Atom surface fragment contribution method for predicting the toxicity of ionic liquids

被引:0
|
作者
Kang, Xuejing [1 ]
Zhao, Yongsheng [2 ]
Chen, Zhongbing [1 ]
机构
[1] Department of Applied Ecology, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, Praha — Suchdol,16500, Czech Republic
[2] Department of Chemical Engineering, University of California, Santa Barbara,CA,93106-5080, United States
关键词
Ionic liquids - Cell culture - Toxicity;
D O I
暂无
中图分类号
学科分类号
摘要
In this study, a novel method—atom surface fragment contribution (ASFC)—was proposed for assessing the properties of compounds. We developed a predictive model using the ASFC method based on the sigma surface areas (Sσ-surface) of fragments/groups for estimating the toxicity of ILs. A toxicity dataset of 140 ILs towards leukemia rat cell line (ICP-81) was gathered and employed to train and validate models. The Sσ-surface values of atoms in each group were firstly calculated from the COSMO profiles of cations and anions for ILs. Then the Sσ-surface values of 26 groups were obtained and used as input descriptors for modelling. The R2 and MSE of the built ASFC model were 0.924 and 0.071, respectively. Results indicate that the ASFC model developed by the new approach possesses great accuracy and reliability. In total, the ASFC method has extensive potential for the application of estimating diverse properties of ILs and other compounds due to its remarkable advantages. © 2021 Elsevier B.V.
引用
收藏
相关论文
共 50 条
  • [1] Atom surface fragment contribution method for predicting the toxicity of ionic liquids
    Kang, Xuejing
    Zhao, Yongsheng
    Chen, Zhongbing
    [J]. JOURNAL OF HAZARDOUS MATERIALS, 2022, 421
  • [2] A Group Contribution Method for Predicting the Freezing Point of Ionic Liquids
    Lazzus, Juan A.
    [J]. PERIODICA POLYTECHNICA-CHEMICAL ENGINEERING, 2016, 60 (04) : 273 - 281
  • [3] Strategy Combining Free Volume Theory and Fragment Contribution Corresponding State Method for Predicting Viscosities of Ionic Liquids
    Tu, Wenhui
    Zeng, Shaojuan
    Zhang, Xiaochun
    He, Xuezhong
    Liu, Lei
    Zhang, Suojiang
    Zhang, Xiangping
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, 58 (14) : 5640 - 5649
  • [4] A new method of Ionic Fragment Contribution-Gradient Boosting Regressor for predicting the infinite dilution activity coefficient of dichloromethane in ionic liquids
    Li, Kaikai
    Chang, Fei
    Shi, Sensen
    Jiang, Chongyang
    Bai, Yinge
    Dong, Haifeng
    Meng, Xianghai
    Wu, Jeffery C. S.
    Zhang, Xiangping
    [J]. FLUID PHASE EQUILIBRIA, 2023, 564
  • [5] A novel group contribution method in the development of a QSAR for predicting the toxicity (Vibrio fischeri EC50) of ionic liquids
    Luis, P.
    Ortiz, I.
    Aldaco, R.
    Irabien, A.
    [J]. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY, 2007, 67 (03) : 423 - 429
  • [6] An automated group contribution method in predicting aquatic toxicity: The diatomic fragment approach
    Casalegno, M
    Benfenati, E
    Sello, G
    [J]. CHEMICAL RESEARCH IN TOXICOLOGY, 2005, 18 (04) : 740 - 746
  • [7] Group Contribution Method for Predicting Melting Points of Imidazolium and Benzimidazolium Ionic Liquids
    Huo, Yan
    Xia, Shuqian
    Zhang, Yan
    Ma, Peisheng
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2009, 48 (04) : 2212 - 2217
  • [8] New Fragment Contribution-Corresponding States Method for Physicochemical Properties Prediction of Ionic Liquids
    Huang, Ying
    Dong, Haifeng
    Zhang, Xiangping
    Li, Chunshan
    Zhang, Suojiang
    [J]. AICHE JOURNAL, 2013, 59 (04) : 1348 - 1359
  • [9] Predicting diffusivities in liquids by the group contribution method
    Fei, WY
    Bart, HJ
    [J]. CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2001, 40 (06) : 531 - 535
  • [10] An ionic fragments contribution-COSMO method to predict the surface charge density profiles of ionic liquids
    Tu, Wenhui
    Bai, Lu
    Zeng, Shaojuan
    Gao, Hongshuai
    Zhang, Suojiang
    Zhang, Xiangping
    [J]. JOURNAL OF MOLECULAR LIQUIDS, 2019, 282 : 292 - 302