ZnO thin film surface acoustic wave based lab-on-a-chip

Lab-on-a-chip (LOC) is one of the most important microsystem applications with promise for use in microanalysis, drug development, diagnosis of illness and diseases etc. LOC typically consists of two main components: microfluidics and sensors. Integration of microfluidics and sensors on a single chip can greatly enhance the efficiency of biochemical reactions and the sensitivity of detection, increase the reaction/detection speed, and reduce the potential cross-contamination, fabrication time and cost etc. However, the mechanisms generally used for microfluidics and sensors are different, making the integration of the two main components complicated and increases the cost of the systems. A lab-on-a-chip system based on a single surface acoustic wave (SAW) actuation mechanism is proposed. SAW devices were fabricated on nanocrystalline ZnO thin films deposited on Si substrates using sputtering. Coupling of acoustic waves into a liquid induces acoustic streaming and motion of droplets. A streaming velocity up to ∼ 5cm/s and droplet pumping speeds of ∼lcm/s were obtained. It was also found that a higher order mode wave, the Sezawa wave is more effective in streaming and transportation of microdroplets. The ZnO SAW sensor has been used for prostate antigen/antibody biorecognition systems, demonstrated the feasibility of using a single actuation mechanism for lab-on-a-chip applications. © 2010 Materials Research Society.

ZnO based SAW and FBAR devices for lab-on-a chip applications

Acoustic wave devices were fabricated incorporating ZnO films deposited using both a standard rf magnetronand a novel High Target Utilisation (HiTUS) Sputtering System. Our results demonstrated the feasibility of using a single SAW-based actuation mechanism for both microfluidics and sensing. To further improve the sensitivity of our bio-sensors we have also investigated the use of Thin Film Bulk Acoustic Resonators.

Evaluation of manufacturing techniques for a minifluidics demonstrator system

A multi-disciplinary team based at Heriot-Watt University and other Universities has been set up to tackle the design and manufacturing of lab-on-a-chip for industries as one of the demonstrators of the EPSRC Grand Challenge project "3D-Mintegration". The team focuses on the analysis of foetal genetic material extracted from maternal blood as a smart alternative to invasive prenatal testing such as amniocentesis. The first module of the microsystem envisaged achieves a separation of blood cells from plasma. This system permits the testing of different manufacturing techniques.

Application of neural networks to the ranking of perinatal variables influencing birthweight.

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mother's body-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

Electroosmotic flow analysis of a branched U-turn nanofluidic device.

In this paper, we present the analysis of electroosmotic flow in a branched -turn nanofluidic device, which we developed for detection and sorting of single molecules. The device, where the channel depth is only 150 nm, is designed to optically detect fluorescence from a volume as small as 270 attolitres (al) with a common wide-field fluorescent setup. We use distilled water as the liquid, in which we dilute 110 nm fluorescent beads employed as tracer-particles. Quantitative imaging is used to characterize the pathlines and velocity distribution of the electroosmotic flow in the device. Due to the device's complex geometry, the electroosmotic flow cannot be solved analytically. Therefore we use numerical flow simulation to model our device. Our results show that the deviation between measured and simulated data can be explained by the measured Brownian motion of the tracer-particles, which was not incorporated in the simulation.

Guided growth of neurons and glia using microfabricated patterns of parylene-C on a SiO2 background.

This paper describes a simple technique for the patterning of glia and neurons. The integration of neuronal patterning to Multi-Electrode Arrays (MEAs), planar patch clamp and silicon based 'lab on a chip' technologies necessitates the development of a microfabrication-compatible method, which will be reliable and easy to implement. In this study a highly consistent, straightforward and cost effective cell patterning scheme has been developed. It is based on two common ingredients: the polymer parylene-C and horse serum. Parylene-C is deposited and photo-lithographically patterned on silicon oxide (SiO(2)) surfaces. Subsequently, the patterns are activated via immersion in horse serum. Compared to non-activated controls, cells on the treated samples exhibited a significantly higher conformity to underlying parylene stripes. The immersion time of the patterns was reduced from 24 to 3h without compromising the technique. X-ray photoelectron spectroscopy (XPS) analysis of parylene and SiO(2) surfaces before and after immersion in horse serum and gel based eluant analysis suggests that the quantity and conformation of proteins on the parylene and SiO(2) substrates might be responsible for inducing glial and neuronal patterning.

Spinning off a semiconductor company from University premises -The story of Camsemi

The spinning off of Cambridge Semiconductor Ltd (Camsemi) from the High Voltage Microelectronics Lab at Cambridge University is discussed. The technology originated from Cambridge University and was subsequently developed and commercialized as PowerBrane by Camsemi. The paper also discusses the business model and the enabling financial factors that led to the formation of Camsemi as a fables IC company, including access to seed funding from University and the subsequent investments of venture capital in several rounds. © 2011 IEEE.