Dissimilar material joining of polyamide 6 and polyethylene plates to a plain carbon steel (SPCC) plate was performed using friction lap joining. The polyamide 6 and SPCC plates could be directly joined by friction lap joining, whereas the polyethylene and SPCC plates could not. Corona discharge treatment of the polyethylene surface enabled the joint formation with SPCC. The tensile shear fracture load of the SPCC/polyamide 6 and SPCC/corona-discharge-treated polyethylene joints increased with the joining speed up to 600 mm min − 1 , beyond which it decreased. These joints were fractured at the base material of the plastic plate at optimal joining speeds in the tensile shear test. Continuously joined interfaces of these materials were observed via cross-sectional microstructure analysis. Transmission electron microscopy and selected area diffraction patterns indicated that these materials were joined through the surface oxide layer of SPCC composed of Fe 3 O 4 . The relation between the tensile shear fracture loads and the results of XPS analysis indicated that polar groups such as amide, hydroxyl, and carboxyl groups on the plastic surfaces were highly effective for joint formation of the SPCC/plastic joints.

Digital microfluidic biochips have become one of the most promising technologies in many biomedical fields. In a digital microfluidic biochip, a group of (adjacent) cells in the microfluidic array can be configured to work as storage, functional operations, as well as for transporting fluid droplets dynamically. There has been proposed a very efficient Integer Linear Programming (ILP)-based method to schedule operations with considering this dynamic reconfigurability. However, the method cannot directly deal with a case having an operation with multiple successors, which is necessary in some bioassays, e.g., sample preparation applications. Sample preparation is a crucial preprocessing step to produce droplets of the desired target concentrations from input reagents. In every optimized application graphs for sample preparation, there are many operations with more than one successors. Thus, the previous method cannot be used to get an optimal scheduling, and thus we propose a new framework to use another ILP formulation for scheduling operations in a digital microfluidic biochips. Our formulation can successfully deal with a case where there is a node with multiple successors. Also, our method can find a binding solution at the same time unlike the above-mentioned previous one thanks to our new ILP formulation. Although our ILP formulation seems to be a bit more complex than the previous one, a preliminary experiment demonstrates that the proposed ILP formulation can successfully find the optimal scheduling for practical sample preparation applications within a reasonable time.

No abstract