Behavior of liquid plugs at bifurcations in a microfluidic tree network

Flows in complex geometries, such as porous media or biological networks, often contain plugs of liquid flowing within air bubbles. These flows can be modeled in microfluidic devices in which the geometric complexity is well defined and controlled. We study the flow of wetting liquid plugs in a bifurcating network of micro-channels. In particular, we focus on the process by which the plugs divide as they pass each bifurcation. The key events are identified, corresponding to large modifications of the interface curvature, the formation of new interfaces, or the division of a single interface into two new ones. The timing of the different events and the amplitude of the curvature variations are analyzed in view of the design of an event-driven model of flow in branching micro-networks. They are found to collapse onto a master curve dictated by the network geometry.     

Is graphite lithiophobic or lithiophilic?

Graphite and lithium metal are two classic anode materials and their composite has shown promising performance for rechargeable batteries. However, it is generally accepted that Li metal wets graphite poorly, causing its spreading and infiltration difficult. Here we show that graphite can either appear superlithiophilic or lithiophobic, depending on the local redox potential. By comparing the wetting performance of highly ordered pyrolytic graphite, porous carbon paper (PCP), lithiated PCP and graphite powder, we demonstrate that the surface contaminants that pin the contact-line motion and cause contact-angle hysteresis have their own electrochemical-stability windows. The surface contaminants can be either removed or reinforced in a time-dependent manner, depending on whether the reducing agents (C₆→LiC₆) or the oxidizing agents (air, moisture) dominate in the ambient environment, leading to bifurcating dynamics of either superfast or superslow wetting. Our findings enable new fabrication technology for Li–graphite composite with a controllable Li-metal/graphite ratio and present great promise for the mass production of Li-based anodes for use in high-energy-density batteries.     

Swimming direction reversal of flagella through ciliary motion of mastigonemes

Bio-inspired designs can provide an answer to engineering problems such as swimming strategies at the micron or nano-scale. Scientists are now designing artificial micro-swimmers that can mimic flagella-powered swimming of micro-organisms. In an application such as lab-on-a-chip in which micro-object manipulation in small flow geometries could be achieved by micro-swimmers, control of the swimming direction becomes an important aspect for retrieval and control of the micro-swimmer. A bio-inspired approach for swimming direction reversal (a flagellum bearing mastigonemes) can be used to design such a system and is being explored in the present work. We analyze the system using a computational framework in which the equations of solid mechanics and fluid dynamics are solved simultaneously. The fluid dynamics of Stokes flow is represented by a 2D Stokeslets approach while the solid mechanics behavior is realized using Euler-Bernoulli beam elements. The working principle of a flagellum bearing mastigonemes can be broken up into two parts: (1) the contribution of the base flagellum and (2) the contribution of mastigonemes, which act like cilia. These contributions are counteractive, and the net motion (velocity and direction) is a superposition of the two. In the present work, we also perform a dimensional analysis to understand the underlying physics associated with the system parameters such as the height of the mastigonemes, the number of mastigonemes, the flagellar wave length and amplitude, the flagellum length, and mastigonemes rigidity. Our results provide fundamental physical insight on the swimming of a flagellum with mastigonemes, and it provides guidelines for the design of artificial flagellar systems.     

Systematic characterization of degas-driven flow for poly(dimethylsiloxane) microfluidic devices

Degas-driven flow is a novel phenomenon used to propel fluids in poly(dimethylsiloxane) (PDMS)-based microfluidic devices without requiring any external power. This method takes advantage of the inherently high porosity and air solubility of PDMS by removing air molecules from the bulk PDMS before initiating the flow. The dynamics of degas-driven flow are dependent on the channel and device geometries and are highly sensitive to temporal parameters. These dependencies have not been fully characterized, hindering broad use of degas-driven flow as a microfluidic pumping mechanism. Here, we characterize, for the first time, the effect of various parameters on the dynamics of degas-driven flow, including channel geometry, PDMS thickness, PDMS exposure area, vacuum degassing time, and idle time at atmospheric pressure before loading. We investigate the effect of these parameters on flow velocity as well as channel fill time for the degas-driven flow process. Using our devices, we achieved reproducible flow with a standard deviation of less than 8% for flow velocity, as well as maximum flow rates of up to 3 nL∕s and mean flow rates of approximately 1-1.5 nL∕s. Parameters such as channel surface area and PDMS chip exposure area were found to have negligible impact on degas-driven flow dynamics, whereas channel cross-sectional area, degas time, PDMS thickness, and idle time were found to have a larger impact. In addition, we develop a physical model that can predict mean flow velocities within 6% of experimental values and can be used as a tool for future design of PDMS-based microfluidic devices that utilize degas-driven flow.     

Numerical simulation of intracellular drug delivery via rapid squeezing

Intracellular drug delivery by rapid squeezing is one of the most recent and simple cell membrane disruption-mediated drug encapsulation approaches. In this method, cell membranes are perforated in a microfluidic setup due to rapid cell deformation during squeezing through constricted channels. While squeezing-based drug loading has been successful in loading drug molecules into various cell types, such as immune cells, cancer cells, and other primary cells, there is so far no comprehensive understanding of the pore opening mechanism on the cell membrane and the systematic analysis on how different channel geometries and squeezing speed influence drug loading. This article aims to develop a three-dimensional computational model to study the intracellular delivery for compound cells squeezing through microfluidic channels. The Lattice Boltzmann method, as the flow solver, integrated with a spring-connected network via frictional coupling, is employed to capture compound capsule dynamics over fast squeezing. The pore size is proportional to the local areal strain of triangular patches on the compound cell through mathematical correlations derived from molecular dynamics and coarse-grained molecular dynamics simulations. We quantify the drug concentration inside the cell cytoplasm by introducing a new mathematical model for passive diffusion after squeezing. Compared to the existing models, the proposed model does not have any empirical parameters that depend on operating conditions and device geometry. Since the compound cell model is new, it is validated by simulating a nucleated cell under a simple shear flow at different capillary numbers and comparing the results with other numerical models reported in literature. The cell deformation during squeezing is also compared with the pattern found from our compound cell squeezing experiment. Afterward, compound cell squeezing is modeled for different cell squeezing velocities, constriction lengths, and constriction widths. We reported the instantaneous cell center velocity, variations of axial and vertical cell dimensions, cell porosity, and normalized drug concentration to shed light on the underlying physics in fast squeezing-based drug delivery. Consistent with experimental findings in the literature, the numerical results confirm that constriction width reduction, constriction length enlargement, and average cell velocity promote intracellular drug delivery. The results show that the existence of the nucleus increases cell porosity and loaded drug concentration after squeezing. Given geometrical parameters and cell average velocity, the maximum porosity is achieved at three different locations: constriction entrance, constriction middle part, and outside the constriction. Our numerical results provide reasonable justifications for experimental findings on the influences of constriction geometry and cell velocity on the performance of cell-squeezing delivery. We expect this model can help design and optimize squeezing-based cargo delivery.     

Salvinia-like slippery surface with stable and mobile water/air contact line

Superhydrophobic surfaces are widely used in many industrial settings, and mainly consist of rough solid protrusions that entrap air to minimize the liquid/solid area. The stability of the superhydrophobic state favors relatively small spacing between protrusions. However, this in turn increases the lateral adhesion force that retards the mobility of drops. Here we propose a novel approach that optimizes both properties simultaneously. Inspired by the hydrophobic leaves of Salvinia molesta and the slippery Nepenthes pitcher plants, we designed a Salvinia-like slippery surface (SSS) consisting of protrusions with slippery heads. We demonstrate that compared to a control surface, the SSS exhibits increased stability against pressure and impact, and enhanced lateral mobility of water drops as well as reduced hydrodynamic drag. We also systematically investigate the wetting dynamics on the SSS. With its easy fabrication and enhanced performance, we envision that SSS will be useful in a variety of fields in industry.     

Growth propagation of yeast in linear arrays of microfluidic chambers over many generations

The growth of microorganisms is often confined in restricting geometries. In this work, we designed a device to study the growth propagation of budding yeast along linear arrays of microfluidic chambers. Vacuum assisted cell loading was used to seed cells of limited numbers in the up-most chambers of each linear array. Once loaded, cells grow until confluent and then overgrow, pushing some of the newborns into the neighboring downstream chamber through connection channels. Such a scenario repeats sequentially along the whole linear chamber arrays. We observed that the propagation speed of yeast population along the linear arrays was strongly channel geometry dependent. When the connection channel is narrow and long, the amount of cells delivered into the downstream chamber is small so that cells grow over several generations in the same chamber before passing into the next chamber. Consequently, a population growth of more than 50 generations could be observed along a single linear array. We also provided a mathematical model to quantitatively interpret the observed growth dynamics.     

Zero dynamics and funnel control for linear electrical circuits

We consider electrical circuits containing linear resistances, capacitances and inductances. The circuits can be described by differential-algebraic input–output systems, where the input consists of voltages of voltage sources and currents of current sources and the output consists of currents of voltage sources and voltages of current sources. We generalize a characterization of asymptotic stability of the circuit and give sufficient topological criteria for its invariant zeros being located in the open left half-plane. We show that asymptotic stability of the zero dynamics can be characterized by means of the interconnectivity of the circuit and that it implies that the circuit is high-gain stabilizable with any positive high-gain factor. Thereafter we consider the output regulation problem for electrical circuits by funnel control. We show that for circuits with asymptotically stable zero dynamics, the funnel controller achieves tracking of a class of reference signals within a pre-specified funnel; this means in particular that the transient behavior of the output error can be prescribed and the funnel controller does neither incorporate any internal model for the reference signals nor any identification mechanism, it is simple in its design. The results are illustrated by a simulation of a discretized transmission line.     

Disrupting the wall accumulation of human sperm cells by artificial corrugation

Many self-propelled microorganisms are attracted to surfaces. This makes their dynamics in restricted geometries very different from that observed in the bulk. Swimming along walls is beneficial for directing and sorting cells, but may be detrimental if homogeneous populations are desired, such as in counting microchambers. In this work, we characterize the motion of human sperm cells ∼60 μm long, strongly confined to ∼25 μm shallow chambers. We investigate the nature of the cell trajectories between the confining surfaces and their accumulation near the borders. Observed cell trajectories are composed of a succession of quasi-circular and quasi-linear segments. This suggests that the cells follow a path of intermittent trappings near the top and bottom surfaces separated by stretches of quasi-free motion in between the two surfaces, as confirmed by depth resolved confocal microscopy studies. We show that the introduction of artificial petal-shaped corrugation in the lateral boundaries removes the tendency of cells to accumulate near the borders, an effect which we hypothesize may be valuable for microfluidic applications in biomedicine.     

Entry, exit and knowledge: evidence from a cluster in the info-communications industry

The process by which knowledge is created, accumulated and eventually destroyed appears crucial to many industrial dynamics patterns, since it shapes the profile of evolution of industries by favouring the entry of new companies, the co-existence of incumbents and new entrants and, eventually, their selective or joint exit over time. Though problematic, and all too often neglected, the connection between two nodes of interest, Industrial Dynamics on the one hand, and Knowledge Dynamics on the other hand, thus appears as a promising field of research. On the basis of a case study in the info-communications industry, we start by emphasizing that this field of research has direct importance at the empirical level. Knowledge dynamics can create specific models of evolution among firms at the local level, such as non-shakeout patterns within the cluster, which significantly differ from more global patterns of evolution in the info-communications industry, now generally oriented towards trends of decline and bust. We further argue in favour of the development of Knowledge-Based Industrial Dynamics, an approach that lies at the interface of industry and knowledge dynamics, and which can explain how a cluster may decrease the barriers to knowledge of clustered companies and, further, create a specific knowledge dynamics that is able to shape the industrial dynamics. Finally, we document how this process of knowledge dynamics was collectively implemented in our case study on the info-communications cluster and decompose the mechanisms that led to a local non-shakeout pattern of industrial dynamics. We conclude with some remarks on the policy implications.     

《新技术与创新的经济学》近期论文摘要——风险投资：干中学的捕食-食饵动态角色

本文指出“捕食一食饵”范例的内因动态,可以作为高风险投资密度的产业与产业投资力度呈“盛衰”局面的解释。风险投资商大都热衷于投资具有显著经历以及大量优秀投资机会的产业,基于该考量,我们设计了一个模型。然而,当投资“用尽”了所有机会后,便倾向于转而利用大量尚未开发的机遇。最终呈现出的产业层面的交互力度会自然而然地引起风险投资周期愈加趋向于研究者所观察的模式。     

Less is more: wiring-economical modular networks support self-sustained firing-economical neural avalanches for efficient processing

The brain network is notably cost-efficient, while the fundamental physical and dynamic mechanisms underlying its economical optimization in network structure and activity have not been determined. In this study, we investigate the intricate cost-efficient interplay between structure and dynamics in biologically plausible spatial modular neuronal network models. We observe that critical avalanche states from excitation-inhibition balance under modular network topology with less wiring cost can also achieve lower costs in firing but with strongly enhanced response sensitivity to stimuli. We derive mean-field equations that govern the macroscopic network dynamics through a novel approximate theory. The mechanism of low firing cost and stronger response in the form of critical avalanches is explained as a proximity to a Hopf bifurcation of the modules when increasing their connection density. Our work reveals the generic mechanism underlying the cost-efficient modular organization and critical dynamics widely observed in neural systems, providing insights into brain-inspired efficient computational designs.     

Threshold behavior in a stochastic delayed SIS epidemic model with vaccination and double diseases

In this paper, we investigate the threshold dynamics of a stochastic delayed SIS epidemic model with vaccination and double diseases which make the research more difficult. We establish sufficient conditions for extinction and persistence in the mean of the two diseases. We also obtain the threshold between persistence in the mean and extinction of the stochastic system. It is shown that: (i) time delay and environmental white noise have important effects on the persistence and extinction of the two diseases; (ii) the two diseases can coexist under certain conditions. Finally, some numerical simulations are provided to demonstrate the analytical results.     

两端锚定的单链聚电解质在交流电场中的滞后效应

在均匀的交流电场作用下,应用布朗动力学模拟方法,研究了两端锚定的柔性和半柔性的单链聚电解质的动力学行为。研究结果表明,链段的位置随交流电场的变化表现出类似于磁滞回线的滞后效应,随着交流电的频率减小,这种滞后效应运渐消失,成为一条单一的曲线。本项目针对两端锚定的聚电解质随交流电场变化的动力学行为的研究,文献中未见报道。     

Innovation and network structural dynamics: Study of the alliance network of a major sector of the biotechnology industry

We study the large-scale topology and dynamics of maps of alliances in a major segment of the biotechnology industry. The results point to the joint dynamics of network and innovation. The study demonstrates that the network is scale-free. Competition for links translates into a dynamic exponent that seems to follow the fitter-get-richer model of network growth, with preferential attachment to firms holding key technologies. This network also shows a small-world effect. This work highlights the strategic importance of understanding the growth dynamics and structure of collaboration networks for the building of leading positions in industries led by sustained radical change.     

Evaluating collaborative information-seeking interfaces with a search-oriented inspection method and re-framed information seeking theory

Despite the many implicit references to the social contexts of search within information seeking and retrieval research, there has been relatively little work that has specifically investigated the additional requirements for collaborative information-seeking interfaces. Here, we re-assess an existing analytical inspection framework, designed for individual information seeking, and then apply it to evaluate a recent collaborative information-seeking interface: SearchTogether. The framework was built upon two models of solitary information seeking, and so as part of the re-assessment we first re-frame the models for collaborative contexts. We re-frame a model of search tactics, providing revised definitions that consider known collaborators. We then re-frame a model of searcher profiles to analyse support for different group dynamics. After presenting an analysis of SearchTogether, we reflect on its accuracy, showing that the framework identified eight known truths, eight new insights, and no known-to-be-untrue insights into the design. We conclude that the framework: (a) can still be applied to collaborative information-seeking interfaces; (b) can successfully produce additional requirements for collaborative information-seeking interfaces; and (c) can successfully model different dynamics of collaborating searchers.     

Reconfiguring confined magnetic colloids with tunable fluid transport behavior

Collective dynamics of confined colloids are crucial in diverse scenarios such as self-assembly and phase behavior in materials science, microrobot swarms for drug delivery and microfluidic control. Yet, fine-tuning the dynamics of colloids in microscale confined spaces is still a formidable task due to the complexity of the dynamics of colloidal suspension and to the lack of methodology to probe colloids in confinement. Here, we show that the collective dynamics of confined magnetic colloids can be finely tuned by external magnetic fields. In particular, the mechanical properties of the confined colloidal suspension can be probed in real time and this strategy can be also used to tune microscale fluid transport. Our experimental and theoretical investigations reveal that the collective configuration characterized by the colloidal entropy is controlled by the colloidal concentration, confining ratio and external field strength and direction. Indeed, our results show that mechanical properties of the colloidal suspension as well as the transport of the solvent in microfluidic devices can be controlled upon tuning the entropy of the colloidal suspension. Our approach opens new avenues for the design and application of drug delivery, microfluidic logic, dynamic fluid control, chemical reaction and beyond.     

Enhancing sensitivity and specificity in rare cell capture microdevices with dielectrophoresis

The capture and subsequent analysis of rare cells, such as circulating tumor cells from a peripheral blood sample, has the potential to advance our understanding and treatment of a wide range of diseases. There is a particular need for high purity (i.e., high specificity) techniques to isolate these cells, reducing the time and cost required for single-cell genetic analyses by decreasing the number of contaminating cells analyzed. Previous work has shown that antibody-based immunocapture can be combined with dielectrophoresis (DEP) to differentially isolate cancer cells from leukocytes in a characterization device. Here, we build on that work by developing numerical simulations that identify microfluidic obstacle array geometries where DEP–immunocapture can be used to maximize the capture of target rare cells, while minimizing the capture of contaminating cells. We consider geometries with electrodes offset from the array and parallel to the fluid flow, maximizing the magnitude of the resulting electric field at the obstacles'' leading and trailing edges, and minimizing it at the obstacles'' shoulders. This configuration attracts cells with a positive DEP (pDEP) response to the leading edge, where the shear stress is low and residence time is long, resulting in a high capture probability; although these cells are also repelled from the shoulder region, the high local fluid velocity at the shoulder minimizes the impact on the overall transport and capture. Likewise, cells undergoing negative DEP (nDEP) are repelled from regions of high capture probability and attracted to regions where capture is unlikely. These simulations predict that DEP can be used to reduce the probability of capturing contaminating peripheral blood mononuclear cells (using nDEP) from 0.16 to 0.01 while simultaneously increasing the capture of several pancreatic cancer cell lines from 0.03–0.10 to 0.14–0.55, laying the groundwork for the experimental study of hybrid DEP–immunocapture obstacle array microdevices.     

Optimal jamming attack schedule for remote state estimation with two sensors

In cyber-physical systems (CPS), cyber threats emerge in many ways which can cause significant destruction to the system operation. In wireless CPS, adversaries can block the communications of useful information by channel jamming, incurring the so-called denial of service (DoS) attacks. In this paper, we investigate the problem of optimal jamming attack scheduling against remote state estimation wireless network. Specifically, we consider that two wireless sensors report data to a remote estimator through two wireless communication channels lying in two unoverlapping frequency bands, respectively. Meanwhile, an adversary can select one and only one channel at a time to execute jamming attack. We prove that the optimal attack schedule is continuously launching attack on one channel determined based on the system dynamics matrix. The theoretical results are validated by numerical simulations.