structure-property relationship model
    Hayashi, Yoshihiro
    Marumo, Yuki
    Takahashi, Takumi
    Nakano, Yuri
    Kosugi, Atsushi
    Kumada, Shungo
    Hirai, Daijiro
    Takayama, Kozo
    Onuki, Yoshinori
    INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2019, 558 : 351 - 356
  • [26] Prediction of density of aromatic explosives by quantitative structure-property relationships (QSPR) method
    Lai, Wei-Peng
    Lian, Peng
    Wang, Bo-Zhou
    Jia, Si-Yuan
    Zhang, Hai-Hao
    Xue, Yong-Qiang
    Pang, Xian-Yong
    Hanneng Cailiao/Chinese Journal of Energetic Materials, 2007, 15 (06): : 626 - 628
  • [27] Modeling of the physicochemical properties of aliphatic alcohols using topological indices and quantitative structure-property relationship
    Arjmand, F.
    Shafiei, F.
    BULGARIAN CHEMICAL COMMUNICATIONS, 2017, 49 (04): : 852 - 858
  • [28] A new descriptor for structure-property and structure-activity correlations
    Radic, M
    Basak, SC
    JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2001, 41 (03): : 650 - 656
  • [29] Platform of possibilities: Polyphosphazenes' structure-property correlations and applications
    Li, Zhongjing
    Allcock, Harry
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2017, 253
  • [30] Interpretation of quantitative structure-property and -activity relationships
    Katritzky, AR
    Petrukhin, R
    Tatham, D
    Basak, S
    Benfenati, E
    Karelson, M
    Maran, U
    JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES, 2001, 41 (03): : 679 - 685