This objective of this research is to decipher the fundamental knowledge required to accelerate the design of a new 3D-printable portlandite-based cementitious binder that permits CO2 uptake. Toward this end, this research aims: (i) to understand, control, and optimize the rheology of concentrated portlandite suspensions to enable printability, (ii) to refine portlandite carbonation routes at ambient temperature to maximize CO2 uptake to accelerate the carbonation kinetics, and (iii) to discover new multi-material 3D-printed metastructures with high load-bearing capability and optimal strength-to-weight ratio. This research relies on an iterative closed-loop integration of simulation (i.e., from electrons to continua), experimental, and machine learning activities that mutually inform and advance each other. The synergy between experimental and computational approaches will shed new light on interfacial reaction processes of mineral sorbents. This project will also advance the state of the art in our understanding of the rheology of concentrated suspensions, and elucidate the molecular design principles behind the discovery of polymers that permit the printability of concentrated slurries. Finally, by pioneering machine-learning-informed multi-material 3D-printing, this research will develop new methods to optimize the geometry and spatial distribution of metastructures that are light, stiff, and strong. Overall, by marrying the benefits of CO2 mineralization and 3D-printing, this work will result in pioneering intellectual contributions to accelerate the design of transformative construction materials with desirable properties and low carbon impact.