System-level comparison and techno-economic evaluation of structured metal–organic framework adsorbents for post-combustion CO2 capture by vacuum/pressure swing adsorption

• System-level evaluation of structured MOFs for CO 2 capture beyond isotherm metrics. • Techno-economic analysis including equipment sizing and column scheduling. • Impact of key operating and design variables on performance. • Structured UiO-66 achieves 72. 50 per ton of CO 2 captured with 95% purity and 88. 8% recovery. Shaping micron-sized metal–organic framework (MOF) powders into millimeter-sized structures addresses handling and processing challenges for practical CO 2 capture. However, most studies focus on simple metrics such as CO 2 uptake capacity and CO 2 /N 2 selectivity, often neglecting system-level cost considerations. Additionally, system-level modeling frequently relies on data generated from MOFs in powder form, without considering their structured variants. This study presents a systematic approach for data generation and evaluation of MOFs, namely UiO-66, MIL-101@GO, and ZIF-8, that have undergone polymer-aided structuring, using dynamic simulations of a cyclic vacuum/pressure swing adsorption (V/PSA) process for CO 2 capture and compression from the flue gas of a 550 MW coal-fired power plant. Parametric sensitivity analyses were performed, and the V/PSA process was optimized to maximize CO 2 purity and recovery while minimizing costs. Results show that the structured UiO-66 achieves a cost of 72. 50 per ton of CO 2 captured with 95 % purity and 88. 8 % recovery, which drops to 60. 60 per ton with 80 % recovery. Structured MIL-101@GO costs 75. 00 per ton for 96. 4 % purity and 88. 6 % recovery, while structured ZIF-8 costs 80. 20 per ton with 91. 2 % purity and 74. 4 % recovery. This study highlights the importance of using cost as a primary evaluation metric for structured adsorbents, integrating data from such adsorbents into system-level modeling, and optimizing cyclic adsorption processes with detailed equipment sizing and column scheduling to assess their feasibility for commercial-scale CO 2 capture.