Concurrent droplet charging and sorting by electrostatic actuation

This paper presents a droplet-based microfluidic device for concurrent droplet charging and sorting by electrostatic actuation. Water-in-oil droplets can be charged on generation by synchronized electrostatic actuation. Then, simultaneously, the precharged droplets can be electrostatically steered into any designated laminar streamline, thus they can be sorted into one of multiple sorting channels one by one in a controlled fashion. In this paper, we studied the size dependence of the water droplets under various relative flow rates of water and oil. We demonstrated the concurrent charging and sorting of up to 600 droplets∕s by synchronized electrostatic actuation. Finally, we investigated optimized voltages for stable droplet charging and sorting. This is an essential enabling technology for fast, robust, and multiplexed sorting of microdroplets, and for the droplet-based microfluidic systems.     

A microfluidic device for on-chip agarose microbead generation with ultralow reagent consumption

Water-in-oil microdroplets offer microreactors for compartmentalized biochemical reactions with high throughput. Recently, the combination with a sol-gel switch ability, using agarose-in-oil microdroplets, has increased the range of possible applications, allowing for example the capture of amplicons in the gel phase for the preservation of monoclonality during a PCR reaction. Here, we report a new method for generating such agarose-in-oil microdroplets on a microfluidic device, with minimized inlet dead volume, on-chip cooling, and in situ monitoring of biochemical reactions within the gelified microbeads. We used a flow-focusing microchannel network and successfully generated agarose microdroplets at room temperature using the “push-pull” method. This method consists in pushing the oil continuous phase only, while suction is applied to the device outlet. The agarose phase present at the inlet is thus aspirated in the device, and segmented in microdroplets. The cooling system consists of two copper wires embedded in the microfluidic device. The transition from agarose microdroplets to microbeads provides additional stability and facilitated manipulation. We demonstrate the potential of this method by performing on-chip a temperature-triggered DNA isothermal amplification in agarose microbeads. Our device thus provides a new way to generate microbeads with high throughput and no dead volume for biochemical applications.     

Computational investigations of the mixing performance inside liquid slugs generated by a microfluidic T-junction

Droplet-based microfluidics has gained extensive research interest as it overcomes several challenges confronted by conventional single-phase microfluidics. The mixing performance inside droplets/slugs is critical in many applications such as advanced material syntheses and in situ kinetic measurements. In order to understand the effects of operating conditions on the mixing performance inside liquid slugs generated by a microfluidic T-junction, we have adopted the volume of fluid method coupled with the species transport model to study and quantify the mixing efficiencies inside slugs. Our simulation results demonstrate that an efficient mixing process is achieved by the intimate collaboration of the twirling effect and the recirculating flow. Only if the reagents are distributed transversely by the twirling effect, the recirculating flow can bring in convection mechanism thus facilitating mixing. By comparing the mixing performance inside slugs at various operating conditions, we find that slug size plays the key role in influencing the mixing performance as it determines the amount of fluid to be distributed by the twirling effect. For the cases where short slugs are generated, the mixing process is governed by the fast convection mechanism because the twirling effect can distribute the fluid to the flow path of the recirculating flow effectively. For cases with long slugs, the mixing process is dominated by the slow diffusion mechanism since the twirling effect is insufficient to distribute the large amount of fluid. In addition, our results show that increasing the operating velocity has limited effects on improving the mixing performance. This study provides the insight of the mixing process and may benefit the design and operations of droplet-based microfluidics.     

Characterization of microfluidic mixing and reaction in microchannels via analysis of cross-sectional patterns

For the diagnosis of biochemical reactions, the investigation of microflow behavior, and the confirmation of simulation results in microfluidics, experimentally quantitative measurements are indispensable. To characterize the mixing and reaction of fluids in microchannel devices, we propose a mixing quality index (M_qi) to quantify the cross-sectional patterns (also called mixing patterns) of fluids, captured with a confocal-fluorescence microscope (CFM). The operating parameters of the CFM for quantification were carefully tested. We analyzed mixing patterns, flow advection, and mass exchange of fluids in the devices with overlapping channels of two kinds. The mixing length of the two devices derived from the analysis of M_qi is demonstrated to be more precise than that estimated with a commonly applied method of blending dye liquors. By means of fluorescence resonance-energy transfer (FRET), we monitored the hybridization of two complementary oligonucleotides (a FRET pair) in the devices. The captured patterns reveal that hybridization is a progressive process along the downstream channel. The FRET reaction and the hybridization period were characterized through quantification of the reaction patterns. This analytical approach is a promising diagnostic tool that is applicable to the real-time analysis of biochemical and chemical reactions such as polymerase chain reaction (PCR), catalytic, or synthetic processes in microfluidic devices.     

Droplet-based microfluidic washing module for magnetic particle-based assays

In this paper, we propose a continuous flow droplet-based microfluidic platform for magnetic particle-based assays by employing in-droplet washing. The droplet-based washing was implemented by traversing functionalized magnetic particles across a laterally merged droplet from one side (containing sample and reagent) to the other (containing buffer) by an external magnetic field. Consequently, the magnetic particles were extracted to a parallel-synchronized train of washing buffer droplets, and unbound reagents were left in an original train of sample droplets. To realize the droplet-based washing function, the following four procedures were sequentially carried in a droplet-based microfluidic device: parallel synchronization of two trains of droplets by using a ladder-like channel network; lateral electrocoalescence by an electric field; magnetic particle manipulation by a magnetic field; and asymmetrical splitting of merged droplets. For the stable droplet synchronization and electrocoalescence, we optimized droplet generation conditions by varying the flow rate ratio (or droplet size). Image analysis was carried out to determine the fluorescent intensity of reagents before and after the washing step. As a result, the unbound reagents in sample droplets were significantly removed by more than a factor of 25 in the single washing step, while the magnetic particles were successfully extracted into washing buffer droplets. As a proof-of-principle, we demonstrate a magnetic particle-based immunoassay with streptavidin-coated magnetic particles and fluorescently labelled biotin in the proposed continuous flow droplet-based microfluidic platform.     

Anti-oscillation and chaos control of the fractional-order brushless DC motor system via adaptive echo state networks

This paper proposes anti-oscillation and chaos control scheme for the fractional-order brushless DC motor system wherein there exist unknown dynamics, immeasurable states and chaotic oscillation. Aimed at immeasurable states, the high-gain observers with fast convergence are presented to obtain the information of system states. To compensate uncertainties existing in the dynamic system, a finite-time echo state network with a weight is proposed to approximate uncertain dynamics while its weight is tuned by a fractional-order adaptive law online. Meanwhile a fractional-order filter is introduced to deal with the repeated derivative of the backstepping. Based on the fractional-order Lyapunov stability criterion, the anti-oscillation and chaos control scheme integrated with a high-gain observer, an echo state network and a filter are proposed by using recursive steps of backstepping. The proposed scheme guarantees the boundedness of all signals of the closed-loop system in the sense of global asymptotic stability, and also suppresses chaotic oscillation. Finally, the effectiveness of our scheme is demonstrated by simulation results.     

Shape-tunable wax microparticle synthesis via microfluidics and droplet impact

Spherical and non-spherical wax microparticles are generated by employing a facile two-step droplet microfluidic process which consists of the formation of molten wax microdroplets in a flow-focusing microchannel and their subsequent off-chip crystallization and deformation via microdroplet impingement on an immiscible liquid interface. Key parameters on the formation of molten wax microdroplets in a microfluidic channel are the viscosity of the molten wax and the interfacial tension between the dispersed and continuous fluids. A cursory phase diagram of wax morphology transition is depicted depending on the Capillary number and the Stefan number during the impact process. A combination of numerical simulation and analytical modeling is carried out to understand the physics underlying the deformation and crystallization process of the molten wax. The deformation of wax microdroplets is dominated by the viscous and thermal effects rather than the gravitational and buoyancy effects. Non-isothermal crystallization kinetics of the wax illustrates the time dependent thermal effects on the droplet deformation and crystallization. The work presented here will benefit those interested in the design and production criteria of soft non-spherical particles (i.e., alginate gels, wax, and polymer particles) with the aid of time and temperature mediated solidification and off-chip crosslinking.     

Chaos control of the permanent magnet synchronous motor with time-varying delay by using adaptive sliding mode control based on DSC

This paper focuses on the problem of chaos control for the permanent magnet synchronous motor with chaotic oscillation, unknown dynamics and time-varying delay by using adaptive sliding mode control based on dynamic surface control. To reveal the mechanism of motor system and facilitate controller design, the dynamic behavior of the system is investigated. Nonlinear items of system model, upper bounds of time delays and their derivatives are taken as unknown in the overall process. A RBF neural network with an adaptive law, which eliminates restrictions on accurate model and parameters, is employed to cope with unknown dynamics. In order to solve issues such as chaotic oscillation, ‘explosion of complexity’ of backstepping, and chattering associated with sliding mode control, a sliding mode controller is developed within the framework of dynamic surface control by the hybrid of adaptive technology and RBF neural network. In addition, an appropriate Lyapunov function is employed to demonstrate the system stability. Finally, the feasibility of the proposed scheme is testified by simulation.     

Temperature-induced droplet coalescence in microchannels

This paper reports a technique for temperature-induced merging of droplets in a microchannel. The multiphase system consists of water droplet and oil as the dispersed phase and the carrying continuous phase. A resistive heater provides heating in a rectangular merging chamber. The temperature of the chamber is controlled by the voltage applied to the heater. The merging process of two neighboring droplets was investigated with different applied voltage, flow rate ratio between water and oil and total flowrate. Merging is found to be effective at high flow rate ratio, high temperature, and low total flowrate. The presented technique could be used for merging and mixing in droplet-based lab-on-a-chip platforms.     

Electronic circuit implementation of the chaotic Rulkov neuron model

Numerical integration is the most common and straightforward approach in computational neuroscience for the study of biological neuron models based on ordinary differential equations. For some purposes, numerical simulations are not enough due to the multiple bottlenecks in computer architectures. However, when electronic circuits are used to simulate in real time large arrays of coupled neurons, the simulations are much faster than the computer simulations. We present here an electronic implementation of a map-based neuron model, a chaotic Rulkov neuron model, that can be easily transferred on a large scale integration circuit and thus provide a framework for the simulation of large networks of neurons. The Rulkov model is a map-based neuron model that has a surprising abundance of features, such as periodic and chaotic spiking and bursting. The discrete time dynamics allows to tune the time scale of the circuit to the needs of the specific application. Since the circuit described here only uses 18 MOS transistors, it offers new perspectives for building large networks of neurons in a single device. This is very relevant for the analysis of large networks of coupled neurons in order to investigate its dynamics over the network and its synchronization properties.     

Integrated microfluidics system using surface acoustic wave and electrowetting on dielectrics technology

This paper presents integrated microfluidic lab-on-a-chip technology combining surface acoustic wave (SAW) and electro-wetting on dielectric (EWOD). This combination has been designed to provide enhanced microfluidic functionality and the integrated devices have been fabricated using a single mask lithographic process. The integrated technology uses EWOD to guide and precisely position microdroplets which can then be actuated by SAW devices for particle concentration, acoustic streaming, mixing and ejection, as well as for sensing using a shear-horizontal wave SAW device. A SAW induced force has also been employed to enhance the EWOD droplet splitting function.     

A “twisted” microfluidic mixer suitable for a wide range of flow rate applications

This paper proposes a new “twisted” 3D microfluidic mixer fabricated by a laser writing/microfabrication technique. Effective and efficient mixing using the twisted micromixers can be obtained by combining two general chaotic mixing mechanisms: splitting/recombining and chaotic advection. The lamination of mixer units provides the splitting and recombination mechanism when the quadrant of circles is arranged in a two-layered serial arrangement of mixing units. The overall 3D path of the microchannel introduces the advection. An experimental investigation using chemical solutions revealed that these novel 3D passive microfluidic mixers were stable and could be operated at a wide range of flow rates. This micromixer finds application in the manipulation of tiny volumes of liquids that are crucial in diagnostics. The mixing performance was evaluated by dye visualization, and using a pH test that determined the chemical reaction of the solutions. A comparison of the tornado-mixer with this twisted micromixer was made to evaluate the efficiency of mixing. The efficiency of mixing was calculated within the channel by acquiring intensities using ImageJ software. Results suggested that efficient mixing can be obtained when more than 3 units were consecutively placed. The geometry of the device, which has a length of 30 mm, enables the device to be integrated with micro total analysis systems and other lab-on-chip devices.     

Synthesizing antipodal chaotic waveforms

Chaotic waveforms are natural information carriers since a correspondence can be established between the symbolic dynamics of a chaotic oscillator and the symbols of a message. Message symbols can be efficiently encoded in a chaotic waveform by applying vanishingly small perturbations to an oscillator to guide its symbolic dynamics to follow a desired course. Recently, two chaotic hybrid dynamical systems were shown to have matched filters enabling robust reception of chaotic communication waveforms in the presence of noise. The first of these, the exact shift oscillator, produces waveforms with desirable properties similar to antipodal signaling, but a physical implementation may be difficult to control using small perturbations. The second oscillator, the exact folded-band oscillator, produces less optimal waveforms but is more easily controlled. Here we introduce a method for generating waveforms of the exact shift oscillator by summing waveforms from a bank of easily controlled exact folded-band oscillators. We show that any solution of the exact shift oscillator can be so constructed using only three folded-band oscillators. Thus, this scheme allows us to realize the advantages of both chaotic systems while overcoming their individual disadvantages, thereby enabling practical chaos communications.     

Numerical modeling of DNA-chip hybridization with chaotic advection

We present numerical simulations of DNA-chip hybridization, both in the “static” and “dynamical” cases. In the static case, transport of free targets is limited by molecular diffusion; in the dynamical case, an efficient mixing is achieved by chaotic advection, with a periodic protocol using pumps in a rectangular chamber. This protocol has been shown to achieve rapid and homogeneous mixing. We suppose in our model that all free targets are identical; the chip has different spots on which the probes are fixed, also all identical, and complementary to the targets. The reaction model is an infinite sink potential of width d_h, i.e., a target is captured as soon as it comes close enough to a probe, at a distance lower than d_h. Our results prove that mixing with chaotic advection enables much more rapid hybridization than the static case. We show and explain why the potential width d_h does not play an important role in the final results, and we discuss the role of molecular diffusion. We also recover realistic reaction rates in the static case.     

Fuzzy control of dithered chaotic systems via neural-network-based approach

This paper presents an effective approach for controlling chaos. First, a neural-network (NN) model is employed to approximate the chaotic system. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of an NN model. Based on the LDI state-space representation, a fuzzy controller is proposed to tame the chaotic system. If the designed fuzzy controller cannot suppress the chaos, a high frequency signal, commonly called dithers, is simultaneously injected into the chaotic system. According to the relaxed method, an appropriate dither is introduced to steer the chaotic motion into a periodic orbit or a steady state. If the frequency of dither is high enough, the trajectory described by the dithered chaotic system and that of its corresponding mathematical model—the relaxed system can be made as close as desired. This phenomenon enables us to get a rigorous prediction of the dithered chaotic system’s behavior by obtaining the behavior of the relaxed system. Finally, a numerical example with simulations is given to illustrate the concepts discussed throughout this paper.     

Spatial effects on the stability of a food-limited moth population

Having obtained anomalous results in an attempt to continue the simulation study of moth-wasp interaction in Auslander, Oster and Huffaker (J. Franklin Inst. 297, 345-375), attention was centered on the role of spatial heterogeneity in an environment with the moth (Anagasta kühniella) alone. Because of the probable presence of chaotic components in the population behavior (random appearing behavior that is actually caused by deterministic influences), a statistically-based parameter sensitivity and parameter identification method was used. By defining a binary performance criterion that measured the ability of a model with a specific set of parameters to maintain a stable population, the importance of spatial heterogeneity was confirmed. In addition, the use of Monte-Carlo type simulation studies, combined with a binary performance criterion, was demonstrated to be effective for parameter identification and/or parameter sensitivity determination of at least some systems with chaotic or nearly chaotic behavior.     

An efficient simulation of the fractional chaotic system and its synchronization

The computational complexity of the numerical simulation of fractional chaotic system and its synchronization control is O(N²) compared with O(N) for integer chaotic system, where N is step number and O is the computational complexity. In this paper, we propose optimizing methods to solve fractional chaotic systems, including equal-weight memory principle, improved equal-weight memory principle, chaotic combination and fractional chaotic precomputing operator. Numerical examples show that the combination of these algorithms can simulate fractional chaotic system and synchronize the fractional master and slave systems accurately. The presented algorithms for simulation and synchronization of fractional chaotic system are up to 1.82 and 1.75 times faster than the original implementation respectively.     

Examination of chaotic behaviours using bond graph model

In this paper, modelling and simulation of Chua's chaotic oscillator, which exhibits rich chaotic behaviours, are presented by using the bond graph model. Up to now modelling of Chua's chaotic oscillator using bond graph model is not yet developed. The non-linear resistor in the circuit is modelled in this contribution by linear time-invariant components and ideal switches using piecewise linearization approach. The bond graph model of all the circuit including switches is then generated. Simulations are provided via the computer program called as BOMAS using the obtained bond graph model. Finally, Chua's circuit is verified experimentally. It is shown that all experimental and simulation results well agree with the chaotic behaviours of Chua's circuit.     

企业科技创新混沌动力学模型研究

基于混沌动力学模型,从企业科技创新的源起出发,深入分析其内外部动因及实现的基础与条件,并以此为基点,构建企业科技创新混沌动力学模型,为更好地揭示企业科技创新产生并发展的根本原因、更全面地了解企业当前面临的科技创新环境与自身能力,提供了科学而可靠的理论依据,具有重大的理论作用与现实意义。     

小波自反馈混沌神经网络的研究与应用

提出了小波自反馈混沌神经网络,分析了小波自反馈对混沌神经网络动力学行为的影响;将该暂态混沌网络模型应用于求解10城市旅行商问题(TSP),分析了小波自反馈对模拟退火的影响,得出了小波的自反馈是模拟退火的有效补充的结论;利用小波自反馈的伸缩平移优化了网络求解TSP的性能;最后研究了网络求解旅行商问题的内部状态的暂态混沌搜索、最大Lyapunov指数、混沌区域以及相空间的散度。实验仿真表明,小波自反馈的暂态混沌神经网络能够实现全局优化并具有较快的收敛速度。