4 resultados para micro-electron capture detection
em Digital Commons - Michigan Tech
Resumo:
A non-intrusive interferometric measurement technique has been successfully developed to measure fluid compressibility in both gas and liquid phases via refractive index (RI) changes. The technique, consisting of an unfocused laser beam impinging a glass channel, can be used to separate and quantify cell deflection, fluid flow rates, and pressure variations in microchannels. Currently in fields such as microfluidics, pressure and flow rate measurement devices are orders of magnitude larger than the channel cross-sections making direct pressure and fluid flow rate measurements impossible. Due to the non-intrusive nature of this technique, such measurements are now possible, opening the door for a myriad of new scientific research and experimentation. This technique, adapted from the concept of Micro Interferometric Backscatter Detection (MIBD), boasts the ability to provide comparable sensitivities in a variety of channel types and provides quantification capability not previously demonstrated in backscatter detection techniques. Measurement sensitivity depends heavily on experimental parameters such as beam impingement angle, fluid volume, photodetector sensitivity, and a channel’s dimensional tolerances. The current apparatus readily quantifies fluid RI changes of 10-5 refractive index units (RIU) corresponding to pressures of approximately 14 psi and 1 psi in water and air, respectively. MIBD reports detection capability as low as 10-9 RIU and the newly adapted technique has the potential to meet and exceed this limit providing quantification in the place of detection. Specific device sensitivities are discussed and suggestions are provided on how the technique may be refined to provide optimal quantification capabilities based on experimental conditions.
Resumo:
Routine bridge inspections require labor intensive and highly subjective visual interpretation to determine bridge deck surface condition. Light Detection and Ranging (LiDAR) a relatively new class of survey instrument has become a popular and increasingly used technology for providing as-built and inventory data in civil applications. While an increasing number of private and governmental agencies possess terrestrial and mobile LiDAR systems, an understanding of the technology’s capabilities and potential applications continues to evolve. LiDAR is a line-of-sight instrument and as such, care must be taken when establishing scan locations and resolution to allow the capture of data at an adequate resolution for defining features that contribute to the analysis of bridge deck surface condition. Information such as the location, area, and volume of spalling on deck surfaces, undersides, and support columns can be derived from properly collected LiDAR point clouds. The LiDAR point clouds contain information that can provide quantitative surface condition information, resulting in more accurate structural health monitoring. LiDAR scans were collected at three study bridges, each of which displayed a varying degree of degradation. A variety of commercially available analysis tools and an independently developed algorithm written in ArcGIS Python (ArcPy) were used to locate and quantify surface defects such as location, volume, and area of spalls. The results were visual and numerically displayed in a user-friendly web-based decision support tool integrating prior bridge condition metrics for comparison. LiDAR data processing procedures along with strengths and limitations of point clouds for defining features useful for assessing bridge deck condition are discussed. Point cloud density and incidence angle are two attributes that must be managed carefully to ensure data collected are of high quality and useful for bridge condition evaluation. When collected properly to ensure effective evaluation of bridge surface condition, LiDAR data can be analyzed to provide a useful data set from which to derive bridge deck condition information.
Resumo:
The biopharmaceutical industry has a growing demand and an increasing need to improve the current virus purification technologies, especially as more and more vaccines are produced from cell-culture derived virus particles. Downstream purification strategies can be expensive and account for 70% of the overall manufacturing costs. The economic pressure and purification processes can be particularly challenging when the virus to be purified is small, as in our model virus, porcine parvovirus (PPV). Our efforts are focused on designing an easy, economical, scalable and efficient system for virus purification, and we focused on aqueous two-phase systems. Industry acceptable standards for virus vaccine recovery can be as low as 30% due to demand of high final titer, virus transduction inhibitors and presence of empty or defective virus capsids as impurities. We have overcome these shortcomings by recovering a high 64% of infectious virus using an aqueous two-phase system. We used high molecular weight polymer and citrate salt to achieve a good yield and eliminated the major contaminant bovine serum albumin. Viruses are also studied for ensuring pure and safe drinking water. Low pressure microfiltrations are continuously being investigated for water filters as they allow high permeate flux and low fouling. Viruses such as PPV are small enough to pass through the microporous membranes. Control of viruses in water is crucial for public health and we have designed an affinity based membrane filter to capture virus. Nanofibers have a high surface to volume ratio providing a highly accessible surface area for virus adsorption. Chitosan an insoluble, biocompatible and biodegradable polymer was used for adsorbing trimer peptide WRW. About 0.2 μmoles of cysteine terminal WRW peptide was conjugated to amine terminal chitosan using maleimide conjugation chemistry. We achieved 90-99% virus removal from water adjusted to a neutral pH. The virus removal from affinity based chitosan was attributed to electrostatic and hydrophobic driven binding effect.
Resumo:
Vapor sensors have been used for many years. Their applications range from detection of toxic gases and dangerous chemicals in industrial environments, the monitoring of landmines and other explosives, to the monitoring of atmospheric conditions. Microelectrical mechanical systems (MEMS) fabrication technologies provide a way to fabricate sensitive devices. One type of MEMS vapor sensors is based on mass changing detection and the sensors have a functional chemical coating for absorbing the chemical vapor of interest. The principle of the resonant mass sensor is that the resonant frequency will experience a large change due to a small mass of gas vapor change. This thesis is trying to build analytical micro-cantilever and micro-tilting plate models, which can make optimization more efficient. Several objectives need to be accomplished: (1) Build an analytical model of MEMS resonant mass sensor based on micro-tilting plate with the effects of air damping. (2) Perform design optimization of micro-tilting plate with a hole in the center. (3) Build an analytical model of MEMS resonant mass sensor based on micro-cantilever with the effects of air damping. (4) Perform design optimization of micro-cantilever by COMSOL. Analytical models of micro-tilting plate with a hole in the center are compared with a COMSOL simulation model and show good agreement. The analytical models have been used to do design optimization that maximizes sensitivity. The micro-cantilever analytical model does not show good agreement with a COMSOL simulation model. To further investigate, the air damping pressures at several points on the micro-cantilever have been compared between analytical model and COMSOL model. The analytical model is inadequate for two reasons. First, the model’s boundary condition assumption is not realistic. Second, the deflection shape of the cantilever changes with the hole size, and the model does not account for this. Design optimization of micro-cantilever is done by COMSOL.