January 1, 2022Digital Discovery80 citationsOpen Access

A smile is all you need: predicting limiting activity coefficients from SMILES with natural language processing

BWBenedikt WinterETH Zurich CWClemens WinterOpenAI (United States)JSJohannes SchillingStrong Memorial Hospital

Key Points

Key points are not available for this paper at this time.

Abstract

SPT is a natural language processing model that predicts limiting activity coefficients from SMILES. High accuracy is achieved by pre-training the model on millions of synthetic data points and fine-tuning the model on limited experimental data.

问 AI

Bookmark

View Full Paper

Cite This Study

Winter et al. (Sat,) studied this question.

synapsesocial.com/papers/6a75513096d04a2f43f58c34 https://doi.org/https://doi.org/10.1039/d2dd00058j

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Measurements of different thermodynamic properties of systems containing ionic liquids and correlation of these properties using modified UNIFAC (Dortmund)2010 · 51 citations
2Group‐contribution estimation of activity coefficients in nonideal liquid mixtures1975 · 3,301 citations
3Accurate statistical associating fluid theory for chain molecules formed from Mie segments2013 · 532 citations
4Flexible heuristic algorithm for automatic molecule fragmentation: application to the UNIFAC group contribution model2019 · 44 citations
5Conductor-like Screening Model for Real Solvents: A New Approach to the Quantitative Calculation of Solvation Phenomena1995 · 4,120 citations

问 AI

Bookmark

View Full Paper