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Development of a Deep Learning-Based Group Contribution Framework for Targeted Design Ionic Liquid

https://doi.org/10.2139/ssrn.4711288
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inferredcites →https://doi.org/10.1002/aic.13910openalex-extracted
A new fragment contribution‐corresponding states method for physicochemical properties prediction of ionic liquids
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A Rational Approach to CO2 Capture by Imidazolium Ionic Liquids: Tuning CO2 Solubility by Cation Alkyl Branching
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Measurement of CO2 solubility in cyanide anion based ionic liquids; [c4mim][SCN], [c4mim][N(CN)2], [c4mim][C(CN)3]
inferredcites →https://doi.org/10.1016/j.cej.2022.136767openalex-extracted
Advances in applications of ionic liquids for phase change CO2 capture
inferredcites →https://doi.org/10.1016/j.compchemeng.2021.107522openalex-extracted
Modeling and optimization of ionic liquid-based carbon capture process using a thin-film unit
inferredcites →https://doi.org/10.1016/j.compchemeng.2022.107925openalex-extracted
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective
inferredcites →https://doi.org/10.1016/j.compstruct.2020.112654openalex-extracted
Optimal filler content for cotton fiber/PP composite based on mechanical properties using artificial neural network
inferredcites →https://doi.org/10.1016/j.compstruct.2020.112885openalex-extracted
Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
inferredcites →https://doi.org/10.1016/j.envint.2019.105189openalex-extracted
Environmental odour management by artificial neural network – A review
inferredcites →https://doi.org/10.1016/j.fluid.2020.112898openalex-extracted
Application of Artificial Intelligence-based predictive methods in Ionic liquid studies: A review
inferredcites →https://doi.org/10.1016/j.jclepro.2016.11.064openalex-extracted
An optimization approach for CO2 capture using ionic liquids
inferredcites →https://doi.org/10.1016/j.molliq.2016.11.123openalex-extracted
A review of ionic liquids: Applications towards catalytic organic transformations
inferredcites →https://doi.org/10.1016/j.molliq.2021.118418openalex-extracted
Modeling of H2S solubility in ionic liquids using deep learning: A chemical structure-based approach
inferredcites →https://doi.org/10.1016/j.molliq.2022.118546openalex-extracted
Machine learning for the prediction of viscosity of ionic liquid–water mixtures
inferredcites →https://doi.org/10.1016/j.neunet.2014.09.003openalex-extracted
Deep learning in neural networks: An overview
inferredcites →https://doi.org/10.1016/j.rser.2018.07.004openalex-extracted
A systematic review on CO2 capture with ionic liquids: Current status and future prospects
inferredcites →https://doi.org/10.1016/j.scitotenv.2021.148081openalex-extracted
Current and future perspectives on catalytic-based integrated carbon capture and utilization
inferredcites →https://doi.org/10.1016/j.supflu.2014.11.009openalex-extracted
Connectionist technique estimates H2S solubility in ionic liquids through a low parameter approach
inferredcites →https://doi.org/10.1021/acs.chemrev.7b00072openalex-extracted
Ionic-Liquid-Based CO2 Capture Systems: Structure, Interaction and Process
inferredcites →https://doi.org/10.1021/ie900250gopenalex-extracted
Critical Properties of Ionic Liquids. Revisited
inferredcites →https://doi.org/10.1021/ja039615xopenalex-extracted
Why Is CO2 So Soluble in Imidazolium-Based Ionic Liquids?
inferredcites →https://doi.org/10.1021/je400542bopenalex-extracted
On the High-Pressure Solubilities of Carbon Dioxide in Several Ionic Liquids
inferredcites →https://doi.org/10.1080/00268976.2019.1652367openalex-extracted
Prediction carbon dioxide solubility in ionic liquids based on deep learning
inferredcites →https://doi.org/10.1080/00268976.2022.2124203openalex-extracted
Intelligent prediction model of ammonia solubility in designable green solvents based on microstructure group contribution
inferredcites →https://doi.org/10.3390/app12052408openalex-extracted
Machine-Learning Model Prediction of Ionic Liquids Melting Points
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