Design Software for Application-Specific Microfluidic Devices | Clinical Chemistry

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Microfluidics-based lab-on-a-chip systems, which feature miniaturization of biological separation and assay techniques, are rapidly transforming biochemical analysis and high-throughput screening. Microfluidic system design requires expertise in materials, chemistry, biology, and engineering, and understanding the complex interplay between variables that influence and limit system performance is difficult without computational assistance. Modeling approaches based on 3-dimensional numerical simulations provide detailed information regarding spatiotemporal variations of the field variables but are computationally very expensive for system-level analysis. Design-modeling tools are needed that rapidly simulate the complex underlying phenomena such as electroosmosis, electrophoresis, sample dispersion, mixing, and biochemical reactions without significantly compromising accuracy (1)(2)(3)(4)(5). In addition, these design tools must be easily usable by the microfluidic community, which comprises scientists and engineers from a variety of disciplines. To meet these challenges, we developed integrated design software that allows rapid layout of microfluidic channel networks, fast system performance simulation using a system solver, and the ability to easily reconfigure chip layout to meet specifications. We illustrate the application of the software to improve the design for an electrokinetic immunoassay chip.

The software design follows a modified form of the traditional client-server architecture. The user interacts with a graphical user interface (GUI) front-end (client). Fig. 1 shows a screenshot of the GUI. The microfluidic lab-on-a-chip system is represented as a network of interconnected components that can be assembled from a component library. The sequence of operations required for the creation of the microfluidic network, analysis, and visualization of results using the GUI is as follows:

(1) Creation of the microfluidic network: The components (such as sample reservoirs, straight channels, bends, biosensors, and interconnects such as Y-, T-, and cross junctions) are selected from the component library and assembled into a network using a drag-and-drop method.

(2) Problem specification: Geometric properties for components (channel length, breadth, and depth, turn radius and angle, well diameter) and operating conditions (applied voltage and pressure, flow rate, and injected analyte concentrations, as appropriate for the problem under consideration) are specified for the components. The property database contains physicochemical property data for commonly used buffers, reagents, and analytes (density and viscosity of buffers; electrical conductivity, and electrokinetic mobility and molecular diffusivity of analytes) and is fully integrated with the GUI.

(3) Solution and visualization: The performance is simulated using the system solver, and the results are analyzed using the visualization toolkit, which allows the results from the simulation to be displayed in a variety of tabular and graphical formats.

The GUI employs the hierarchical model-view-controller (MVC) architecture (6) to achieve the user-friendliness, flexibility, and extensibility needed. MVC programming uses 3-way factoring, whereby objects of different software classes take over the operations related to the application domain (model), the display of the application’s state (view), and the user interaction with the model and the view (controller). The MVC architecture is aimed at exploiting the benefits associated with modular components in the software. The GUI has been developed with the Java™ programming language using standard Java libraries and the included Swing toolkit(7).

(4) System solver: The system solver uses a combination of various modeling approaches for a rapid simulation of the microfluidic chip performance. This mixed-methodology approach uses an integral method to simulate fluid flow and electric field, a method of moments-based analytical solution to compute analyte dispersion, and a Fourier series–based analytical solution to compute microfluidic mixing based on laminar diffusion. These disparate models have been integrated in the system solver and validated against both experimental data and detailed 3-dimensional numerical models. The system solver shows a substantial improvement in computational speed (2–4 orders of magnitude) over the 3-dimensional models without appreciably compromising accuracy (error <10%). Details of the models and validation studies have been described elsewhere (4)(8)(9)(10). A brief explanation of these models is given below:

  • Fluid flow: Pressure-driven flow is calculated by solving the Navier-Stokes and continuity conservation equations in their integral forms. An implicit iterative numerical solution scheme based on the SIMPLE (semiimplicit method for pressure-linked equations) algorithm (11) is used. Details of the implementation are discussed elsewhere(8).

  • Electric field: The electric current conservation law is solved at every component with a constitutive equation to compute currents and voltages. These equations are used to compute the electroosmotic and electrophoretic flow velocity.

  • Analyte transport: An analytical model based on the method of moments approach has been developed to characterize the dispersion induced by combined pressure and electrokinetic-driven flow. In addition, the system solver uses a combination of numerical schemes and analytical approaches to simulate mixing due to laminar diffusion and biochemical reactions; specifically, the method of lines (MOL) and 2-compartment models for biochemical reactions, and a Fourier series-based model for analyte mixing.

We present the use of the microfluidic design software to improve the design of an electrokinetic microfluidic device for an on-chip assay of the drug theophylline (Th) in serum samples. The assay involves on-chip mixing of serum samples with a labeled tracer compound and reaction with a selective antibody. This reaction is followed by an electrophoresis-based separation step to isolate and quantify the reactants and products. This immunoassay method is appropriate for incorporation into a microfluidic format and allows for rapid separation, because of the short separation distances. Starting with the microfluidic device previously demonstrated (12), we applied the software to rapidly explore alternative design concepts to improve device performance and demonstrate the ability to create a lab-on-a-chip for a real clinical analysis using a simulation-based design approach. Similar analysis using an analog hardware description language (Verilog-A) has been previously reported(13).

The operation of the competitive immunoassay chip is a multistep process that includes (a) mixing of serum sample containing Th with fluorescein-labeled Th tracer (Th*), carried out in the microfluidic channel and based on laminar diffusion; (b) reaction of the resulting mixture with an anti-Th antibody (Ab), which allows Th and Th* to compete for a limited number of antibody-binding sites; (c) electrokinetic injection of the solution containing the Ab-Th* complex produced in the reaction, as well as the unreacted Th*, into the separation channel, where they are separated by electrophoresis; and (d) detection of the fluorescent species (Th* and Ab-Th*) by laser-induced fluorescence.

The chip layout was created in the layout editor, using the component library and the drag-and-drop methodology. The layout parameters (channel dimensions, connectivity) and operating conditions (voltages and concentrations) were specified, and the performance of the chip was simulated. All channels had a rectangular cross-section with a uniform depth of 20 microns. The original layout had channels with widths of 52–236 microns, and the same widths were used in the modified layout. Th and Th* in the sample were specified in the system design software as separate species with identical molecular diffusivity (3.3 × 10−10 m2/s) and electrokinetic mobility [2.84 × 10−8 m2/(V s)]. The corresponding properties for the antibody (Ab) were 4.0 × 10−11 m2/s (molecular diffusivity) and 4.45 × 10−8 m2/(V s) (electrokinetic mobility) (14). The binding between Th and Ab was assumed to be irreversible and complete. An electric field of 770 V/cm was used for electrophoretic separation. The performance was characterized by the extent of mixing/reaction and by the efficiency of separation, which is characterized by the separation resolution, peak height, variance, and time for separation. The layout was reconfigured using the layout editor to minimize the chip footprint. The modified layout (3.5 cm × 3.5 cm) occupies <25% of the area of the original chip (7.6 cm × 7.6 cm), and the time required for electrophoretic separation was decreased by more than 50% relative to the original design(12), thereby decreasing the overall assay time. This reconfiguration decreased the separation resolution, but the resulting resolution was still sufficient to resolve the species bands while limiting the band-broadening induced by dispersion. In addition, the signal amplitude increased by 11.5% and 5% for Ab-Th* and Th*, respectively. The degree of mixing for the antibody: Formula

where y is the widthwise coordinate, w is the channel width, c is the concentration profile along the channel width, and cavg is the average concentration along the width, was also improved to 100%. The entire analysis (including layout generation and problem setup) was completed in approximately 4 h, more than 2 orders of magnitude faster than currently available techniques. The improvements are summarized in Table 1 . In retrospect, the original system was substantially overdesigned, a problem that is common to several microfluidic systems currently available today and is attributable primarily to a lack of design tools.

In summary, the design software we describe is useful for estimating device performance and creating microfluidic chip layouts; these layouts can be rapidly modified to design chips that meet performance requirements. We used the software to improve the design of a microfluidic immunoassay chip. The resulting design occupied <25% of the area of the original chip, and the time required for electrophoretic separation was decreased by more than 50% relative to the original design, allowing for a faster assay. This process is more than 2 orders of magnitude faster than conventional design techniques and is ideally suited for design optimization of microfluidic lab-on-a-chip systems.




Continuous flow microreactors in nanoparticle synthesis | Syrris

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Although the pharmaceuticals industry has been the main driving force behind the rise of flow chemistry since early 2000, other chemicals-related industries have now taken an interest in this new laboratory technique. For years, organic synthesis has been the main focus of all research work conducted on flow chemistry equipment and the advantages offered by flow chemistry are now well established and documented.1-3 Other fields– such as biofuels, petrochemistry and nanoparticles – can also benefit from these same advantages.

Syrris has seen growing demand for Asia, its latest flow system (pictured below), from companies and universities specialising in nanoparticle synthesis. In addition, there has been an increasing number of publications on the subject of continuous formation of nanoparticles, quantum dots and colloidal metals.

Automated Asia Flow Chemistry System

Nowadays, nanoparticles are used in a wide range of fields because of their physical and chemical properties, resulting in a growing demand that challenges chemists to provide a reliable supply of large amounts of good quality nanoparticles.

Various chemical methods have been applied to produce nanoparticles in batch, but these all present problems: non-homogeneity in mixing, the importance of ageing, the difficulty of accurate temperature control and questionable reproducibility from batch to batch. Often a batch process relies as much on the skill of the chemist as on the chemistry itself.

All of these issues become even more difficult to address when scaling up the manufacturing. Flow chemistry offers a number of advantages that help to overcome these challenges, notably fast and reproducible mixing, excellent temperature control, the ability to carry out pressurised reactions, modularity and easy scale-up.

Accurate reaction control

One of the key characteristics of a flow chemistry system is the very small diameter of its internal wetted channels, which are typically in the range of 0.3-1 mm. This has a huge impact on both the quality of mixing and temperature control in microreactors.

The flow conditions in a system are defined by the Reynolds number (Re), i.e. the mean viscosity of fluid multiplied by characteristic dimension and divided by kinematic viscosity. For a low Reynolds number (below 4,000), flow conditions are laminar; for a high Reynolds number, they are turbulent. In a flow system, the channel dimension results in the Reynolds number always being small (usually <100), therefore flow conditions are always laminar.

Microreactor size (µl) Total flow rate (µl/min) Estimated mixing volume (µl) Estimated mixing time (secs) Residence time (mins)
1 62.5 60 3.3 3.30 1.04
2 62.5 240 6.6 1.65 0.26
3 250 240 12.6 3.15 1.04
4 250 1000 5.6 0.34 0.25
5 250 5000 5.6 0.07 0.05
6 1000 240 19.8 4.95 4.17
7 1000 1000 19.8 1.19 1.00
8 1000 5000 19.8 0.24 0.20

Table. 1 – Phenolphthalein & sodium hydroxide mixing tests

Under laminar flow conditions, mixing is diffusion-limited and extremely fast. Typically, in a Syrris microreactor the mixing is in the order of 1-5 seconds (Table 1). It is also very reproducible, as the shape of the microreactor does not change and no physical stirrer is involved.

Syrris Micromixer

Syrris Micromixer

The mixing time can be reduced even further to below one second, by using specially designed microreactors called micromixer chips (pictured right). This makes the micromixer chip a reactor of choice for nanoparticle synthesis protocols, where mixing is a critical parameter.

The small diameter of the microreactor channels also means that its surface-to-volume ratio is extremely high. This results in excellent heat transfer and fast, efficient temperature control and response. Not only is there no temperature gradient – as seen in a batch reactor – but any exotherm or endotherm is very quickly absorbed, maintaining a homogeneous temperature throughout the microreactor.

Prof. Seeberger and co-workers at the Max Planck Institute of Colloids & Interfaces noted the key role played by precise control over experimental conditions in a paper describing a process for continuous quantum dot synthesis in a glass microreactor.4 The quantum dots synthesised in flow by Seeberger’s group have a much narrower particle distribution than those obtained using a similar batch protocol. This trend has also been shown by Fitzner and co-workers for the preparation of colloidal gold in a flow microreactor.5

More recently, a continuous synthesis protocol for the synthesis of iron nanoparticles has been developed in Syrris’s laboratory. Here, the size of the particle is critical, as it determines its paramagnetic characteristics. Performing the synthesis in microreactors allowed ultra-fast mixing and, subsequently, the formation of fine magnetic iron nanoparticles with better quality and reproducibility than in batch synthesis.6

Process flexibility

Other advantages of using a flow system for making nanoparticles include easy scalability, the modularity of the system and the ability to carry out high pressure reactions and multi-step processes.

A flow chemistry system consisting of a pump, a microreactor and a pressure controller is a good starting point for nanoparticle synthesis. This system will allow the user to run a series of experiments to determine the best reaction conditions. Once the optimised reaction conditions have been established, the same set-up is used to synthesise multi-gram quantities of nanoparticles continuously in suspension.

By adding an autosampler and automating the system via software, the system’s capabilities are expanded and it becomes ideal for process optimisation and the study of reaction parameters. A series of experiments can quickly be set up, run automatically and all the samples collected separately for analysis. Fitzner and co-workers used this kind of set-up to study the effect of reaction temperature on the particle size distribution of colloidal gold.5

Flow chemistry systems are also very easily and safely pressurised using a back pressure regulator. This allows solvents to be heated above their boiling point, which is commonly called ‘superheating’, thus increasing the reaction kinetics and creating ultra-fast reaction conditions. On top of this, pressurising the system minimises any degassing effect that might occur when a reaction produces gas as a by-product.

Finally, microreactors and flow chemistry are ideal for multi-step processes, commonly called ‘telescoping synthesis’. By simply connecting the output of the first reactor to the input of a second, a two-step reaction can be set up. Seeberger’s group used this flow chemistry benefit in their quantum dot process. First, cadmium-selenium nanoparticles were formed in a microreactor, then the nanoparticles were covered with zinc sulphide in a second microreactor connected in series. This two-step reaction was run as one continuous process, therefore saving time and manual effort.4


Flow chemistry is as an effective technology for the optimisation of nanoparticle reactions and their large-scale synthesis. Among the key advantages of flow chemistry which can assist the nanoparticle industry are excellent reaction control, flexibility and easy scale-up. These benefits are of such importance that, in the near future, continuous-flow is likely to become the method of choice for nanoparticle synthesis.


  1. M. Drobot, Speciality Chemicals Magazine 2011, 31(6)
  2. C. Wiles & P. Watts, Green Chemistry 2012, 14, 38-54
  3. L. Malet-Sanz & F. Susanne, J. Med. Chem., forthcoming
  4. P. Laurino, R. Kikkeri & P.H. Seeberger, Nature 2011, 6, 1209-1220
  5. M. Wojnicki, K. Paclawski, M. Lutyblocho, K. Fitzner, P. Oakley & A. Stretton, Rudy I Metale Niezelane 2009, 12
  6. – a video of the experiment


Micro-reactors Produce Nanoparticles for Next-Generation Solar | Kurzweil

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solar_cell_nanoparticesEngineers at Oregon State University have determined that ethylene glycol, commonly used in antifreeze products, may be the key to making solar cells that cost less and avoid toxic compounds.

Ethylene glycol functions well in a “continuous flow” reactor — an approach to making thin-film solar cells that is easily scaled up for mass production at industrial levels, they note.

The research, published in Material Letters, a professional journal, also concluded this approach will work with CZTS, or copper zinc tin sulfide, a compound of significant interest for solar cells due to its excellent optical properties and the fact these materials are cheap and environmentally benign.

“The global use of solar energy may be held back if the materials we use to produce solar cells are too expensive or require the use of toxic chemicals in production,” said Greg Herman, an associate professor in the OSU School of Chemical, Biological and Environmental Engineering. “We need technologies that use abundant, inexpensive materials, preferably ones that can be mined in the U.S. This process offers that.”

By contrast, many solar cells today are made with CIGS, or copper indium gallium diselenide. Indium is comparatively rare and costly, and mostly produced in China. Last year, the prices of indium and gallium used in CIGS solar cells were about 275 times higher than the zinc used in CZTS cells.

The technology being developed at OSU uses ethylene glycol in meso-fluidic reactors that can offer precise control of temperature, reaction time, and mass transport to yield better crystalline quality and high uniformity of the nanoparticles that comprise the solar cell — all factors which improve quality control and performance.

This approach is also faster — many companies still use “batch mode” synthesis to produce CIGS nanoparticles, a process that can ultimately take up to a full day, compared to about half an hour with a continuous flow reactor. The additional speed of such reactors will further reduce final costs.


CONCEPT: Creating Gold Nanoparticles Using Low-Voltage Electrolysis

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CONCEPT: Creating Nanoparticles Using Laser Ablation | Particular Colloids

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CONCEPT: Making Nanoparticles Using Supercritical Water | Nottingham Science

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CONCEPT: Microfluidic Electrolysis Cell | Science Direct

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A single channel microfluidic electrolysis cell based on inexpensive materials and fabrication techniques is described. The cell is characterised using the electrochemistry of the Fe(CN)63−/Fe(CN)64− couple and its application in electrosynthesis is illustrated using the methoxylation reactions of N-formylpyrrolidine and 4-t-butyltoluene. It is shown that the reactions can be carried out with a good conversion in a single pass. The device, as described, allows the production of several mmol/hour of the methoxylated products.


  • Microflow reactor;
  • Electrolysis cell;
  • Methoxylation reactions
Full-size image (50 K)

Fig. 1. Schematic illustration of the microflow reactor showing the essential components of the electrolysis cell. The diameter of the electrodes was 100 mm. The cell was sealed under compression by 11 stainless steel bolts placed in insulating tubes.

Full-size image (35 K)

Fig. 2. Schematic of the experimental set up, where 1 – the solvent bottle, 2 – pump, 3 – 5 ml sample loop, 4 – microreactor, and 5 – collection vial.


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