FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4376130007> ?p ?o ?g. }

• W4376130007 endingPage "122066" @default.
• W4376130007 startingPage "122066" @default.
• W4376130007 abstract "Ionic liquids (ILs) with many unique features can act as green solvents to dissolve some gases. In this study, two databases are collected to predict the CO2 and N2 solubility in various kinds of ILs with different temperature and pressure ranges. Firstly, 13,055 CO2 solubility data in 164 kinds of ILs and 415 N2 solubility data in 38 kinds of ILs are established. The hundreds of ILs are divided into dozens of ionic fragments (IFs). Then, the quantitative structure–property relationship (QSPR) model is built by combining ionic fragments contribution (IFC) with support vector machine (SVM) and artificial neural network (ANN) to establish the relationship between gas solubility and ILs structure. As a result, for CO2 solubility prediction, the determination of coefficient (R2) is 0.9855 and 0.9732 for training sets by IFC-SVM and IFC-ANN, respectively, while for N2 solubility prediction, the R2 is 0.9966 and 0.9909 for training sets by IFC-SVM and IFC-ANN, respectively. The result indicates that both IFC-SVM and IFC-ANN models can accurately and reliably predict CO2 and N2 solubility in ILs, so as to guide the screening of ILs." @default.
• W4376130007 created "2023-05-12" @default.
• W4376130007 creator A5041756956 @default.
• W4376130007 creator A5055814385 @default.
• W4376130007 creator A5059710195 @default.
• W4376130007 creator A5067206054 @default.
• W4376130007 date "2023-08-01" @default.
• W4376130007 modified "2023-10-16" @default.
• W4376130007 title "Prediction of CO2 and N2 solubility in ionic liquids using a combination of ionic fragments contribution and machine learning methods" @default.
• W4376130007 cites W1968604316 @default.
• W4376130007 cites W1988017792 @default.
• W4376130007 cites W1994204840 @default.
• W4376130007 cites W1999744067 @default.
• W4376130007 cites W2002932065 @default.
• W4376130007 cites W2015236127 @default.
• W4376130007 cites W2029945563 @default.
• W4376130007 cites W2040459007 @default.
• W4376130007 cites W2042169428 @default.
• W4376130007 cites W2065354989 @default.
• W4376130007 cites W2075613930 @default.
• W4376130007 cites W2083639134 @default.
• W4376130007 cites W2109102162 @default.
• W4376130007 cites W2131379134 @default.
• W4376130007 cites W2192572818 @default.
• W4376130007 cites W2213261723 @default.
• W4376130007 cites W2337824365 @default.
• W4376130007 cites W2561941619 @default.
• W4376130007 cites W2767789117 @default.
• W4376130007 cites W2770934075 @default.
• W4376130007 cites W2883170559 @default.
• W4376130007 cites W2890157002 @default.
• W4376130007 cites W2919124420 @default.
• W4376130007 cites W2946645832 @default.
• W4376130007 cites W2947264857 @default.
• W4376130007 cites W2966708832 @default.
• W4376130007 cites W2966935623 @default.
• W4376130007 cites W3021934323 @default.
• W4376130007 cites W3093358822 @default.
• W4376130007 cites W3099314753 @default.
• W4376130007 cites W3114912503 @default.
• W4376130007 cites W3119609586 @default.
• W4376130007 cites W3120426010 @default.
• W4376130007 cites W3126825433 @default.
• W4376130007 cites W3158983985 @default.
• W4376130007 cites W3195820802 @default.
• W4376130007 cites W3199785022 @default.
• W4376130007 cites W3207144108 @default.
• W4376130007 cites W4200205693 @default.
• W4376130007 cites W4200211969 @default.
• W4376130007 cites W4210271265 @default.
• W4376130007 cites W4213277611 @default.
• W4376130007 cites W4221021414 @default.
• W4376130007 cites W4226334071 @default.
• W4376130007 cites W4239510810 @default.
• W4376130007 cites W4246112865 @default.
• W4376130007 cites W4288046500 @default.
• W4376130007 cites W4300772148 @default.
• W4376130007 doi "https://doi.org/10.1016/j.molliq.2023.122066" @default.
• W4376130007 hasPublicationYear "2023" @default.
• W4376130007 type Work @default.
• W4376130007 citedByCount "1" @default.
• W4376130007 crossrefType "journal-article" @default.
• W4376130007 hasAuthorship W4376130007A5041756956 @default.
• W4376130007 hasAuthorship W4376130007A5055814385 @default.
• W4376130007 hasAuthorship W4376130007A5059710195 @default.
• W4376130007 hasAuthorship W4376130007A5067206054 @default.
• W4376130007 hasConcept C12267149 @default.
• W4376130007 hasConcept C145148216 @default.
• W4376130007 hasConcept C147789679 @default.
• W4376130007 hasConcept C154881586 @default.
• W4376130007 hasConcept C154945302 @default.
• W4376130007 hasConcept C155574463 @default.
• W4376130007 hasConcept C161790260 @default.
• W4376130007 hasConcept C164126121 @default.
• W4376130007 hasConcept C178790620 @default.
• W4376130007 hasConcept C185592680 @default.
• W4376130007 hasConcept C186060115 @default.
• W4376130007 hasConcept C2182769 @default.
• W4376130007 hasConcept C41008148 @default.
• W4376130007 hasConcept C50644808 @default.
• W4376130007 hasConcept C71240020 @default.
• W4376130007 hasConcept C86803240 @default.
• W4376130007 hasConceptScore W4376130007C12267149 @default.
• W4376130007 hasConceptScore W4376130007C145148216 @default.
• W4376130007 hasConceptScore W4376130007C147789679 @default.
• W4376130007 hasConceptScore W4376130007C154881586 @default.
• W4376130007 hasConceptScore W4376130007C154945302 @default.
• W4376130007 hasConceptScore W4376130007C155574463 @default.
• W4376130007 hasConceptScore W4376130007C161790260 @default.
• W4376130007 hasConceptScore W4376130007C164126121 @default.
• W4376130007 hasConceptScore W4376130007C178790620 @default.
• W4376130007 hasConceptScore W4376130007C185592680 @default.
• W4376130007 hasConceptScore W4376130007C186060115 @default.
• W4376130007 hasConceptScore W4376130007C2182769 @default.
• W4376130007 hasConceptScore W4376130007C41008148 @default.
• W4376130007 hasConceptScore W4376130007C50644808 @default.
• W4376130007 hasConceptScore W4376130007C71240020 @default.
• W4376130007 hasConceptScore W4376130007C86803240 @default.

• next