A review on artificial intelligence enabled design, synthesis, and process optimization of chemical products for industry 4.0
With the development of Industry 4.0, artificial intelligence (AI) is gaining increasing attention
for its performance in solving particularly complex problems in industrial chemistry and …
for its performance in solving particularly complex problems in industrial chemistry and …
Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategy
We present an extension of our Molecular Transformer model combined with a hyper-graph
exploration strategy for automatic retrosynthesis route planning without human intervention …
exploration strategy for automatic retrosynthesis route planning without human intervention …
Data augmentation and pretraining for template-based retrosynthetic prediction in computer-aided synthesis planning
This work presents efforts to augment the performance of data-driven machine learning
algorithms for reaction template recommendation used in computer-aided synthesis …
algorithms for reaction template recommendation used in computer-aided synthesis …
G2GT: retrosynthesis prediction with graph-to-graph attention neural network and self-training
Z Lin, S Yin, L Shi, W Zhou… - Journal of Chemical …, 2023 - ACS Publications
Retrosynthesis prediction, the task of identifying reactant molecules that can be used to
synthesize product molecules, is a fundamental challenge in organic chemistry and related …
synthesize product molecules, is a fundamental challenge in organic chemistry and related …
Machine learned prediction of reaction template applicability for data-driven retrosynthetic predictions of energetic materials
State of the art computer-aided synthesis planning models are naturally biased toward
commonly reported chemical reactions, thus reducing the usefulness of those models for the …
commonly reported chemical reactions, thus reducing the usefulness of those models for the …