The application of micro-plate dynamics on monitoring cell property

The paper presents a novel biosensing method of monitoring cell properties using the information derived from the dynamics of micro-scale plates. Micro cantilevers have been widely applied as mechanical biosensors. In dynamic sense, cantilever is considered as 1 dimensional whereas plate is a 2 dimensional structure. In this paper we provide the first analytical solution to the dynamics of distributed mass loaded microplate in submerged fluid. In a further step, we propose to derive the dynamical infomation of the micro plate and use it to infer the spatial information of the cells when monitoring the cell growth on the plate

Dynamic analysis of submerged microscale plates: the effects of acoustic radiation and viscous dissipation

The aim of this paper is to study the dynamic characteristics of micromechanical rectangular plates used as sensing elements in a viscous compressible fluid. A novel modelling procedure for the plate–fluid interaction problem is developed on the basis of linearized Navier–Stokes equations and no-slip conditions. Analytical expression for the fluid-loading impedance is obtained using a double Fourier transform approach. This modelling work provides us an analytical means to study the effects of inertial loading, acoustic radiation and viscous dissipation of the fluid acting on the vibration of microplates. The numerical simulation is conducted on microplates with different boundary conditions and fluids with different viscosities. The simulation results reveal that the acoustic radiation dominates the damping mechanism of the submerged microplates. It is also proved that microplates offer better sensitivities (Q-factors) than the conventional beam type microcantilevers being mass sensing platforms in a viscous fluid environment. The frequency response features of microplates under highly viscous fluid loading are studied using the present model. The dynamics of the microplates with all edges clamped are less influenced by the highly viscous dissipation of the fluid than the microplates with other types of boundary conditions

Vibration analysis of submerged micro rectangular plates with distributed mass loading

This paper investigates the vibration characteristics of the coupling system of a microscale fluid-loaded rectangular isotropic plate attached to a uniformly distributed mass. Previous literature has, respectively, studied the changes in the plate vibration induced by an acoustic field or by the attached mass loading. This paper investigates the issue of involving these two types of loading simultaneously. Based on Lamb's assumption of the fluid-loaded structure and the Rayleigh–Ritz energy method, this paper presents an analytical solution for the natural frequencies and mode shapes of the coupling system. Numerical results for microplates with different types of boundary conditions have also been obtained and compared with experimental and numerical results from previous literature. The theoretical model and novel analytical solution are of particular interest in the design of microplate-based biosensing devices

A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis

A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications

Computational fluid dynamics study of dusty air flow over NACA 63415 airfoil for wind turbine applications

Gulf and South African countries have enormous potential for wind energy. However, the emergence of sand storms in this region postulates performance and reliability challenges on wind turbines. This study investigates the effects of debris flow on wind turbine blade performance. In this paper, two-dimensional incompressible Navier-Stokes equations and the transition SST turbulence model are used to analyze the aerodynamic performance of NACA 63415 airfoil under clean and sandy conditions. The numerical simulation of the airfoil under clean surface condition is performed at Reynolds number 460×103, and the numerical results have a good consistency with the experimental data. The Discrete Phase Model has been used to investigate the role sand particles play in the aerodynamic performance degradation. The pressure and lift coefficients of the airfoil have been computed under different sand particles flow rates. The performance of the airfoil under different angle of attacks has been studied. Results showed that the blade lift coefficient can deteriorate by 28% in conditions relevant to the Gulf and South African countries sand storms. As a result, the numerical simulation method has been verified to be economically available for accurate estimation of the sand particles effect on the wind turbine blades

An investigation into the design of a device to treat haemorrhagic stroke

In this study, we present the design considerations of a device to assist in the potential treatment of hemorrhagic stroke with the aim of stopping blood from flowing out into brain tissue. We present and model three designs for the clinical scenarios when saccular aneurysms rupture in the middle cerebral artery in the brain. We evaluate and model these three designs using computer aided design software, SolidWorks, which allows the devices to be tested using finite element analysis and also enables us to justify that the materials chosen were suitable for potential use. Computational fluid dynamics modelling were used to demonstrate and analyse the flow of blood through the artery under conditions of normal and ruptured states. We conclude that our device could potentially be useful in the treatment of hemorrhagic stroke, and the modelling process is useful in assisting in determining the performance of our devices

Variable operation of a renewable energy-driven reverse osmosis system using model predictive control and variable recovery: Towards large-scale implementation

Powering Reverse Osmosis (RO) systems with Renewable Energy (RE) is essential for decarbonising water production. Integration of RE requires large-scale RO plants to operate efficiently using variable power. Nevertheless, variable operation (involving matching the RO load to available power without battery back-up) has only been implemented for small-scale systems. This paper presents a variable-speed operation technique suitable for large-scale RO systems using an optimised operational strategy and a Model Predictive Controller (MPC). The technique was validated using a laboratory test rig having comparable performance to large-scale systems. A dynamic plant model was used to design the operational strategy and control system. Several operational strategies were explored for varying the operating parameters according to power available from a RE source. An advanced control system based on MPC was designed and compared to a conventional Proportional-Integral-Differential controller. The results showed that operation at variable recovery with constant brine flowrate delivered the lowest specific energy consumption and widest operation range for a system with an isobaric pressure exchanger. The MPC controller improved the settling time for a 10% step-change in permeate flowrate by 47%. Moreover, it improved energy utilisation, giving a 2.35% increase in hourly permeate production for a defined power input time-series

Tissue morphology and gene expression characterisation of transplantable adenocarcinoma bearing mice exposed to fluorodeoxyglucose-conjugated magnetic nanoparticles

Fluorodeoxyglucose-conjugated magnetic nanoparticles, designed to target cancer cells with high specificity when heated by an alternating magnetic field, could provide a low-cost, non-toxic treatment for cancer. However, it is essential that the in vivo impacts of such technologies on both tumour and healthy tissues are characterised fully. Profiling tissue gene expression by semi-quantitative reverse transcriptase real-time PCR can provide a sensitive measurement of tissue response to treatment. However, the accuracy of such analyses is dependent on the selection of stable reference genes. In this study, we determined the impact of fluorodeoxyglucose-conjugated magnetic nanoparticles on tumour and non-tumour tissue gene expression and morphology in MAC16 adenocarcinoma established male NMRI mice. Mice received an injection of 8mg / kg body weight fluorodeoxyglucose-conjugated magnetic nanoparticles either intravenously in to the tail vein, directly into the tumour or subcutaneously directly overlying the tumour. Tissues from mice were sampled between 70 minutes and 12 hours post injection. Using the bioinformatic geNorm tool, we established the stability of six candidate reference genes (Hprt, Pgk1, Ppib, Sdha, Tbp and Tuba); we observed Pgk1 and Ppib to be the most stable. We then characterised the expression profiles of several apoptosis genes of interest in our adenocarcinoma samples, observing differential expression in response to mode of administration and exposure duration. Using histological assessment and fluorescent TUNNEL staining, we observed no detrimental impact on either tumour or non-tumour tissue morphology or levels of apoptosis. These observations define the underlying efficacy of fluorodeoxyglucose-conjugated magnetic nanoparticles on tumour and non-tumour tissue morphology and gene expression, setting the basis for future studies

Large extraordinary Hall effect in [Pt/Co]5/Ru/[Co/Pt]5 multilayer

This Brief Report presents giant extraordinary Hall effect (EHE) in the Ru-mediated antiferromagnetically coupled [Pt/Co]5/Ru/[Co/Pt]5 multilayers (MLs) compared with those MLs without the Ru spacer. The enhancement of the EHE is attributed to the strong Ru/Co interface scattering. Through the variation in the Pt layer thickness and the temperature, we determine the relation between the Hall voltage and the longitudinal resistivity. It is found that the conventional scaling analysis has difficulties in consistently interpreting our data

Prospects of wind power prediction and variable operation in optimizing wind-powered reverse osmosis operation

Reverse Osmosis (RO) is a dominant process in the desalination industry. However, concerns have been raised regarding its impact on the environment due to the dependency of commercial-scale plants on fossil fuels. Renewable Energy (RE) has been used in several studies to operate RO plants and decarbonize water production. However, the technology is either limited to small-scale plants, or large-scale plants that rely on a grid connection to meet the required water demand. This study is part of an international collaboration that aims to efficiently operate large-scale RO plants using wind energy and achieve the transition to fully sustainable RO. Variable-speed operation and modular operation are defined as strategies to operate the RO plant according to the available wind energy. As an initial step, this paper studies the combination of variable operation and wind-speed prediction in optimizing the operation of wind-powered RO. An Artificial Neural Network (ANN) was trained using a full year wind speed time-series to predict hourly average wind speed using a previously recorded 12-hour time series. The prediction exhibited high accuracy based on the regression analysis and would be implemented in the RO control system during the next stages of development. Wind speed prediction presents great potential for scheduling the startup/shutdown cycles of RO trains during modular operation. Currently, a pilot RO plant is being developed at Aston University for future testing. It is designed to deliver comparable operation to commercial RO plants by using commercial components arranged in a split feed flow configuration