Data-driven multi-objective molecular design of ionic liquid with high generation efficiency on small dataset

Data-driven multi-objective molecular design of ionic liquid with high generation efficiency on small dataset

Ionic liquids (ILs) are promising electrolytes or solvents for numerous applications owing to their unique properties. However, it is a challenge to design the ideal IL with the required properties. Variational autoencoders (VAEs) trained by significantly large datasets have shown good performance i...

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Bibliographic Details
Main Authors: Chu, J. (Author), He, M. (Author), Liu, X. (Author), Zhang, Z. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2022
Subjects:
Auto encoders
Data driven
Efficiency
Generative model
Ionic liquid
Ionic liquids
Large dataset
Large datasets
Learning systems
Machine learning
Machine-learning
Molecular design
Molecules
Multi objective
Multiobjective optimization
Optimisations
Particle swarm optimization (PSO)
Property
Small data set
Specific heat
Thermal conductivity
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