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A QSPR model for estimating Henry's law constant of H2S in ionic liquids by ELM algorithm

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F21%3A85351" target="_blank" >RIV/60460709:41330/21:85351 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0045653520329416?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0045653520329416?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.chemosphere.2020.128743" target="_blank" >10.1016/j.chemosphere.2020.128743</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A QSPR model for estimating Henry's law constant of H2S in ionic liquids by ELM algorithm

  • Original language description

    Ionic liquids (ILs) as green solvents have been studied in the application of gas sweetening. However, it is a huge challenge to obtain all the experimental values because of the high costs and generated chemical wastes. This study pioneered a quantitative structure-property relationship (QSPR) model for estimating Henrys law constant (HLC) of H2S in ILs. A dataset consisting of the HLC data of H2S for 22 ILs within a wide range of temperature (298,15-363,15 K) were collected from published reports. The electrostatic potential surface area (S-EP) and molecular volume of these ILs were calculated and used as input descriptors together with temperature. The extreme learning machine (ELM) algorithm was employed for nonlinear modelling. Results showed that the determination coefficient (R2) of the training set, test set and total set were 0,9996, 0,9989,0,9994, respectively, while the average absolute relative deviation (AARD%) of them were 1,3383, 2,4820 and 1,5820, respectively. The statistical paramet

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10511 - Environmental sciences (social aspects to be 5.7)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Chemosphere

  • ISSN

    0045-6535

  • e-ISSN

    1879-1298

  • Volume of the periodical

    269

  • Issue of the periodical within the volume

    128743

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    10

  • Pages from-to

    1-10

  • UT code for WoS article

    000631725000060

  • EID of the result in the Scopus database

    2-s2.0-85094954822