High process yield rates of thermoplastic nanofluidic devices using a hybrid thermal assembly technique†
Abstract
Over the past decade, thermoplastics have been used as alternative substrates to glass and Si for microfluidic devices because of the diverse and robust fabrication protocols available for thermoplastics that can generate high production rates of the desired structures at low cost and with high replication fidelity, the extensive array of physiochemical properties they possess, and the simple surface activation strategies that can be employed to tune their surface chemistry appropriate for the intended application. While the advantages of polymer microfluidics are currently being realized, the evolution of thermoplastic-based nanofluidic devices is fraught with challenges. One challenge is assembly of the device, which consists of sealing a cover plate to the patterned fluidic substrate. Typically, channel collapse or substrate dissolution occurs during assembly making the device inoperable resulting in low process yield rates. In this work, we report a low temperature hybrid assembly approach for the generation of functional thermoplastic nanofluidic devices with high process yield rates (>90%) and with a short total assembly time (16 min). The approach involves thermally sealing a high Tg (glass transition temperature) substrate containing the nanofluidic structures to a cover plate possessing a lower Tg. Nanofluidic devices with critical feature sizes ranging between 25–250 nm were fabricated in a thermoplastic substrate (Tg = 104 °C) and sealed with a cover plate (Tg = 75 °C) at a temperature significantly below the Tg of the substrate. Results obtained from sealing tests revealed that the integrity of the nanochannels remained intact after assembly and devices were useful for fluorescence imaging at high signal-to-noise ratios. The functionality of the assembled devices was demonstrated by studying the stretching and translocation dynamics of dsDNA in the enclosed thermoplastic nanofluidic channels.