Here, we capitalize on several of these co-current developments to revisit the problem of postcombustion carbon capture. Given previous efforts in this field, we impose the following constraints on our approach from the outset: i) instead of performing computational screening, we employ a generative approach, accelerated by efficient ML models; ii) the hypothetical MOFs should be based on realistic building blocks that have been previously used and reported in successful experimental syntheses of MOFs; iii) the performance of the generated materials is evaluated at the process level on a consistent basis with previous studies.