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Optimization of CaO–Ni Blends for Enhanced CO 2 Adsorption: Aspen Plus Simulation Study

Carbon capture and storage (CCS) technologies are essential for mitigating global CO 2 emissions, yet challenges such as high energy consumption and material degradation hinder their widespread adoption. This study… Click to show full abstract

Carbon capture and storage (CCS) technologies are essential for mitigating global CO 2 emissions, yet challenges such as high energy consumption and material degradation hinder their widespread adoption. This study investigates the integration of nickel (Ni) into calcium oxide (CaO) sorbents to enhance CO 2 capture efficiency by leveraging Ni's catalytic properties to optimize carbonation kinetics. Aspen Plus simulations were employed to evaluate the effects of varying Ni concentrations (5–25 wt%) on reaction rates, activation energy, and carbonation efficiency. The results revealed that adding Ni considerably reduced the activation energy from 178 kJ/mol (pure CaO) to 70–90 kJ/mol. The maximum catalytic efficiency was achieved at 20 wt% Ni. At this concentration, the rate of the carbonation reaction increased exponentially, leading to considerable improvements in CO 2 collection and CaCO 3 formation rates. Sensitivity analysis identified key operational parameters, such as temperature, CO 2 partial pressure, and flow rates, for improving process optimization in industrial settings. In comparison to typical CaO‐based sorbents, Ni–CaO blends demonstrated higher catalytic efficiency and lower energy needs, addressing key challenges in CCS systems. This work distinguishes itself from previous CaO stability studies by integrating process optimization and kinetic modeling, resulting in practical insights for the development of energy‐efficient CO 2 capture technologies. Future research ought to explore the long‐term stability of Ni–CaO sorbents and incorporate renewable energy sources to increase the sustainability and economic feasibility of CCS systems.

Keywords: cao blends; energy; cao; study; aspen plus; optimization

Journal Title: Greenhouse Gases: Science and Technology
Year Published: 2025

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