Module Overview
Carbon Capture, Utilization, and Storage (CCUS) is fundamental to global decarbonization efforts, enabling substantial reductions in greenhouse gas emissions, and helping the world reach the 2050 net-zero goals. Accurate prediction of CO₂ thermophysical properties in the presence of impurities is essential for the safe and efficient design of CCUS transport systems. This work presents a systematic study of impure CO₂ behavior using advanced equations of state, phase equilibrium modeling, and machine learning-physics hybrid methods. The objective is to improve density, viscosity, and phase behavior predictions for CO₂ mixtures relevant to pipeline transport. Results demonstrate improved accuracy across a wide range of pressures, temperatures, and impurity concentrations, contributing to more reliable CCUS system design and operation.
















