Micro- and nanosystems for biology and medicine

The development of new tools and instruments for biomedical applications based on nano- (NEMS) or microelectromechanical systems technology (MEMS) are bridging the gap between the macro- and the nano-world. The well mastered microtechnique allows controlling many parameters of these instruments, which is essential for conducting reproducible and repeatable experiments in the life sciences. Examples are multifunctional scanning probe sensors for cell biology, an arthroscopic scanning force microscope for minimally invasive medical interventions and a nanopore sensor for single molecule experiments in biochemistry. This paper reviews some of the activities conducted in a fruitful interdisciplinary collaboration between physicists, engineers, biologists and physicians

Patterns for Analogous Representation

Analogous Representation patterns offer a way to express entities and their relationships in an analogous fashion. Redundant but useful information seems more natural and/or friendly for human beings to understand than that has been handled in conventional Information Technologies (hereafter, IT) systems, can be captured and represented in a consistent way

Evaporation based micro pump integrated into a scanning force microscope probe

A micro pump was integrated into a scanning force microscope probe for circulating liquid through its hollow cantilever and tip. The interior cross section of the cantilever was 2.25 μm × 3.75 μm. All fluidic parts were made of SiO2, while the tip apex was made of Si3N4. The key fabrication techniques were silicon wafer bonding and wet-oxidation. The pumping mechanism was relying on the enhanced evaporation at an enlarged water/air interface at the exit of the microchannel. Capillary forces continuously wetted this interfacial area, thus drawing the liquid through the system. At room temperature, a pump rate of 11 pl s−1 was experimentally evaluated. The observed temperature dependence of the pump rate could be qualitatively understood by a plain model calculation