论文标题
在多孔培养基中的流动细菌分散
Dispersion of motile bacteria in a porous medium
论文作者
论文摘要
了解多孔培养基中细菌的流量和运输对于诸如生物修复,生物矿化或增强石油恢复等技术至关重要。尽管有充分的文献记录了物理化学细菌过滤,但最近的研究表明,细菌运动性在运输过程中起关键作用。在包含随机放置障碍物的微流体芯片中进行的流量和运输实验证实,非气动颗粒的分布保持紧凑,而对于机动菌株,分布的特征是显着的保留和快速的下游运动。对于运动细菌,对单个细菌轨迹的详细显微镜研究揭示了两个显着特征:(i)因运动性触发的主动保留过程的出现,(ii)由于固体晶粒固体晶粒维质性中快速流动通道和低流量区域之间的交换而增加了分散体。我们建议基于连续时间随机步行方法的物理模型。这种方法通过可变的孔隙尺度流速度通过马尔可夫模型来解释细菌的分散液。细菌的运动性是通过一个两率捕获过程来建模的,该过程解释了障碍物的运动和主动陷阱。这种方法捕获了观察到细菌位移分布的前尾,并量化了增强的流体动力分散效应,该效应起源于孔隙尺度和细菌运动的流动之间的相互作用。该模型重现了实验观察结果,并预测了宏观上的细菌分散和运输。
Understanding flow and transport of bacteria in porous media is crucial to technologies such as bioremediation, biomineralization or enhanced oil recovery. While physicochemical bacteria filtration is well-documented, recent studies showed that bacterial motility plays a key role in the transport process. Flow and transport experiments performed in microfluidic chips containing randomly placed obstacles confirmed that the distributions of non-motile particles stays compact, whereas for the motile strains, the distributions are characterized by both significant retention as well as fast downstream motion. For motile bacteria, the detailed microscopic study of individual bacteria trajectories reveals two salient features: (i) the emergence of an active retention process triggered by motility, (ii) enhancement of dispersion due to the exchange between fast flow channels and low flow regions in the vicinity of the solid grains. We propose a physical model based on a continuous time random walk approach. This approach accounts for bacteria dispersion via variable pore-scale flow velocities through a Markov model for equidistant particle speeds. Motility of bacteria is modeled by a two-rate trapping process that accounts for the motion towards and active trapping at the obstacles. This approach captures the forward tails observed for the distribution of bacteria displacements, and quantifies an enhanced hydrodynamic dispersion effect that originates in the interaction between flow at the pore-scale and bacterial motility. The model reproduces the experimental observations, and predicts bacteria dispersion and transport at the macroscale.