With the view of enhancing the functionality of label-free single molecule nanopore-based detection, we have designed and developed a highly robust, mechanically stable, integrated nanopipette-microfluidic device which combines the recognized advantages of microfluidic systems and the unique properties/advantages of nanopipettes. Unlike more typical planar solid-state nanopores, which have inherent geometrical constraints, nanopipettes can be easily positioned at any point within a microfluidic channel. This is highly advantageous, especially when taking into account fluid flow properties. We show that we are able to detect and discriminate between DNA molecules of varying lengths when motivated through a microfluidic channel, upon the application of appropriate voltage bias across the nanopipette. The effects of applied voltage and volumetric flow rates have been studied to ascertain translocation event frequency and capture rate. Additionally, by exploiting the advantages associated with microfluidic systems (such as flow control and concomitant control over analyte concentration/presence), we show that the technology offers a new opportunity for single molecule detection and recognition in microfluidic devices.

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With the increasing attention toward renewable platform chemicals, a considerable amount of reaction pathways are being investigated for the potential of scale-up and industrialization. Heat integration, as a key feature in the field of process engineering, needs to be taken into consideration when developing preliminary reaction networks producing value-added products. In this study, we introduce an optimization-based framework for the simultaneous process synthesis and heat integration with the goal of finding the most profitable biobased platform chemical and its production pathways from a number of alternatives. A process superstructure that consists of master reaction stages and lower-level separation stages is introduced to demonstrate the theory. With a novel variable discretization approach, the problem is formulated as a mixed integer linear programming model to determine the optimal reaction pathways and separation sequences along with the heat integration cascade using simple data. The solutions to the problem reveal key information of the optimal flowsheet such as the maximum economic performance the process can achieve and the minimum cooling and heating duties required resulting from the heat integration analysis. A case study is presented to illustrate the applicability of the proposed approach.