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“Found in Translation”: predicting outcomes of complex organic chemistry reactions using neural sequence-to-sequence models† †Electronic supplementary information (ESI) available: Time-split test set
TLDR
Using a text-based representation of molecules, chemical reactions are predicted with a neural machine translation model borrowed from language processing. Expand
Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
TLDR
We show that a multihead attention Molecular Transformer model outperforms all algorithms in the literature, achieving a top-1 accuracy above 90% on a common benchmark data set. Expand
New QSPR Models to Predict the Critical Micelle Concentration of Sugar-Based Surfactants
Sugar-based surfactants represent a fruitful field of research in the context of sustainable chemistry since they can be obtained from renewable resources. In this work, new quantitative structureExpand
Mixture Descriptors toward the Development of Quantitative Structure–Property Relationship Models for the Flash Points of Organic Mixtures
Quantitative structure–property relationships (QSPRs) are increasingly used for the prediction of physicochemical properties of pure compounds, but only a few have been developed to predict theExpand
Molecular Transformer for Chemical Reaction Prediction and Uncertainty Estimation
TLDR
We show that a multi-head attention Molecular Transformer model outperforms all algorithms in the literature, achieving a top-1 accuracy above 90% on a common benchmark dataset. Expand
Combining mixing rules with QSPR models for pure chemicals to predict the flash points of binary organic liquid mixtures
Abstract Flash point is a key property of liquids to evaluate the safety of industrial processes. Mixing rules are commonly used to calculate the flash point of liquid mixtures, but they needExpand
Investigating the impact of sugar-based surfactants structure on surface tension at critical micelle concentration with structure-property relationships.
HYPOTHESIS Surface tension of aqueous solutions of surfactants at their critical micelle concentrations (γCMC), may be quantitatively linked to the surfactant structure using Quantitative StructureExpand
Conformations of n-alkyl-α/β-d-glucopyranoside surfactants: Impact on molecular properties
Abstract Sugar-based surfactants are amphiphilic compounds bearing a head group derived from sugar. Such surfactants represent a good alternative to petroleum-based surfactants, because they can beExpand
Non-equilibrium micelles formed by sugar-based surfactants under their Krafft temperature
Abstract Sugar-based surfactants are renewable substitutes to petroleum-based ones as wetting, dispersing and emulsifying agents in the formulation industry. In a substitution approach, knowledge ofExpand
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