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Updated: Jul 4, 2025

Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells
Published on: October 2, 2016
A non-equilibrium dissipation system with tunable molecular fuel flux
Jiayu Yang1, Tengfang Zhang1, Linghao Zhang1
1College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China. xinsu@mail.buct.edu.cn.
Abstract:
Cells convert macromolecule fuel into small molecule fuel through energy pathways, including glycolysis, the citric acid cycle, and oxidative phosphorylation. These processes drive vital dissipative networks or structures. Distinct from direct fuel (DF) utilization (directly acquire and utilize small molecule fuel), this macromolecule fuel mechanism is referred to as indirect fuel (IF) utilization, wherein the generation rate of small molecule fuel (fuel flux) can be effectively regulated. Here, we reported a bionic dissipation system with tunable fuel flux based on dynamic DNA nanotechnology. By regulating the rates of strand displacement and enzymatic reactions, we controlled the fuel flux and further tuned the strength of non-equilibrium transient states. Interestingly, we found that within a certain range, the fuel flux was positively correlated with the strength of the transient state. Once saturation was reached, it became negatively correlated. An appropriate fuel flux supports the maintenance of high-intensity non-equilibrium transients. Furthermore, we harnessed the dissipation system with tunable molecular fuel flux to regulate the dynamic assembly and disassembly of AuNPs. Different fuel fluxes resulted in varying assembly and disassembly rates and strengths for AuNPs, accomplishing a biomimetic process of regulating microtubule assembly through the control of fuel flux within living organisms. This work demonstrated a dissipation system with tunable molecular fuel flux, and we envision that this system holds significant potential for development in various fields such as biomimetics, synthetic biology, smart materials, biosensing, and artificial cells.
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