Organic Rankine cycle (ORC) systems are a class of distributed power-generation systems
that are suitable for the efficient conversion of low-to-medium temperature thermal energy to …

We propose excess Gibbs free energy graph neural networks (GE-GNNs) for predicting
composition-dependent activity coefficients of binary mixtures. The GE-GNN architecture …

The bioavailability of poorly water-soluble active pharmaceutical ingredients (APIs) can be
improved via the formulation of an amorphous solid dispersion (ASD), where the API is …

We propose Gibbs–Duhem-informed neural networks for the prediction of binary activity
coefficients at varying compositions. That is, we include the Gibbs–Duhem equation …

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 …

Nucleic acids such as mRNA have emerged as a promising therapeutic modality with the
capability of addressing a wide range of diseases. Lipid nanoparticles (LNPs) as a delivery …

Drilling fluids exhibit complex rheological behavior due to a non-linear response to shear
rate variations and high sensitivity to changes in temperature, time, and pressure conditions …

Solvation free energy is an important design parameter in reaction kinetics and separation
processes, making it a critical property to predict during process development. In previous …