80 citations · 279 across the 12 of their papers we have counts for
3 papers · 1 filter
Understanding the language of molecules: Predicting pure component parameters for the PC-SAFT equation of state from SMILES
Benedikt Winter, Philipp Rehner, Timm Esper +2
A major bottleneck in developing sustainable processes and materials is a lack of property data. Recently, machine learning approaches have vastly improved previous methods for pre…
SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients
Benedikt Winter, Clemens Winter, Timm Esper +2
The availability of property data is one of the major bottlenecks in the development of chemical processes, often requiring time-consuming and expensive experiments or limiting the…
A smile is all you need: Predicting limiting activity coefficients from SMILES with natural language processing
Benedikt Winter, Clemens Winter, Johannes Schilling +1
Knowledge of mixtures' phase equilibria is crucial in nature and technical chemistry. Phase equilibria calculations of mixtures require activity coefficients. However, experimental…