Energy and climate change represent significant factors in global security. Atmospheric carbon dioxide levels, while global in scope, are influenced by pore-scale phenomena in the subsurface. We are developing tools to visualize and investigate processes in pore network microfluidic structures that serve as representations of normally-opaque porous media. These structures enable, for example, visualization of water displacement from pore spaces by hydrophobic fluids, including carbon dioxide, in studies related to carbon sequestration. In situ fluorescent oxygen sensing methods and fluorescent cellulosic materials are being used to investigate processes related to terrestrial carbon cycling involving cellulolytic respiring microorganisms.
Nevada Nanotech Systems, Inc. (Nevada Nano) has developed a multi-sensor solution to Chemical, Biological, Radiological, Nuclear and Explosives (CBRNE) detection that combines the Molecular Property Spectrometer™ (MPS™)—a micro-electro-mechanical chip-based technology capable of measuring a variety of thermodynamic and electrostatic molecular properties of sampled vapors and particles—and a compact, high-resolution, solid-state gamma spectrometer module for identifying radioactive materials, including isotopes used in dirty bombs and nuclear weapons. By conducting multiple measurements, the system can provide a more complete characterization of an unknown sample, leading to a more accurate identification. Positive identifications of threats are communicated using an integrated wireless module. Currently, system development is focused on detection of commercial, military and improvised explosives, radioactive materials, and chemical threats. The system can be configured for a variety of CBRNE applications, including handheld wands and swab-type threat detectors requiring short sample times, and ultra-high sensitivity detectors in which longer sampling times are used. Here we provide an overview of the system design and operation and present results from preliminary testing.
The potential for the use of biological agents by terrorists is a real threat. Two approaches for antibody-based detection
of biological species are described in this paper: 1) The use of microbead arrays for multiplexed flow cytometry
detection of cytokines and botulinum neurotoxin simulant, and 2) a microfluidic platform for capture and separation of
different size superparamagnetic nanoparticles followed by on-chip fluorescence detection of the sandwich complex.
These approaches both involve the use of automated fluidic systems for trapping antibody-functionalized microbeads,
which allows sample, assay reagents, and wash solutions to be perfused over a micro-column of beads, resulting in faster
and more sensitive immunoassays. The automated fluidic approach resulted in up to five-fold improvements in
immunoassay sensitivity/speed as compared to identical immunoassays performed in a typical manual batch mode. A
second approach for implementing multiplexed bead-based immunoassays without using flow cytometry detection is
currently under development. The goal of the microfluidic-based approach is to achieve rapid (<20 minutes),
multiplexed (≥ 3 bioagents) detection using a simple and low-cost, integrated microfluidic/optical detection platform.
Using fiber-optic guided laser-induced fluorescence, assay detection limits were shown to be in the 100's of picomolar
range (10's of micrograms per liter) for botulinum neurotoxin simulant without any optimization of the microfluidic
device or optical detection approach.
Field-portable sensor system are currently needed for the detection and characterization of biological pathogens in the environment. Nucleic acid analysis is frequently the method of choice for discriminating between pathogenic and non-pathogenic bacteria in environmental samples, however standard protocols are difficult to automate and current microfluidic devices are not configured to analyze environmental samples. In this paper, we describe an automated DNA sample processing system and demonstrate its use for the extraction of bacterial DNA form water and sediment samples. Two challenges in environmental sample analysis are the need to process relatively large sample volumes in order to obtain detectable quantities of DNA present at low concentrations, and the need to purify DNA form a complex sample matrix for downstream detection. These problems are addressed by using sequential injection fluid handling techniques for precise manipulation of the required volumes, and renewable separation columns for automatically trapping and releasing microparticles that are used for sample purification. The renewable microcolumns are used for both bacterial cell concentration and DNA purification. The purified bacterial DNA is then amplified using an on-line PCR module in order to produce detectable quantities of the target DNA.
Automated microfluidic analysis has historically been carried out by flow injection analysis techniques. Sequential injection analysis represents a more versatile method for automated fluid handling. We have explored the use of sequential injection analysis for performing microcolumn separations. These separations can be used as part of a microanalytical procedure, or for sample preparation. In addition, with detection of retained species on the microcolumn, sequential injection separation represents a technique for sensing. Recently, it has been demonstrated that sequential injection separation can be carried out with renewable separation columns--the beads with interactive surfaces can be delivered to the microcolumn, used for processing the sample, and discarded after each measurement. Delivery of new beads for each measurement provides a method for renewable surface separation and renewable surface sensing. Applications in environmental analysis and bioanalytical chemistry will be presented.
In this paper we will demonstrate chemometric approaches that can be applied to data from a well-understood polymer- coated acoustic wave vapor sensor array to extract information about the properties of detected vapors, whether that vapor was in the training set or not. Derivation of the approach and simulation using `synthetic' data are presented.
The ability to collect broadband spectroscopic information about chemical analytes is highly desirable. We report on a technique that combines chemically selective coatings and optical spectroscopy. A 1-meter fiber 150 micrometers in diameter has approximately 5 cm2 surface area. This entire surface is used by incorporating selective moieties into the fiber cladding. The Large-Area Chemical Sensor concept for chemical sensing and measurement is based on a combination of three techniques. Specifically, it uses: (1) optical waveguides as the sensor substrate, (2) selectively adsorbing or absorbing materials to concentrate the target materials, and (3) spectroscopic interrogation for verification and quantification. The concept has been demonstrated for an iodine sensor by co-polymerizing methyl, phenyl siloxane into di-methyl siloxane. The phenyl group forms a charge-transfer complex with iodine which has an absorption at ca. 500 nm. Fused silica is the waveguide core. This system provides sensitivities in the 10-ppm range. The concept has been implemented into a prototype field iodine sensor unit. Work on the sensor concept continues with the goal of improving the sensitivity by allowing each photon multiple opportunities to interact with a target molecule.
Many chemical sensors rely on a sorbent material to collect and concentrate analyte molecules at the sensor's surface where they can be detected. Ideally, this sorbent material will impart the chemical sensor with both sensitivity and selectivity for the target species. If the sensor is to be reversible, then the species must also desorb from the material or be actively removed by some process such as catalytic destruction. Polymer materials offer many attractive features for chemical sensing. Organic compounds are readily sorbed in a reversible fashion, selectivity can be altered by varying the chemical structure, and polymer materials can be processed into thin films. In this paper, we discuss the factors that govern the sorption of vapors by organic polymers. The approach described has been applied in the past for the design and selection of polymers for acoustic wave sensors. However, the principles apply equally well to the sorption of vapors by polymers used on optical chemical sensors. For example, the polymer could be applied as a thin film to a planar waveguide as the cladding along the length of an optical fiber, or to the end of an optical fiber. Species sorbed into the polymer could then be detected by a change in an optical signal.
A sensor system using surface acoustic wave (SAW) vapor sensors has been fabricated and tested against hazardous organic vapors, simulants of these vapors, and potential background vapors. The vapor tests included two- and three-component mixtures, and covered a wide relative humidity range. The sensor system was compared of four SAW devices coated with different sorbent materials with different vapor selectivities. Preconcentrators were included to improve sensitivity. The vapor experiments were organized into a large data set analyzed using pattern recognition techniques. Pattern recognition algorithms were developed to identify two different classes of hazards. The algorithms were verified against a second data set not included in the training. Excellent sensitivity was achieved by the sensor coatings, and the pattern recognition analysis, and was also examined by the preconcentrators. The system can detect hazardous vapors of interest in the ppb range even in varying relative humidity and in the presence of background vapors. The system does not false alarm to a variety of other vapors including gasoline, jet fuel, diesel fuel and cigarette smoke.
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