Chemical Power Variability among Microscopic Robots in Blood Vessels

TL;DR

This work introduces a network-based model to quantify how variation in blood circulation—transit time, hematocrit, and tissue demand—affects oxygen availability and power for swarms of microscopic robots powered by glucose-oxygen fuel cells. By aggregating circulation into segments and applying conservation and mixing rules, the study shows that up to $10^{11}$ robots induce negligible tissue hypoxia, while $10^{12}$ can cause substantial depletion in long-path sectors such as legs, liver, and slow-spleen transit, with the minimum oxygen concentration occurring in long veins before merging with shorter-path blood. The authors propose mitigation strategies including onboard oxygen storage, location-aware power limits, adaptive path selection, patient-specific planning, and active mixing at merges, highlighting both safety implications and potential stigmergy-based swarm signaling. Overall, the results guide mission planning and hardware design for chemical-power microscopic robots, emphasizing the importance of circulation variation in safety assessments and real-time swarm control.

Abstract

Fuel cells using oxygen and glucose could power microscopic robots operating in blood vessels. Swarms of such robots can significantly reduce oxygen concentration, depending on the time between successive transits of the lung, hematocrit variation in vessels and tissue oxygen consumption. These factors differ among circulation paths through the body. This paper evaluates how these variations affect the minimum oxygen concentration due to robot consumption and where it occurs: mainly in moderate-sized veins toward the end of long paths prior to their merging with veins from shorter paths. This shows that tens of billions of robots can obtain hundreds of picowatts throughout the body with minor reduction in total oxygen. However, a trillion robots significantly deplete oxygen in some parts of the body. By storing oxygen or limiting their consumption in long circulation paths, robots can actively mitigate this depletion. The variation in behavior is illustrated in three cases: the portal system which involves passage through two capillary networks, the spleen whose slits significantly slow some of the flow, and large tissue consumption in coronary circulation.

Figures (23)

• Figure 1: Circulation from lungs to the rest of the body and back to the lungs.
• Figure 2: Concentration $c$ and flow $F$ near branches. (a) A vessel splits into two branches. (b) Two vessels merge into one.
• Figure 3: Graph of the circulation grouped by segments with similar properties. (a) Overall circuit. The large blue and red edges indicate the pulmonary circulation from the right heart through the lungs and to the left heart. The other edges are the systemic blood flow. (b) Detail of the flow through the portal system.
• Figure 4: Path flow and total transit time (on a log scale) indicated by the height and width of each bar, respectively. Each path is a full loop through both the systemic and pulmonary circulation. Path labels are the name of the first node along the path after leaving the heart in the graph shown in Fig. \ref{['fig.circulation']}. The total flow of these paths and their flow-weighted average transit time equal $F_{\textnormal{blood}}$ and $t_{\textnormal{blood}}$, respectively, given in Table \ref{['table.blood parameters']}.
• Figure 5: Schematic hematocrit profiles associated with the segments of the circulation model. Values range from $0.45$ in large vessels down to $0.33$ in capillaries, except for flow through the slow spleen compartment where hematocrit in capillaries is $0.71$. For clarity, the profiles show an exaggerated fraction of time in small vessels. Actual transit time through capillaries is one second, except for an extended transit through the slow compartment of the spleen. The arrows indicate the direction of flow. (a) Overall circuit. (b) Detail of the portal system.