Two years ago, we described the first droplet digital PCR (ddPCR) system aimed at empowering all researchers with a tool that removes the substantial uncertainties associated with using the analogue standard, quantitative real-time PCR (qPCR). This system enabled TaqMan hydrolysis probe-based assays for the absolute quantification of nucleic acids. Due to significant advancements in droplet chemistry and buoyed by the multiple benefits associated with dye-based target detection, we have created a "second generation" ddPCR system compatible with both TaqMan-probe and DNA-binding dye detection chemistries. Herein, we describe the operating characteristics of DNA-binding dye based ddPCR and offer a side-by-side comparison to TaqMan probe detection. By partitioning each sample prior to thermal cycling, we demonstrate that it is now possible to use a DNA-binding dye for the quantification of multiple target species from a single reaction. The increased resolution associated with partitioning also made it possible to visualize and account for signals arising from nonspecific amplification products. We expect that the ability to combine the precision of ddPCR with both DNA-binding dye and TaqMan probe detection chemistries will further enable the research community to answer complex and diverse genetic questions.
Nikuradse’s [1] work on friction factors focused on the turbulent flow regime in addition to being performed in large diameter pipes. Laminar data was collected by Nikuradse, however only low relative roughness values were examined. A recent review by Kandlikar [2] showed that the uncertainties in the laminar region of Nikuradse’s experiments were very high, and his conclusion regarding no roughness effects in the laminar region is open to question. In order to conclusively resolve this discrepancy, we have experimentally determined the effects of relative roughness ranging from 0–5.18% in micro and minichannels on friction factor and critical Reynolds numbers. Reynolds numbers were varied from 30 to 7000 and hydraulic diameters ranged from 198μm to 1084μm. There is indeed a roughness effect seen in the laminar region, contrary to what is reported by Nikuradse. The resulting friction factors are well predicted using a set of constricted flow parameters. In addition to higher friction factors, transition to turbulence was observed at decreasing Reynolds numbers as relative roughness increased.
Nanoparticles and polymers have great potential for lowering cost and increasing functionality of printed sensors and electronics. However, creation of practical devices requires that many of these materials be patterned on a single substrate, and many current patterning processes can only handle a single material at a time, necessitating alignment of serial processing steps. Higher throughput and lower cost can be achieved by patterning multiple materials simultaneously. To this end, the microfluidic molding process is adapted to pattern various nanoparticle and polymer inks simultaneously, in a completely additive manner, with three-dimensional control and high relative positional accuracy between the different materials. A differential template distortion observed in channels containing different inks is analyzed and found to result from pressure force in the template due to flow of a highly viscous and highly concentrated ink in small channels. The resulting optimization between patterning speed and dimensional fidelity is discussed.
Recently, a set of new roughness parameters was proposed by Kandlikar et al. [1] and Taylor et al. [2] for reporting surface roughness as related to fluid flow. The average roughness Ra parameter is often used in microfluidic applications, but this parameter alone is insufficient for describing surface roughness; a specimen with deep grooves and sharp obstructions can share the same average roughness value as a relatively smooth surface with low uniform surface roughness. Since the average roughness parameter is broad, it is difficult to access the surface topography features that result from different machining processes or etches. A profilometer and a digital microscope are used to examine the surface roughness profiles of various materials submitted to different machining techniques. The materials studied will be similar to those used for microchannels including aluminum, stainless steel, copper, and silicon. Depending on the material, these samples are submitted to several machining processes including milling, grinding, fly cutting, and microfabrication techniques. These machining processes and microfabrication techniques are of practical interest in microfluidics applications. After studying the surface roughness patterns exhibited in these samples, the roughness parameters employed in some of the recent roughness models are evaluated. This study is expected to provide more understanding of assorted surface roughness.
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