Predicting Temperature?Dependent Activity Coefficients at Infinite Dilution Using Tensor Completion

Knowledge of thermodynamic properties mixtures is essential in many fields science and engineering. However, the experimental data usually scarce, so prediction methods are needed. Matrix completion have proven to be very successful predicting binary mixtures. In this approach, organized a matrix whose rows columns correspond two components, entries indicate value studied property at fixed conditions. present work, we extend concept tensor (TCMs). This allows account for variation depending on chosen The feasibility demonstrated by applying TCM predict activity coefficients infinite dilution. third dimension used describe influence temperature. shown yield better predictions than well-established UNIFAC method. Furthermore, proposed able learn unveil physical law describing temperature dependence from scarce mixture only.