Lab-on-a-chip : a component view

Miniaturization is being increasingly applied to biological and chemical analysis processes. Lab-on-a-chip systems are direct creation of the advancement in the miniaturization of these processes. They offer a host of exciting applications in several areas including clinical diagnostics, food and environmental analysis, and drug discovery and delivery studies. This paper reviews lab-on-a-chip systems from their components perspective. It provides a categorization of the standard functional components found in lab-on-a-chip devices together with an overview of the latest trends and developments related to lab-on-a-chip technologies and their application in nanobiotechnology. The functional components include: injector, transporter, preparator, mixer, reactor, separator, detector, controller, and power supply. The components are represented by appropriate symbols allowing designers to present their lab-on-a-chip products in a standard manner. Definition and role of each functional component are included and complemented with examples of existing work. Through the approach presented in this paper, it is hoped that modularity and technology transfer in lab-on-a-chip systems can be further facilitated and their application in nanobiotechnology be expanded.

Modeling and simulation of a periodic grating coupled configuration for surface plasmon excitation

The deficiencies in the design of surface plasmon resonance (SPR) systems that are reported in numerous published works consistently identify the optics assembly as the main problem in the miniaturization of SPR sensors for integration into biosensor systems. This paper presents a novel design of a grating coupled optical waveguide surface plasmon (SP) excitation mechanism, investigated with the intention of addressing the problems associated with using the traditional prism input-output light coupling approach. Computational multiphysics modeling and simulation of the design is carried out. The results are presented and discussed.

Biocompatible ionic liquid-biopolymer electrolyte-enabled thin and compact magnesium-air batteries.

With the surge of interest in miniaturized implanted medical devices (IMDs), implantable power sources with small dimensions and biocompatibility are in high demand. Implanted battery/supercapacitor devices are commonly packaged within a case that occupies a large volume, making miniaturization difficult. In this study, we demonstrate a polymer electrolyte-enabled biocompatible magnesium-air battery device with a total thickness of approximately 300 μm. It consists of a biocompatible polypyrrole-para(toluene sulfonic acid) cathode and a bioresorbable magnesium alloy anode. The biocompatible electrolyte used is made of choline nitrate (ionic liquid) embedded in a biopolymer, chitosan. This polymer electrolyte is mechanically robust and offers a high ionic conductivity of 8.9 × 10(-3) S cm(-1). The assembled battery delivers a maximum volumetric power density of 3.9 W L(-1), which is sufficient to drive some types of IMDs, such as cardiac pacemakers or biomonitoring systems. This miniaturized, biocompatible magnesium-air battery may pave the way to a future generation of implantable power sources.

Energy efficient sleep schedule with service coverage guarantee in wireless sensor networks

Service oriented architecture has been proposed to support collaborations among distributed wireless sensor network (WSN) applications in an open dynamic environment. However, WSNs are resource constraint, and have limited computation abilities, limited communication bandwidth and especially limited energy. Fortunately, sensor nodes in WSNs are usually deployed redundantly, which brings the opportunity to adopt a sleep schedule for balanced energy consumption to extend the network lifetime. Due to miniaturization and energy efficiency, one sensor node can integrate several sense units and support a variety of services. Traditional sleep schedule considers only the constraints from the sensor nodes, can be categorized to a one-layer (i.e., node layer) issue. The service oriented WSNs should resolve the energy optimization issue considering the two-layer constraints, i.e., the sensor nodes layer and service layer. Then, the one-layer energy optimization scheme in previous work is not applicable for service oriented WSNs. Hence, in this paper we propose a sleep schedule with a service coverage guarantee in WSNs. Firstly, by considering the redundancy degree on both the service level and the node level, we can get an accurate redundancy degree of one sensor node. Then, we can adopt fuzzy logic to integrate the redundancy degree, reliability and energy to get a sleep factor. Based on the sleep factor, we furthermore propose the sleep mechanism. The case study and simulation evaluations illustrate the capability of our proposed approach.