Scalable Swarm Intelligence for Atmospheric Carbon Remediation: Magnetic Microbot Ensembles with Metal-Organic Framework Functionalization

Direct air capture (DAC) of CO₂ remains constrained by the fundamental trade-off between sorbent surface area and parasitic energy costs. We propose a paradigm shift: rather than static, high-surface-area contactors, we investigate diffusive swarms of magnetically actuated microrobotic agents functionalized with Mg-MOF-74, a metal-organic framework exhibiting strong CO₂ affinity and rapid kinetics at the microscale. Through theoretical analysis and computational modeling, we demonstrate that miniaturization to the 10–50 µm scale exploits critical scaling advantages: the Linear Driving Force mass-transfer coefficient scales as k_LDF ∝ R⁻², yielding orders-of-magnitude acceleration relative to millimeter-scale pellets. The distributed viscous drag of a dilute swarm can circumvent the monolithic pressure-drop trap inherent to packed-bed systems. We model swarm transport via mean-field advection–diffusion equations, percolation theory for agent connectivity, and low-Reynolds-number helical propulsion physics. Preliminary analysis suggests magnetic microswarms could reduce electrical energy consumption by 30–50% relative to commercial DAC systems (Climeworks, Carbon Engineering) for equivalent throughput, contingent on recovery efficiency and actuation constraints. Deployment scenarios range from confined HVAC ducts (near-term viable) to open urban street canyons (higher risk, limited near-term viability). The approach raises critical questions of control scalability, environmental persistence, and the limits of decentralized systems. We argue that hybrid architectures leveraging global magnetic guidance and local emergent behavior offer a viable near-term path in confined, recoverable settings. This theoretical study establishes physical viability and identifies key engineering challenges for experimental development.