Highly efficient patterning technique for silver nanowire electrodes by electrospray deposition and its application to self-powered triboelectric tactile sensor

A patterned transparent electrode is a crucial component of state-of-the-art wearable devices and optoelectronic devices. However, most of the patterning methods using silver nanowires (AgNWs), which is one of the outstanding candidate materials for the transparent electrode, wasted a large amount of unused AgNWs during the patterning process. Here, we report a highly efficient patterning of AgNWs using electrospray deposition with grounded electrolyte solution (EDGE). During electrospray deposition, a patterned electrolyte solution collector attracted AgNWs by strong electrostatic attraction and selectively deposited them only on the patterned collector, minimizing AgNW deposited elsewhere. The enhanced patterning efficiency was verified through a comparison between the EDGE and conventional process by numerical simulation and experimental validation. As a result, despite the same electrospray deposition conditions for both cases except for the existence of the electrolyte solution collector, the coverage ratio of AgNWs fabricated by the EDGE process was at least six times higher than that of AgNWs produced by the conventional process. Furthermore, the EDGE process provided high design flexibility in terms of not only the material of the substrate, including a polymer and a ceramic but also the shape of the substrate, including a 2D flat and 3D curved surface. As an application of the EDGE process, a self-powered touch sensor exploiting the triboelectric effect was demonstrated. Thus, the EDGE process would be utilized in further application in wearable or implantable devices in the field of biomedicine, intelligent robots, and human–machine interface.

Adaptive Edge Process Migration for IoT in Heterogeneous Fog and Edge Computing Environments

To address the latency issue of the cloud-centric IoT management systems, researchers have introduced fog and edge computing (FEC) architecture, which distributes the computational tasks and decision making from the distant cloud to the edge or near the edge of IoT network. Considering the need for dynamic process migration from the mobile sensors to other resources when the mobile sensors are unable to continue their tasks, the IoT system needs to provide a flexible mechanism that allows the mobile sensors to dynamically migrate their tasks to the other FEC resources at runtime. The paper proposes a resource-aware edge process migration (REM) scheme that is capable of optimising the process migration decision. To realise such a system and to validate the REM scheme, the authors have developed a framework called edge process-enabled internet of thing (EPIoT) host. The framework and the REM scheme are implemented and evaluated. The results have shown that the REM scheme is capable of enhancing the performance of the process migration in heterogeneous FEC environment.

Abstracting Synchronization Process in Workflow Involving Partial Synchronization Pattern

For the partial synchronization problem in integration of workflow process model with data model, this paper develops an algorithm through synchronization edges to get synchronization processes. Firstly, a workflow model called RTWD net is introduced. Then the concepts of synchronization edge, process, synchronization process, base process, process tree, data type and trace-set of types is given. Finally, an algorithm for abstracting the synchronization process and a case study is presented.