Although the present paper focused on the CO 2 chemisorption in liquid ammonia, the proposed methodology equally applies to study the reactive CO 2 adsorption in condensed phase amines with more complex chemical structure. Amino-polymers, for instance, are widely used for the direct capture of CO 2 from air. The computational efficiency and the quantum accuracy of machine learning potentials are key to investigate how the chemical structure of amino-polymers shapes their CO 2 adsorption affinity, paving the way to the computational screening of more efficient sorbents for the direct air capture of CO 2 .